Berkeley City Council
July 29, 2025

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The City could consider a robust internal borrowing policy. There will always be some chanc e that Berkeley could find that it needs access to more financial resources than are available in its reserves.

GFOA’s research suggests that interfund borrowing could be a practical “last line of defense” in emergency circumstances. Some other funds might be able to make short-term loans to the general fund in case of an emergency. The City could develop policies to provide the flexibility to use these borrowing tools while also providing the necessary guidelines and limitations to ensure that borrowing oc curs in a fiscally prudent manner.

Berkeley might consider if a policy could recognize internal borrowing’s role as a supplementary risk management tool. A policy would “pre -position” the City to better respond to an extreme financial catastrophe. A policy could address the following points:
• The rationale for using internal borrowing (reserves may not be able to handle every possible contingency).
• When internal borrowing may be used (if reserves are ever exhausted by an extreme event). • Differentiate between short-term (to be paid back within the same fiscal year) and long -term borrowing.
• How the interest on the borrowing will be calculated (can have multiple alternatives to be determined on a case-by-case basis); and
• General repayment terms (e.g., interest only, fully amortized, duration, etc.).

GFOA’s analysis has its limits. It is impossible for any risk analysis to be completely comprehensive of all considerations facing the City. Appendix 1 to this report lists the important limitations of this analysis.

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Section 2 - Introduction
“Reserves” are the portion of a local government’s fund balance that are available to respond to the unexpected. Reserves are the cornerstone of financial flexibility, sustainability, and continuity of existing service levels. Reserves provide a government with options to respond to emergencies and provide a buffer against shocks and other forms of risk. Managing reserves, though, can be a challenge. Foremost is the question of how much money to maintain in a general fund reserve. How much is enough and when does a reserve become too much?
The City of Berkeley has been considering the implication that various types of extreme events, like natural disasters, could have on the City government’s financial condition , particularly its reserve l evels for the general fund. The City engaged the GFOA to produce a recommendation to help it decide the appropriate reserve level for the general fund, given the risks from extreme events. GFOA is a non-profit association of more than 21,000 state and loca l government finance professionals and elected officials from across North America. A key part of GFOA’s mission is to promote best practices in public finance, including reserve policies. The analysis by GFOA also shed light on the potential broader econ omic losses to the community, not just City government.

GFOA’s approach to reserves does not suppose “one -size-fits-all.” Ideally, a local government’s reserve strategy will be customized to the risk that the local government faces. For example, GFOA’s “B est Practice” on general fund reserves recommends that general-purpose governments maintain reserves of no less than two months of regular operating revenues or regular operating expenditures (i.e., reserves equal to about 16.7 percent of revenues or expenditures), but that local governments should determine a reserve target that is most appropriate for their circumstances.7 Therefore, GFOA worked with the City to conduct an analysis of the risks influenc ing the need for reserves as a hedge against uncerta inty and loss.

A “risk” is defined as the probability and magnitude of a loss, disaster, or other undesirable event. 8 The GFOA’s framework of risk assessment is based on the risk management cycle: identify risk; assess risk; identify risk mitigation approaches; assess expected risk reduction; and select and implement mitigation methods. Our analysis focuses primarily on risk retention, or using reserves, to manage risk. However, our analysis also encourages the City to think about how other risk management methods might alleviate the need to hold larger reserves. In other words, can the City manage its risks in some other way besides holding reserves? For example, could insurance or borrowing strategies complement the City’s reserve strategy? A thorough ex amination of the risk factors should lead to a range of desired reserves and improve the City’s understanding of its overall risk profile. A risk-aware analysis helps the City stress test its reserve strategy.

7 GFOA Best Practice. “Appropriate Level of Unrestricted Fund Balance in the General Fund.” GFOA. 2009. 8 Definition of risk taken from: Douglas W. Hubbard. The Failure of Risk Management: Why It’s Broken and How to Fix It. John Wiley and Sons, Inc. Hoboken, New Jersey. 2009.

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As a first step to this project, GFOA conducte d a review of the risk factors influencing the amount of reserves a municipal government should hold.9 This review identified the risks on Exhibit 2.1 as the most salient risks to Berkeley’s general fund reserve.

Exhibit 2.1 – Primary Risk Factors that Influence Reserve Levels for Berkeley

Revenue source stability, particularly as it relates to the potential for revenue decline from an economic downturn
Vulnerability to extreme events and public safety concerns, with emphasis on:
• Wildfires
• Recessions and revenue volatility
• Earthquakes
• High winds
• Tsunamis
• Pensions
• Other hazards, such as infectious disease

The next section gives an overview of how we analyze these risks and what you can expect to see in the rest of this report.

9 The risk factors and basic review method were developed and published in the GFOA publication: Shayne C.

Kavanagh. Financial Policies. (Government Finance Officers Association: Chicago, IL) 2012.

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Section 3 - The Approach to Uncertainty
The accomplished forecasting scientist, Spyros Makridakis, suggests a “Triple-A” approach for dealing with highly uncertain phenomena.10

1. Accept. First, we must accept that we are subject to uncertainty . For example, the severity and timing of an earthquake is unpredictable. Berkeley could go years without experiencing a serious earthquake or one could occur next month!

2. Assess. Next, we must assess the potential impact of the uncertainty , with history providing a useful reference point . The experie nces of other local governments are also a good reference point. For example, we used the historical experiences of Berkeley and other relevant municipalities to estimate the potential impact of future extreme events . However, historical experiences are not perfectly predictive of the future. That leads us to the next point…

3. Augment. The range of uncertainty we face will almost always be greater than what we initially assess it to be. Therefore, we must augment our understanding of risk beyond what our historical experiences show us. For example, very few people saw the 2008 Great Recession coming or thought it could be as bad as it was. They were unprepared for this historically unprecedented recession. We can augment our understanding of risk using a techn ique called “Probability Management.”11 Probability Management is an application of modern information processing technology that allows us to simulate thousands of potential events (e.g., floods, recessions, etc.) so that we can observe the probability of events of various magnitudes coming to pass. The statistical technique that Probability Management is based on is called “Monte Carlo analysis .” This technique was established in the late 1940s, but until very recently required special computers and software to use. Modern information technology has made Monte Carlo analysis accessible to anyone with a personal computer.

To use Probability Management, we express any given type of extreme event as a range of possibilities that the City might experience. This range is called a “distribution.” A distribution is a shape that signifies how frequently the City might expect to experience a certain type of event and/or how severe the event might be.

The most common type of distribution is called the “normal distri bution,” more popularly known as the “bell curve.” Many phenomena fit a bell curve. To help us understand how to read a distribution, we can start with an example that is related to everyday life: the height of American men.

10 See: Spyros Makridakis, Robin Hogarth, and Anil Gaba. Dance with Chance: Making Luck Work for You. (Oneworld Publications: Oxford, England). 2009.
11 The discipline of “Probability Management” was developed by Dr. Sam Savage, author of The Flaw of Averages .

You can learn more about Probability Management at probabilitymana gement.org.

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Exhibit 3.1 shows a bell curve for the height of American men. The horizontal axis of Exhibit 3.1 represents height. The vertical axis represents frequency. The most common height is 5’9”, so it is shown at the top of the curve. Much taller men, like NBA centers, would be found on the right-hand side of the curve. Very short men would be found on the left.

Exhibit 3.1 – The Normal Distribution for American Men

Frequency

Height➔

The normal distribution can help analyze risk. To illustrate, the severity of an economic downturn is roughly normally distributed. A
few downturns are slight, a few
are severe, but most are closer to
average.

Another type of distribution we
use in our ana lysis is an
asymmetrical distribution,
shown in Exhibit 3.2 .

Earthquakes fit an asymmetrical
distribution. Exhibit 3.2 shows
that tremors are the most
common. Full-fledged
earthquakes are relatively rare.

The distribution is
“asymmetrical” because the
frequency with which we will
experience these events are not evenly distributed around the middle of the distribution. Put another way, there are far more tremors that are smaller than the “average” earthquake. Yet, there are far fewer earthquakes (“the big one”) that are larger than the average earthquake.

Exhibit 3.2 – Sample Asymmetrical Distribution

Frequency
of Quake

Severity of Quake ➔
5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60%
Earthquake
Tremor
"The Big One"
Very Short Very Tall
Average
5’9”
55

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Expressing Berkeley’s vulnerability as distributions allows us to calculate the probability that an event of a given magnitude will come to pass. When we associate a dollar amount with that event, we can estimate the probability or chance that Berkeley will need to have a given amount of money on-hand to respond.

Exhibit 3.3 is not a distribution but is a type of graphic we will use in this report. It is called a “cumulative probability chart.” It shows the economic losses to the entire Berkeley community from earthquakes over the course of 10 years. Earthquakes are rare events, so over a ten-year period there is a chance that there will be no earthquakes at all. Hence, the blue line intersects the vertical axis at about 50% (there is about a 50% chance of no earthquake). We then see the blue line go up and to the right from the vertical axis.

This means that the chance of larger and larger losses becomes increasingly remote. To illustrate, the blue line intersects 70% at about $300 million. This means there is a 70% chance that total economic losses are $300 million or less (or a 30% chance that losses will be more). The blue line insects 80% at $670 million, which means there is an 80% chance that losses will be less than that (or a 20% chance that losses will be more).

Another type of chart we will show is a loss exceedance curve. It is another way of look ing at the same concept as we saw in Exhibit 3.3. Exhibit 3.4 shows the loss exceedance curve for the same earthquake data. It just pr esents it in an inverse way. So, the 20% point in the vertical axis is $670 million because there is a 20% chance that damages will be more than. Exhibit 3.4 showed there was an 80% of damages being less.

Exhibit 3.3 – Cumulative Chance of Economic Losses to Berkeley Community from Earthquakes over 10 Years
Chance that
damages will be

EQUAL TO OR
LOWER THAN the
amount shown on
the graph

Damages in Millions of Dollars

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Both cumulative probability charts and loss exceedance curves are commonly used when quantifying risk.

It is important for the reader of this report to understand that there is never one single, objectively best amount of reserves to hold. The amount of reserves the City will want to hold will partially be a function of the City’s willingness to take on risk. If City officials are willing to take on risk, they might opt for lower reserves and spending more money on current services. If officials are more risk averse, they might opt for higher reserves. GFOA’s recommendations are informed by where reserves appear to provide the best value or “bang for the buck.” The spot on a cumulative probability chart, like Exhibit 3.3, before where the line begins to flatten out is usually where the best bang for the buck lies.

In Section 4, we cover revenue instability owing to economic downturns. In Section 5 of this report, we will review the City’s primary risks posed by extreme events, including wildfires, earthquakes, tsunamis, and more . Section 6 reviews secondary risk factors that have le ss weighty implications for the City’s reserve strategy. We include Section 6 to highlight the full range of risks that were considered, even if some of them did not seem to present as clear and present a threat to the City’s general fund reserve.

After we analyze the individual risks, in Section 7, we will consider the risks holistically. This section will:
• Consider the risks over a ten-year period. This provides a more complete perspective on potential vulnerability and how to use reserves. For example, the numbers shown in Exhibit 3.3 pertain just to one year. The potential losses are much greater over a ten-year period. • Consider the potential occurrence of any of the risks we analyzed to occur at the same time.

Obviously, if they did occur at the same time, the stress on the City’s reserves would be compounded.

Exhibit 3.4 Loss Exceedance Curve for of Economic Losses to Berkeley Community from Earthquakes over 10 Years
Chance that
damages will be

EQUAL TO OR
MORE THAN the
amount shown on
the graph

Damages in Millions of Dollars
0%
10%
20%
30%
40%
50%
60%
$0 $2,000 $4,000 $6,000 $8,000
Millions

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Section 4 - General Fund Revenue Volatility and Pension Risk An important risk for any local government is revenue volatility owing to downturns in the economy.

Reserves can be used to help a local govern ment make a “soft landing” in the event of a revenue downturn. In this section of the report, we will analyze the City’s vulnerability to revenue downturns.

For the purposes of our analysis, we divided the City’s revenues into the categories shown in Exhibit 4.1.

Property taxes are the most important single source, as you can see in Exhibit 4.1. Immediately following Exhibit 4.1, we will analyze the risk the City faces in each category.

Exhibit 4.1 – Relative Importance of City Revenues, based on 2023 Estimated Actuals Revenue % of Total
Taxes
Property Tax 38%
Sales Taxes 7%
Real Property Transfer Tax 12%
Business License Tax 10%
Utility Users Fee 7%
All Other Taxes 3%
All other revenue 22%
TOTAL 100%

Before we examine each individual revenue source, let’s make a note of Berkeley’s historical population growth. The City grew from 103,000 people in 2000 to 119,000 people as of the 2020 US Census, which is about a 15% increase over the period. The increase appears to steady over this period, as th e 2010 population was 113,000. Our analysis starts in 1999 to capture the impact of two recessions: the 2001 “dot.bomb recession” and 2008 “Great Recession.” The City appears to have experienced a small bump in population growth right around the time of th e Great Recession. It could be that the bump in growth offset at least some of the revenues losses the City would have otherwise experienced from the 2008 Great Recession. Therefore, we converted all historical revenues to per-capita figures for our analysis and all figures presented are per capita unless otherwise noted. Note that we do not consider the COVID-19 recession to be as useful an analogue as the two recessions mentioned above. This is because that recession was not a result of conventional econ omic causes and behaved much differently than past recessions. For example, the COVID recession featured a record decline followed by record recovery). This does not mean we ignored COVID. Risk from unconventional sources, like a pandemic, is addressed in a later section of this report.

Below we will briefly review key, relevant features about the volatility of each revenue shown in Exhibit

4.1. The purpose of this section is to be clear about the assumptions that go into our simulation of the City’s revenue volatility in the face of recessions. Before we dive into the details, we should note that the year-over-year percent changes we describe below are not necessarily the chance from one fiscal year to the next. Rather, we examined monthly data to find th e worst 12 month decline in each revenue. The reason is that the City’s fiscal year is an arbitrary period that is not related to the performance of the

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economy. This might obscure the full impact of a recession on revenue. For example, imagine there is recession lasting 12 months. It starts 6 months into a fiscal year and ends six months into the next fiscal year. Each fiscal year would only reflect half of the recession, thereby obscuring the total magnitude of the revenue loss.

Property Taxes
Property taxes are a stable revenue for Berkeley. They have exhibited consistent year -over-year growth since 1999. Of course, the 2008 recession featured a popping property price bubble that was felt across much of the world. Even so, during the entire length of the Great Recession Berkeley’s property tax growth merely slowed down for three years – around 3% annual growth, compared an average of 7% annual growth for all other years, 1999 to 2018. That said, we should not discount the possibility that future recessions could result in declining property values and property tax revenues. In fact, GFOA’s examination of recessions before 1999 shows that housing prices have declined during some of these recessions.

So, to model risk we looked at the decline during the Gre at Recession and found that the single worst continuous 12-month performance was a 5% decline in property tax revenue. We took this as emblematic of the possibility of future severe recessions. During the 2001 recession, property taxes grew for Berkeley.

This represents the possibility that during a relatively mild recession, like 2001’s, property tax revenue could go up. The 2008 recession is the worst recession, in terms of GDP 12 decline since World War II whereas the 2001 recession was one of the mildest. Hence, we can use these two recessions rough “boundaries” on the possibilities for future recessions.13 In our simulation we did account for the fact that the 2008 recession was unusually weighted towards losses in real estate. This was done to avoid overestimating the vulnerability of property taxes to recessions. We looked at how much property values declined, nationally, during a past, more “average” recession and compared that to what happened in 2001 and 2008. This “average” price decline was not exact ly in between 2001 and 2008 but was skewed closer to 2001. We included this skew in our simulation.

Finally, it is worth noting that Berkeley does not have a material risk from concentration of the tax base in one or few taxpayers. An example of this risk would be if a small municipality has a large industrial property, where that property makes up a large portion of the tax base – if the factory were to close, then it would have a big impact on the tax base. Fortunately, Berkeley does not appear to have such a risk. The taxpayer with the highest assessed value is 742 Grayson Owver LLC, whose property comprises less than 1% of the City’s assessed value.

Sales Taxes
Sales taxes have a reputation for being more responsive to economic downturns than property tax and this is true in Berkeley. Sales taxes declined by 7% during the 2001 recession and the worst year-over-year decline during the 2008 recession was 12%. When it comes to COVID-19, the federal government provided

12 Gross domestic product, a standard measure of national economic activity. 13 Our simulation method does not treat these as firm boundaries. Rather there were about ten recessions since World War II, the Great Recession was the worst, the 2001 recession the mildest which puts them at the 10 th and 90th percentile. This leaves room for even worse or even milder recessions than these two in our simulations.

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financial aid to individual citizens during the pandemic, beyond what is normal for an economic downturn.

Hence, we should not take 2019 and the subsequent COVID -19 experience as representative of future possible downturns. We used the 2001 and 2008 recessions as our boundaries for the analysis.

Real Property Transfer Tax
The real property transfer tax has proven a volatile revenue for Berkeley. It declined around 7%, year- over-year, during the 2001 recession, which was not that much different from other revenues. However, during the Great Recession, the revenue dropped an astounding 44% year-over-year. That said, the 2008 recession was uniquely driven by difficulties in the property market. Hence, the 44% decline might represent a particularly bad outcome. For this reason, we adjusted the model for potential skew, like we did for the property tax.

Business License Tax
The business license tax’s vulnerability to recessions is not as clear cut as the other revenues we have examined. Revenue from the tax is largely based on gross receipts of local businesses, which suggests that there should be some vulnerability to rec essions. However, when we examine the 2001 recession there was only a 2% decline in the early part of the recession. The 2008 Great Recession is more complicated because, according to the City’s 2008 financial report, a correction to a miscoding in City revenues resulted in about $800,000 in increased annual revenues. Presumably, this would have offset at least some of the decreases we might have otherwise observed during the recessio n. However, even backing out this additional revenue, it does not appear that there was a large decline in this revenue during the Great Recession.

To provide an additional perspective, we also looked at what happened to this revenue during COVID-19.

Though COVID was not a conventional recession in the way that we are defining it in this analysis (non - conventional risks, like COVID, are addressed later in this report), it does demonstrate what an economic dislocation could do to this revenue. In 2021, the revenue declined about 15% year over year from 2020.

Because COVID was the sharpest economic decline since World War 2 and the fastest recover y, it does not seem wise to use a 15% decline as an analogue for future recessions. Nevertheless, this experience does suggest that declines are possible. To make better use of the COVID experience we might consider that the largest annual quarter to quarter decline in national GDP during COVID was 9.5%. This compares to the worst quarterly decline in GDP during the Great Recession of 8.4%. The worst total annual loss in GDP during COVID and during the Great Recession was somewhat similar. These two data points suggest that because GDP loss was somewhat less severe during the Great Recession that assuming a tax loss somewhat less than the COVID experience could be a reasonable assumption. We used a 10% decline to avoid the risk of projecting too much of the COVID experience onto a conventional recession. The worst decline we could find for the City during the Great Recession was 6.5%.

Utility Users Fees
Perhaps unsurprisingly, utility users fees are a stable revenue source because demand for utility services does not change much during a recession. The total decline was close to 6% in each recession.

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All Other Taxes
When we look at all remaining City taxes (i.e., hotel tax plus a host of much smaller taxes), we see year- over-year declines of about 15% during both the 2001 and Great Recessions.

All Other (Non-Tax) Revenues
When we look at all other non -tax revenues, we saw relatively little decline during the Great Recession (3% year over year decline), but a larger decline during the 2001 recession (12%). This may be due to the mixed bag of sources that make up other revenues and their potential for idiosyncratic behavior. Let’s take, for example, intergovernmental revenue. It declined quite a bit during the 2001 recession but almost not all during the 2008 recession. The explanation may be that intergovernmental revenues, unlike the tax revenues we have described above, are primarily dependent on the whims of state policy makers.

Local taxes are primarily dependent on economic activity (property transfers, retail sales, etc.). To simulate this, our model uses the declines from the recessions as the parameter for other revenues but makes the impact independent from what happens to taxes. For example, if the model simulates a “bad” recession that results in a sharp decline for taxes, we do not assume that necessarily means a sharp decline in other revenues.

Analyzing Revenue Volatility Risk
To analyze the risk that the City is subject to we used the information presented above to inform our Risk Model. In addition to this information, we also used the following information:
• We used data on how often recessions have occurred and how long those recessions have lasted from 1950 onwards to simulate the frequency and duration of future recessions. • We examined the timing of each revenue’s decline relative to the others. Meaning, not all revenues declined at the same time. For example, both property transfer tax and non-tax revenues appeared to decline well before most other revenues during both the recessions we examined. Thus, the Risk Model shows these two revenues decline immediately upon a recession while there is a one-year lag for all other revenues. • The model does not include any assumptions about what the City might do in response to a recession like cutting expenditures or adding new revenues. However, the model does not ignore these possibilities either. The user of the model has the option to define the City’s assumed response to recessions and see how that impacts the City’s financial position. This is discussed in more detail in Section 7 of this report.

Exhibit 4.2 below shows the cumulative probability curve for a sing le year loss, accounting for all the information described in this section. The blue line shows the losses if recession DOES occur, and it lasts the entire year. The red line shows the losses given the chance a recession does OR does not occur. This accounts for the fact that a recession could not occur at all or last less than the entire year. Note that although the lines in Exhibit 4.2 are limited to what could happen in a single year, our simulation also allows for the possibility that a recession could span multiple years. We will discuss the multi -year perspective on all the of the City’s risks that we analyzed in Section 7.

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In Exhibit 4.2, we can see the red line remains at zero about 70% of the time, which means that 70% of the time the City is simulated to not be in a period of revenue downturns. The blue line approaches zero as well because the very mildest of recessions could have negligible financial impact.

Both lines slope up and to the right, which means that as we move to the right the potenti al losses get higher, but we also get higher and higher confidence that the losses would be less than the indicated amount. We see that on an annual basis, losses around $4 million to $ 9 million might be considered a plausible, not just possible, risk. For example, on the red line, we can be 85% confident that losses will be less than $ 6.2 million in any given year, and 15% confident that losses will be more. We can be 90% confident that losses would be less than $9.2 million.

Both lines flatten out at the right end. This shows that extreme annual losses, over $20 million, are possible, but are also highly unlikely. This is because the corresponding values on the vertical axis are above 95%, which means we can be 95%, or more, confident that the losses duri ng a given year will be less than these extreme amounts.

Exhibit 4.2 – Cumulative Probability Chart for Annual Recession Losses (total, not per capita)

Confidence
that losses
will be the
indicated
amount or
less

Checkpoints
✓ Property tax is an important source of revenue for the City and is also very stable. ✓ Sales tax and property transfer taxes are importa nt revenue source s but are responsive to economic conditions.
✓ Historical data does not show much of a decline in business license taxes during past recessions, but there is reason to believe that the revenue could exhibit a larger decline in future recessions.

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These reasons include an anomalous event in 2008 that resulted in an increase in revenues and the fact that this revenue did decline markedly during the COVID downturn. ✓ There is also potential for instability in other City revenues, though these revenue s constitute a relatively small portion of total revenue, compared to those above. ✓ In a given year, there is about a 70% chance that there would be no impact at all from a recession.

There is a 90% chance that losses in a given year would be less than $10 million. ✓ The analysis presented in this section does not take account of any willingness on the part of the City to cut its budget in response to a recession. That is addressed in Section 7.

Pension Risk
Like many cities throughout the country, Berkeley has a substantial liability for employee pensions. This is potentially a risk for the general fund because if the pension plan investments consistently perform below expectations, then the City will need to make up the difference. This potential unplanned, unavoidable expenditure places additional pressure on the City finances.

The GFOA Risk Model examines the vulnerability of the City’s pension situation under different scenarios.

We worked with Foster and Foster to develop a range of different possible outcomes that are consistent with different long-term return assumptions from CalPERS. Of particular relevance to the questions being posed by th is report is the possibility of underperformance of CalPERS investments . Foster and Foster provided the range of possible outcomes, informed by assumptions from C alPERS about the expected range of possible performance of its investment strategies.14 We then correlated these ranges with the GFOA recession model, so that, generally, in scenarios reflecting poor economic performance, generally, there would be poor CalPERS performance as well.

The model does not assume that any and all underperformance by the pension will translate directly into an impact on the reserve. There are several filters pension costs must pass before impacting reserves in the risk model.

First, CalPERS itself takes steps to shield participating local governments from the effects of year-to-year changes in investment performance. The scope of our contract did not accommodate duplicating CalPERS’ pension cost smoothing algorithms, but we did develop a model that balances out under-performing years with over -performing years such that the C ity would see greater additional burden when under - performing years outweigh the over performing years across all ten years of the simulation.

Second, the City has proven willing to accommodate pension cost increases in its budget. Hence, the model includes a user-defined variable for how much pension costs would need to increase before the City becomes unwilling to absorb the full cost in its budget. We assume the City is willing to absorb up to a 15% annual increase in pensions, based on past experiences of the City. You can think of this variable as the amount the City would find a way to accommodate in its normal budget planning for pensions.

14 To be more precise, the range took the form of a distribution with a median value and favorable and unfavorable results distributed around the median.

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Third, the City has a pension trust fund. The model includes the pension trust fund as an alternative to reserves for covering excess pension costs that the budget cannot absorb. In essence, the simulation splits any excess pension costs evenly between the reserves and the pension trust. The model also accounts for interest earned on the pension trust balance.

With these assumptions applied the model shows:
• There is about a 50% chance that the general fund reserve and pension trust fund, together, will need to absorb, at most, an additional $10 million in costs over a ten-year period. • About a 75% chance that the general fund reserve and pension trust fund, together, will need to absorb, at most, an additional $15 million in costs over a ten-year period. • About a 90% chance that the general fund reserve and pension trust fund, together, will need to absorb, at most, an additional $19 million in costs over a ten-year period.

To see just the burden on the reserve, simply divide the dollars in the points above in half.

Checkpoints
✓ Pensions are an important risk for the City not only because of the size of the liability but because poor performance of the pension investment will likely be correlated with poor performance of the City’s revenues. That means the general fund reserves will be under pressure from both revenue losses and pension losses at the same time, if the economy performs poorly. ✓ There is about a 25% chance that the general fund reserve will need to absorb $7.5 million or more over a ten -year period due to pension under -performance and a 10% chance of need to absorb more than $9.5 million.

Section 5 - Extreme Events
Although Berkeley can receive
reimbursement from insurance and public
agencies for natural disasters and some
human-caused extreme events , having
adequate reserves in place is important to
respond to extreme events quickly and
decisively. For example, FEMA
reimbursement will not cover all the costs the
City incurs, and it could take months, if not
years, to receive reimbursement. Wildfires,
earthquakes, and tsunamis are the leading
potential catastrophic natural disaster risks
the City faces. In discussions with City staff,
these disasters represent the greatest risk of
catastrophic loss and will be the focus of this
section of the analysis. Other exposures
included in the Risk Model and discussed in
FEMA, CalOES, and Reserves
The U.S. Federal Emergency Management Agency
(FEMA) reimburses local governments for monies spent
in response to a federally-declared disaster. FEMA
reimbursement is only partial (typically 75 percent) and is often not immediate. Therefore, local governments
must have the financial capacity to respond quickly and decisively, independent of FEMA assistance . In
California, CalOES (California Office of Emergency
Services) provides additional assistance to supplement
FEMA. Our simulati on includes FEMA and CalOES
assistance but also simulates the time lag to get the
assistance. Note when we refer to “FEMA assistance”
we are also referring to CalOES since our model treats
assistance from both agencies in essentially the same
way.

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this section are high winds, severe storms and landslides. This section will also discuss the provisions made in the model for other risks, not named above.

The following sub-sections will explore the potential economic and budgetary implications that these hazards have for the Berkely community and City government. These sections will explain any notable features of the data sets we used and discuss the range of potential damage the City could experience, as suggested by the data we gathered.

A. Wildfires
According to the First Street Foundation,15 “there are 15,085 properties in Berkeley that have some risk of being affected by wildfire over the next 30 years. This represents 57% of all properties in Berkeley. ” Exhibit 5.A.1 shows a wildfire risk map from First Street. That said, we should also note that the overall risk to Berkeley is considered “moderate” by FirstStreet, which is the second lowest risk level on their scale (the scale can be seen in the bottom right corner of Exhibit 5.A.1).

Exhibit 5.A.1 – Wildfire Risk in Berkeley (according to the First Street Foundation)

Though the First Street data does help illuminate the potential for wildfires in the City of Berkeley, it does not address consequences of nearby fires, like smoke heavy enough severely impede daily life in Berkeley.

Therefore, we should recognize that the total risk to Berkeley from fires is more than might be implied in the map above. However, for the purposes of this analysis we are focused on the more narrowly defined risk of losses to the City government due to unplanned, unavoidable expenditures from a large fire.

To analyze wildfire risk, we divided the risk into two parts.

First are very large wildfires – including those large enough to be historically unprecedented in the region.

We obtained simulated fires from a company called Pyrologix, w hich specializes in simulating fires.

Pyrologix’s customers include the US Forest Service. Pyrologix’s data set focused only on very large fires and showed which geographic areas of the City burned.

15 The mission of First Street Foundation is to make climate risk accessible, easy to understand and actionable for individuals, governments, and industry.

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Second are wildfires that are less intense, which we will call “medium” fires – even though the fires simulated here are still often large enough to be eligible for FEMA assistance. These medium fires are simulated to occur 4 times more frequently than the large fires. For medium fires, we used historical data from across California to see how often wildfires directly impact urbanized areas to the point where city governments incur material costs, and we used those historical costs to simulate the impact on Berkeley.

We simulated both kinds of fires and then comb ined the results into a single model. The result was the cumulative probability chart shown in Exhibit 5.A.2.

We can see that, like Exhibit 5.B.1, there is a small chance of any losses at all – the red line is equal to zero up until about the 60% mark, which means that 6 out of 10 times when we look at a ten-year period the losses will be zero. The line also goes vertical (up) very sharply after it diverges from the zero axis . This means that most wildfires the City might experience are simulated to not cause a drastic amount of losses.

This would be consistent with the actual experiences of cities at “moderate” wildfire risk in our FEMA database (where “moderate” is as defined by FirstStreet). The line does extend out quite some distance to the right, which represents the fact that there is a very small chance of some very large losses over a ten-year period. The long-tail is the result of the very larger wildfire simulation we discussed earlier.

Note that the losses shown in Exhibit 5. A.2 do not reflect re imbursement from FEMA to the City government. The impact FEMA reimbursement and other mitigating factors will be included in Section 7 of this report, “Putting it All Together”.

Exhibit 5.A.2 – Cumulative Probability Chart of Losses to the City Government from Wildfires Over a Ten-Year Period (millions of dollars)
Chance Losses
will be Equal to
or Less Than
Dollar Amount
on Horizontal
Axis

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Our data does not factor in the impact of climate change, so the 10 -year losses may be understated. 16 However, there are other assumptions in our model that cause the model to simulate greater losses. This might offset the absence of a climate change assumption. These assumptions are:
• The model does not assume that a fire in one year reduces the chance of a fire in t he next year.

In reality, if a fire occurs it often burns the fuel that could otherwise feed a fire in the future. In our model, the chance of a fire in a given year is not reduced if a fire had occurred the prior year.

Put another way, the chance of fire is the same every year. • When gathering losses from other cities to use as analogues from Berkely we looked across the entire state of California for cities that are roughly comparable size to Berkeley. 17 Perhaps unsurprisingly, only a handful of cities tha t have actually experienced material losses from a fire are at “moderate” risk (by the FirstStreet s cale). Most are at “major” risk or worse. A lso, the average per capita losses experienced by the “major” risk cities was materially higher than those experienced by the “moderate” risk cities. Nevertheless, we included most of the “major” risk cities as analogues for Berkeley when simulating potential damages.18 This means our model may be biased towards overstating the damage from a fire.

1. T
Checkpoints
✓ According to the First Street Foundation’s analysis, Berkeley’s risk from wildfire is “moderate”. ✓ We used data from the fire simulation firm Pyrologix to simulate very large wildfires. ✓ We used historical data from FEMA to help simulate more moderate wildfires , coupled with information from First Street on relative risk of cities in California. This helped us pick analogues for Berkeley.
✓ The results show that over a ten-year period there is about a 6 in 10 chance that damage from wildfire is zero.
✓ There is a chance of larger damage over a ten-year period. For example, there is a 1 in 10 chance damages could exceed $350,000 . There is small chance of extreme multi -million-dollar losses (about 1 in 50 chance).

B. Tsunamis
Berkeley is at some risk from Tsunamis. The worst tsunami that researchers have mostly contemplated is the 1-in-900-year tsunami. This represents a tsunami so large that we would expect to see one that large only once in 900 years. Exhibit 5.B.1 shows a map of the area of the City we could expect to be impacted by such a tsunami. A tsunami of this size is expected to impact about 1,400 residents, a daytime population of 6,800, and 448 buildings . The damage of less intensive tsunamis is substantially less. A tsunami of

16 Wildfire is, perhaps, the most difficult type of natural catastrophe to model because there is a smaller base of experience to draw upon, compared to more well-studied risks like hurricanes, and because the physics of wildfires are more complicated, compared risks like flooding. Though many r esearchers are working on improving wildfire models, we could not obtain data that included climate change effects. 17 Our research has shown that very small cities tend to have higher per capita losses from fires, so we don’t use small cities as analogues for cities that are not small. 18 We dropped cities much larger than Berkeley and outliers that experienced extreme damages far beyond anything experienced by the moderate risk cities in the data set.

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sufficient intensity to occur on ly once every 475 years is only estimated to impact 125 residents, 1,100 daytime population, and 14 businesses.

Exhibit 5.B.1 – Area Impacted by a 1-in-900 Year Tsunami

Unfortunately, researchers have not produced nearly as much information on projected economic losses from a tsunami as has been produced for other types of disasters. To arrive at an estimate, we used a joint report from the United States Geological Survey and California Geological Survey that modeled a large, plausible tsunami.19 We will refer to this as the “SAFR report” (Science Application for Risk Reduction report). The tsunami contemplated by the SAFR report appears to be the rough equivalent of the 475- year tsunami described above.20 The SAFR report does not estimate losses for Berkeley but does for all Alameda County: $184 million. We derived a share of this for Berkeley by looking at Berkeley’s share of the Alameda coastline, which equates to about 7% or about $13 million. Our estimate of 7% is somewhat conservative (overestimates Berkeley’s share) because we excluded a portion of the coast that the SAFR report appears to project will not be significantly impacted by a tsunami and because we used straight

19 The main report is: “ The SAFRR (Science Application fo r Risk Reduction) Tsunami Scenario ”, Stephanie Ross and Lucile Jones, Editors . The specific sub -report we used was: “ The SAFRR Tsunami Scenario —Physical Damage in California” By Keith Porter, William Byers, David Dykstra, Amy Lim, Patrick Lynett, Jamie Rat liff, Charles Scawthorn, Anne Wein, and Rick Wilson Open-File Report 2013–1170–E California Geological Survey Special Report 229 U.S. Department of the Interior, U.S. Geological Survey 20 The report does not give a recurrence interval for the tsunami the re port describes , but it does give wave amplitudes which we compared to projected wave amplitudes for different tsunami scenarios in Berkeley. The 475- year scenario appears to be the closest match.

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line estimates,21 which discounts inlets, coves, islands, etc. We then were able to scale the estimated damages from a 475-year tsunami ($13 million in economic losses to the community) to tsunamis of other recurrence intervals but using estimates of the number of people impacted by different sizes of tsunamis in Berkely.22
The next step is to estimate the potential loss to the City government. Again, because there is not much research available on the projected financial impacts of tsunamis, we had to make some assumptions. We started with the estimate of total economic losses, as per above. We then examined data we had available for earthquakes and wildfires and found damages to public entities (e.g., local governments) typically range between 11% and 32% of the economic losses. 23 This resulted in the cumulative probability chart shown in Exhibit 5.B.1.

We can see that, like in Exhibit 5.B.1, there is a relatively small chance of any losses at all – the red line is equal to zero up until about the 90% mark, which means that 9 out of 10 times when we look at a ten - year period the los ses will be zero. The line does extend out quite some distance to the right, which represents the fact that there is a very small chance of some very large losses over a ten-year period. It should also be noted that estimates from the tsunami unit of the California Geological Survey show that a very small number of people (less than 25) and households (less than 10) would be impacted by a 200- year tsunami. This means that many of the tsunamis that the risk model simulates will have very little financial impact.

Note that the losses shown in Exhibit 5.B. 1 do not reflect reimbursement from FEMA to the City government. The impact FEMA reimbursement and other mitigating factors will be included in Section 7 of this report, “Putting it All Together”.

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21 By this, we mean we drew straight lines on a map of the county coast and measured the distances of those lines. 22 Estimates produced using ESRI software, by the tsunami unit of the California Geological Survey. 23 Based on estimates from Aon . Aon’s data shows projected public assistance provided by FEMA. Knowing that FEMA reimburses 75% of local cost allowed us to simulate total costs to city government.

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Exhibit 5.B.1 – Cumulative Probability Chart of Losses to the City Government from Tsunamis Over a Ten-Year Period (million of dollars)
Chance Losses
will be Equal to
or Less Than
Dollar Amount
on Horizontal
Axis

Checkpoints
✓ Tsunami experts believe that a tsunami large enough to do a great deal of damage to Berkeley is a very rare event – we might expect such a tsunami once every 900 years. ✓ Though less severe tsunamis are quite possible, the damage a less severe tsunami would do is estimated to be far less though certainly not inconsequential.

✓ The simulation shows that over a ten -year period there is a 90% chance the City of Berkely would have zero financial losses from tsunamis. There is a very small chance, though, of experiencing very large losses.

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C. Earthquakes
Berkeley is susceptible to earthquake risk. Exhibit 5.C.1 provides a map of major fault lines in the region.

Exhibit 5.C.1 – Map of Known Active Geologic Faults24

To address earthquakes, we obtained a data set of simulated earthquakes from Aon for the Contra Costa and Alameda County area.25 The simulation includes projected economic losses for earthquakes. We then scaled these losses to Berkeley by comparing Berkeley’s share of total property value to the r est of the two-county area. Berkeley comprises about 4% of the total property value, so we assumed Berkeley would experience about 4% of the economic losses from a given quake. We also set a limit in our model to only address quakes above 6.0 in magnitude. In the USGS report that Exhibit 5.C.1 came from describ es the potential damage of a 6.0 quake as “light” so earthquakes below the limit might not cause a material amount of economic loss. That said, our model does provide the ability to manually adjust the threshold downward to include other quakes.

24 From: “The HayWired Earthquake Scenario—Earthquake Hazards” published by the US Geological Survey. 25 Aon is global insurance and data analytics firm.

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5.C.2 provides a loss exceedance curve for ten years and 1 year, showing total economic losses Berkeley.

Exhibit 5.C.2 – Loss Exceedance Curve for Economic Losses from Earthquakes, Over 10 Years and 1 Year
Chance
Losses
will
Exceed
Dollar
Amount
on
Horizontal
Axis

We next converted the earthquake simulation into losses for the City of Berkeley general fund. First, we converted economic losses to total public assistance provided by FEMA to governmental agencies in the two-county area. Next, we estimated the share of losses to the governments that serve Berkely (city, county, school, etc) , using measure s of the total capital assets owned by each government .26 We then identified the City of Berkeley’s general fu nd share by looking at the percent of Berkeley’s capital assets attributable to governmental funds versus those not owned by governmental funds. Finally, we compared the results of the simulation to actual losses of California municipal governments from three historical earthquakes. The results of the simulation were consistent with these historical experiences. The results are shown in Exhibit 5.C.3.

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26 This inc ludes adjusting for the community of Berkeley’s “share” of each government’s assets. For example, community’s share of the school district’s assets is 100%, but the share of the transit district ’s assets is much less.

We also included an allocation for state government and quasi-governmental agencies, based on these entities share of earthquake losses in historical quakes.
0%
10%
20%
30%
40%
50%
60%
$0 $4,000 $8,000
Millions
10 year

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Exhibit 5.C.3 - Cumulative Probability Chart of Losses to the Cit y Government General Fund from Earthquakes Over a Ten-Year Period (millions of dollars) Chance Losses
will be Equal to
or Less Than
Dollar Amount
on Horizontal
Axis

Exhibit 5.C.2 shows that there is about 50% chance of no losses at all. But there is also a chance of large losses. There is an 80% chance that losses are less than $13 million over a 10-year period, which means there is 20% chance losses could be more. Note that Exhibit 5.C.2 does not include the FEMA assistance that the City would receive. This chart also does not address the possibility that a very severe quake could impair the City’s tax base. Both of these issues will be addressed in Section 7.

Finally, we should address the fact that a powerful earthquake (e.g., 7.0 or greater) could impair the City’s taxbase. Uninhabitable retail buildings could not make sales. Uninhabitable residential buildings would not make purchases. Both would result in lower sales taxes, for example. An impaired tax base would result in lower revenues for the C ity over a multi -year period, which would not be recoverable through FEMA or by property insurance.

The risk model accounted for tax base impairment. If the model simulates a 7.0 or greater magnitude quake, then a tax base impairment simulation is activat ed. The assumptions for this simulation were largely taken from a body of work by the United States Geological Survey called the “HayWired Earthquake Scenario” which investigates the potential societal impacts of a 7.0 earthquake in the region. 27 The information in the report was supplemented with estimates from relevant subject matter experts, such as City staff . We also used estimate s for earthquake recovery timelines developed as part of another project with Salt Lake City, Utah . Examples of variables tha t the tax base impairment model addresses include:

27 Within this body of work, we relied on the report: “The HayWired Earthquake Scenario—Engineering Implications” Scientific Investigations Report 2017 -5013-I-Q, Version 1.1, April 2022. Edited by Shane T. Detweiler and Anne M.

Wein, U.S. Department of the Interior, U.S. Geological Survey

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• Berkeley’s share of buildings stock within Alameda County. The HayWired scenario only provides county-level estimates.
• The degree of damage to buildings that might be expected from a 7.0 quake. • The range of economic losses that could be expected to buildings that are damaged to one degree or another.
• The estimated time to rebuild damaged buildings.
• Short and long-term impacts of tax base impairment and the fact that lost tax revenue is not covered by FEMA assistance. Later in this report (Section 7) we discuss parametric insurance as one way to provide coverage for lost tax revenues, in addition to reserves. • Offsetting increases in sales tax revenue from construction activity to rebuild, including cost of buildings that are materials, percent of materials that are purchased inside Berkeley, and the additional cost necessary to rebuild a home vs building new.

The analysis shows the losses to the general fund could be material, approaching 5% of general fund revenues in the first year, before much rebuilding has taken place. The model assumes it would take around 8 years to completely replace all the lost buildings.28

Checkpoints
✓ Earthquakes are an important risk for the City of Berkeley . There are multiple active fault lines in the region.
✓ There is about a 50% chance of no losses at all over a ten-year period. ✓ Earthquakes can produce substantial losses. For example, there is a 20% chance that losses to the City government could be more than $13 million.

✓ A large earthquake (e.g., magnitude 7.0) could impair the City’s tax base by a material amount – approaching 5% of general fund revenue in the first year.

D. Rainfall Triggered Major Landslides
Heavy rainfalls can trigger landslides in Berkeley. A search of historical records indicates that there have been 3 major, damaging landslides,29 triggered by rain, in Berkeley since 1982. We used this as the basis for the potential frequency of landslides in the future: 3 landslides in 41 years implies a 7% annual chance of a landslide.

For potential damages landslides might cause we looked at two sources:

28 This is based on discussions with building officials in Salt Lake City. We worked with Salt Lake Cit y to build this model and then transferred it to Berkeley. We changed all the assumptions that were specific to Salt Lake City. The time required to rebuild buildings is the only variable that wasn’t changed, however, it can be changed quite easily, if needed.
29 By “ major and damaging” we simply mean that the damage was large enough to require intervention by City government and cause City government a significant cost.

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• FEMA estimates of total exposure to landslides in each census tract in Berkeley and estimated loss ratios. This provided a starting point for what losses might be from a landslide. • Historical records of losses from landslides in the region. This provided a sense of the variation that can take place.

We put all these pieces of data together to develop a range of possible landslide outcomes. This resulted in the potential community economic losses shown in Exhibit 5.D.1.

Exhibit 5.D.1 – Loss Exceedance Curve for Landslides, 10 Year and 1 Year Risks (millions of dollars) Chance Losses
will Exceed
Dollar Amount
on Horizontal
Axis

The next step is to estimate the potential loss to the City government. There is not much research available on the projected financial impacts of landslides or much historical data to draw upon, so we had to make some assumptions. We started with the estimate of total economic losses, as per above. We then examined data we had available for earthquakes and wildfires and found damages to public entities (e.g., local governments) typically range between 11% and 32% of the economic losses. 30 This resulted in the cumulative probability chart shown in Exhibit 5.D.2.

We can see that there is about a 50% chance of no losses at all – the red line is equal to zero up until about the 50% mark, which means that 5 out of 10 times when we look at a ten -year period the losses will be zero. The line does extend out to about $500 thousand, which represents the high-end of losses produced by the simulation.

We should note that there is no instance, in the FEMA records we had access to, of FEMA reimbursing a California municipality for landslides . Therefore, now here in our model do we assume FEMA reimbursement for landslides costs. Also, the simulation resulted in many landslides of marginal cost to

30 Based on estimates from Aon. Aon’s data shows projected public assistance provided by FEMA. Knowing that FEMA reimburses 75% of local cost allowed us to simulate total costs to city government.

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City government. We might reasonably assume that these minor landslides will be absorbed by the regular City budget, rather than the general fund reserve. This will be reflected in Section 7 of this report, “Putting it All Together”.

Exhibit 5.D.2 – Cumulative Probability Chart of Losses to the City Government from Landslides Over a Ten-Year Period (thousands of dollars)
Chance Losses
will be Equal to
or Less Than
Dollar Amount
on Horizontal
Axis

Checkpoints
✓ Berkeley has experienced three damaging landslides since 1982. ✓ We used FEMA data on potential losses from landslides plus historical data from other landslides in the region to simulate potential costs to the City government.

✓ The simulation shows that over a ten -year period there is a 50% chance the City of Berkely would have zero financial losses from landslides. The simulation showed that losses could reach about $500 thousand, if the City is unlucky.

E. High Winds
High winds can cause damage in the community and occur relatively frequently. For example, data from the National Weather Service indicates that there have been 118 wind events in the entire San Francisco Bay Shoreline zone since 2011, with an average speed of 43 miles per hour. Of course, not every wind event in this zone will impact Berkeley. An examination of wind data from a local weather station for the last 24 months showed that the average windspeed of the 10 sustained wind events was about 30 mph.

For comparison, FEMA regards 67 mph as a very strong wind event that would be likely to cause significant damage. During the same 24 -month period, the San Francisco Bay Shoreline Zone experienc ed three

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events over 40 mph. The biggest was on April 11, 2002. On that day in Berkeley, the maximum sustained wind period was around 40 mph. It should be noted that sustained winds (customarily measured over ten minutes31) are not as strong as unsustained wind gusts that can happen during the same wind event. For example, during a recent two -year period 32 the top speed of a wind gust was an average of 4.7 mph greater than the speed measured for the associated sustained wind event.

If we compare the 24 months of local weather station data to the same period from the National Weather Service data, we find that the wind events for the San Fransico Bay Shoreline zone were fully felt in Berkeley in four out of eleven cases (36%). Hence, we applied that some portion to entire 12-year period of history to arrive at an assumption that there will be an average of 3.5 wind events per year, on average.

We assumed that there was a 3% chance of a wind event with sustained winds of 67 mph or greater, which is equivalent t o assumptions from FEMA’s estimates of losses for Berkeley. 50% of wind events were assumed to be 45 mph or less, which is consistent with historical data. To estimate damage, we started with estimates from FEMA for damages from a very strong wind event (6 7 mph), based on total exposed value and expected rates of loss, which was $43,200 per event. We then scaled that loss down to expected damage from a 45-mph event. According to the Beaufort Wind Scale33 winds at 45 mph result in damages such as twigs and sm all branches broken from trees. Hence, we assumed that damage was minimal at winds of this speed. This resulted in the loss exceedance curve shown in Exhibit 5.F.1.

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31 https://www.rmets.org/metmatters/beaufort-wind-scale 32 September 2023 to September 2021
33 You can see the full scale at: https://www.weather.gov/mfl/beaufort. The scale is typically used to measure mean speeds, usually averaged over 10 minutes by convention, and do not capture the speed of wind gusts.

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Exhibit 5.F.1 – Loss Exceedance Curve for Strong Winds, 10 Year and 1 Year Risks (Millions of Dollars)

The next step is to estimate the potential loss to the City government. There is not much research available on the projected financial impacts of high winds or much historical data to draw upon, so we had to make some assumptions. We started with the estimate of total economic losses, as per above. We then examined data we had available for earthquakes and wildfires and found damages to public entities (e.g., local governments) typically range bet ween 11% and 32% of the economic losses. 34 This resulted in the cumulative probability chart shown in Exhibit 5.F.2.

We can see that there is about a n 85% chance of total losses over 10 years less than $500,000 – the red line is equal to $500,000 up until about the 85% mark. The line does extend out to about $3.3 million which means our simulation did show that large costs are possible, even if the chances a very remote. For example, there is only a 3% chance that total losses over ten years would be more than $1 million.

Note that we are considering this risk to be different from a severe storm, which might include lightning and heavy rain. The high winds risk only relates to winds that may or not be accompanied by storm conditions. Because this risk is limited to more “routine” winds, which fall short of a “natural catastrophe”, we do not assume FEMA would get involved. However, we also assume that many wind events will only result in marginal damage, which could be absorbed in the City budget, rather than the general fund

34 Based on estimates from Aon. Aon’s data show s projected public assistance provided by FEMA. Knowing that FEMA reimburses 75% of local cost allowed us to simulate total costs to city government.

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reserve. This will be reflected in Section 7 of this report, “Putting it All Together”. We also have another section of this report on severe storms.

Exhibit 5.F.2 – Cumulative Probability Chart of Losses to the City Government from High Winds Over a Ten-Year Period (thousands of dollars)
Chance Losses
will be Equal to
or Less Than
Dollar Amount
on Horizontal
Axis

Checkpoints
✓ High winds occur regularly in the bay areas and sometimes reach high enough speed that they could cause a material amount of damage to the community.
✓ There could also be costs to the City government. Most of these costs could probably be absorbed by the City budget, but it is possible that extraordinary costs would require the use of the reserve. ✓ Our simulation shows that there is about an 85% chance of total losses over 10 years less than $500,000. There is only a 3% chance that total losses over ten years would be more than $1 million.

F. Severe Storms
A prior section of this report addressed high winds, which focused on winds in the range of around 35 to 67 mph, where many simulated wind events cause marginal or no damage. That section did not address severe storms which could include not only high winds, but also violent precipitation. In 2006, Berkeley, along with 16 other cities in Alameda and Contra Costa counties experienced a storm that was severe enough to receive assistance from FEMA. We used this storm as a starting point to simulate future storms.

There was also a severe storm in 2023, but not enough data from that storm is available to be able to fully include in the risk model (but it still partially informs the model).

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Let’s start simulating the frequency of storms. There have been three severe storms in Alameda and Contra Costa counties that were bad enough to receive FEMA support since 1998. [3] Berkeley was only impacted by two of the storms. Hence, we simulated an 12% annual chance of storms,[4] with a 66% chance that Berkeley would be impacted by any given storm.[5]
To simulate damages, we looke d a per capita damage from each of the cities impacted by the 2006 storms.35 That provided a range of potential losses. We used this range to simulate Berkeley’s potential losses from future storms: both economic losses to the community at large and financial losses to the City government.

Exhibit 5.G.1 shows the loss exceedance curve for the economic losses to the entire community from severe storms. We see that some very large losses seem possible, even if highly unlikely.

Exhibit 5.G.1 - Loss Exceedance Curve for Tsunamis for Berkeley Community, 10 Year Risk (millions of dollars)

Chance Losses
will Exceed
Dollar Amount
on Horizontal
Axis

Section 6 -
Chance that Economic Losses Will Exceed Dollar Amounts (Millions) Indicated Below
Time Horizon 5% 10% 50% 90%
1-Year $1.1M $0 $0 $0
10-Year $10.5M $8M $0.4M $0

Exhibit 5.G.2 shows the cumulative probability chart for direct losses to the City government from severe storms. Similar to 5.G.1, we see that very large losses are possible, though highly unlikely. The cumulative

[3] This is as far back as we can obtain records from FEMA [4] 3 storms in 25 years is 3/25 or 0.12
[5] Berkeley was impacted by 2 of 3 storms, or .66.
35 2023 data is not available as of this writing

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probability chart does not include FEMA reimbursement. That will be addressed in Section 7 of this report, “Putting it All Together”.

Exhibit 5.G.2 – Cumulative Probability Chart of Losses to the City Government from Severe Storms Over a Ten-Year Period (millions of dollars)
Chance Losses
will be Equal to
or Less Than
Dollar Amount
on Horizontal
Axis

Checkpoints
✓ Severe storms present a greater amount of possible damage than just high winds. ✓ Severe storms powerful enough to cause material amounts of damage are rare, but the amount of potential damage could be quite large.
✓ That said the chance of very large damage is remote. There is a 7-in-10 chance of zero losses to City government over 10 years and a 9-in-10 ten chance of losses less than $1 million.

H. Pandemics / Infectious Disease and Other Risks
COVID-19 has made people more aware of the risks posed by pandemics. We included pandemics in the Risk Model by developing a “miscellaneous risks” simulation to account for pandemics as well as other unusual events that don’t fit into the categories above, but that have the potential to require the City to use reserves. Another example of such an event occurred in 2013. A wildfire in the Tahoe region caused extensive damage to propert y owned by the City of Berkeley, requiring a large outlay from the general fund (on top of reimbursements from insurance) to mediate. Other events might not cause much damage.

For example, civil unrest in 2019 created overtime costs for public safety personnel, but the total cost was relatively modest. Note that by limiting the scope of this simulation to events that might impact reserves we are excluding insurable losses.

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The simulation provides for a small annual chance that an unusual event might occur. The annual chance is aligned with how frequently such events have happened to Berkeley in the past. If an event is simulated to occur, the potential damages are also aligned with the damages for events Berkeley has experienced in the past. Something on th e scale of the damage from COVID would be very rare. Finally, the model simulates reimbursement by outside entities. The chances of reimbursement are also aligned with Berkeley’s experience. Also, GFOA’s experience with building similar models for other local governments allowed us to draw on the experience of other local governments to provide more data points to base the model on.

Exhibit 5.H.1 shows a cumulative probability chart of simulated losses over a ten -year period. Because reimbursements were customized for the miscellaneous simulation, we included lines for gross losses and losses net of reimbursement.

Exhibit 5.H.1 – Cumulative Probability Chart of Losses to the City Government from Miscellaneous Risks Over a Ten-Year Period (millions of dollars)
Chance Losses
will be Equal to
or Less Than
Dollar Amount
on Horizontal
Axis

We see Berkeley has a 33% chance of zero losses. Even if losses do occur, they are relatively mild most of the time (compared to some other hazards we have discussed in th is report). For example, there is 70% chance net losses will be less than $1 million in a ten-year period. Nevertheless, larger losses are possible.

There is a 5% chance net losses could exceed $5 million in a ten-year period.

Section 7 of this report show s how miscellaneous risks impact the City’s reserves, along with the other risks we analyzed.

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Checkpoints
✓ The City could be impacted by other, unexpected hazards; besides those we’ve described in other sections of this report. Pandemics are the most re cent example of a hazard that was not top of mind for many local governments until recently.
✓ We used the experience with COVID-19 as well as other unusual events the City has experienced to simulate the exposure of the City’s reserve to other hazards. We also drew upon GFOA’s experience building similar models for other cities to broaden the data available.

✓ The simulation suggests that very large losses, net of reimbursement from other entities, from miscellaneous risks is unlikely. There is a 70% chance net losses will be less than $1 million in a ten- year period. Larger losses are possible. There is a 5% chance net losses could exceed $5 million in a ten-year period.

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Section 6 - Secondary Risks and Comparable Analysis
Prior sections of this report reviewed the risks of the greatest financial consequence to Berkeley. In this section we briefly review other risks that we considered, but that did not appear to be as important to Berkeley’s general fund reserve as the other risks we examined. This is not to say that Berkeley should not prepare for these risks or that they are not important. It is only to say that these events were not included in the scope of our analysis because of the low potential impact on the general fund reserve. Finally, we should note that the primary risk section of this report includes an “other hazards” model which is intended to capture the possibility of losses from unexpected sources. For example, we will see later in this section although the City has solid cyber insurance, like every other city, there are exceptions in the policy for acts of war. One could imagine a scenario in which a cyber-attack by state-sponsored actors is not covered by the policy, requiring the city self -fund the recovery. These kinds of “unconventio nal” scenario are the purpose of the “other hazards” model.

Also, in this section we examine how Berkely compares to other cities in terms of indebtedness and the amount of fund balance maintained.

A. High Heat
According to the First Street Foundation’s Risk Factor tool, Berkeley has a “moderate” risk for heat. This is, first, because “feels like” temperatures have been rising. Exhibit 5.G.1 shows First Street’s rising expectations for heat waves in the future. We see that it is going up, where a hot day is defined as temperatures above 83 degrees Fahrenheit.

Exhibit 6.A.1 – First Street’s Estimation of the Chance of a 3+ Day Heat Wave

First Street also posits that homes in Berkley have moderate vulnerabilities to heat based on factors like shade and proximity to bodies of water.

We used data from First Street to simulate the number of heat days along the following thresholds, where the indicated temperature is the “feels like” temperature, so includes humidity (which increases the

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perceived temperature).36 First Street provided an estimate of the average number of days between 80 and 90 degrees and above 90 degrees for the next 30 years. We focused on the next ten years. Historically, we looked at the difference between what First Street’s algorithm w ould have predicted for past years and compared it to what actually happened to estimate the potential variation between what First Street’s algorithm predicts for the future and what actually happens.

Unfortunately, not much useful research exists on eco nomic impacts of high heat at the local level – research seems to focus on aggregated losses at the national or international level. Further, by speaking with a CFO of a large city in the Phoenix area (which has a much larger risk of high heat days than Berkeley) we learned that high heat days don’t seem to have much potential impact on general fund reserves.

Therefore, we did not quantify this risk. Instead, Exhibit 5.G.2 provides summaries of the simulation results for 10 years in the future.

Exhibit 6.A.2 – Summary of Simulation Results for Number of High Heat Days “Feel Like”
Temperature
Annual
Average
Now
Annual
Average in 10
Years
Annual 90th
Percentile
Now
Annual 90th
Percentile in
10 Years
80-85 Degree Days 17 18 25 26
85-90 Degree Days 8 10 13 16
90-100 Degree Days 6 7 11 12
100+ Degree Days 0 1 2 2

B. Cyber Risk
Local governments are at high risk for cyberattack, particularly ransomware attacks. In fact, studies have shown that local governments are one of the most popular ransomware targets for cybercriminals.37 The City currently has coverage under “Alliant Insurance Services, Inc. Alliant Property Insurance Program (APIP) Cyber Insurance Evidence Attachment.” GFOA is not an insurance analyst, and a comprehensive review of all policy detail s was outside the scope of our project, but we can offer the following observations from our review of the policy as it relates to the City’s reserve strategy.

The insurance has a $2 million limit aggregate limit of liability. There are also several sublimits for different kinds of coverages. For example, there is a $500,000 limit for “Breach Response Costs”. It is conceivable that a particularly bad attack could exceed one or more of these sublimits. Research suggests that the potential damages from and at tack and size of the government are only weakly correlated. This means that even small governments can be on the receiving end of large attacks – and Berkeley is not a small government. Losses over these sublimits might be covered using the City’s reserves. It is also worth noting that there is a $40 million aggregate limit for all members of the policy. Presumably, this refers to the governments that participate in the Bay Cities Joint Powers Insurance Authority. In most cases, this joint

36 The “Feels Like” temperature relies on environmental data including the ambient air temperature, relative humidity, and wind speed to determine how weather conditions feel to bare skin. 37 The GFOA report “Cyber Risk Savvy” describes multiple such sources. It is available at gfoa.org.

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limit would not be much of a concern but could be an issue in the case of widespread attack that impacts many jurisdictions at the same time.

There is also a retention (deductible). 38 The policy describes a sliding scale of retentions, depending on the insured’s size. The scale ranges from $50,000 to $250,000. Presumably, the City would be on the upper half of this scale, however it is also very important to understand how retentions work in cyber policies.

There are two basic approaches single retention and multiple retenti on. A cyber -attack could trigger multiple types of coverage within the policy. The City’s policy has around twenty different types of coverage. An important question is: if a claim occurs would the City pay a separate retention for each type of coverage that is triggered (“multiple retention”) or one retention amount for the entire cyber -attack event (“single retention”)? This is not a trivial issue because the deductible amount the City would face could be multiple times larger under a multiple retention p olicy compared to a single retention policy.

GFOA could not discern whether the policy is single or multiple retention from the documents provided.

The City may wish to inquire with its insurance provider on this point.

The policy provides coverage on a “claims made and reported basis.” According to the International Risk Management Institute (IRMI), a claims-made and reported policy is a type of policy in which a claim must be both made against the insured and reported to the insurer during the policy per iod for coverage to apply. Further, IRMI states: claims-made and reported policies are unfavorable from the insured's standpoint because it is sometimes difficult to report a claim to an insurer during a policy period if the claim is made late in that poli cy period. This is particularly important when it comes to cyber risk. For example, imagine malicious software infiltrated the City’s network months ago but the City finds out about it after the policy period is over. How would the policy cover that situation? Cyberattacks can cause many types of losses. As mentioned above, the City’s policy includes several coverages to address different losses. Nevertheless, cyber policies are rarely, if ever, comprehensive of every cost that could arise from every cyberattack scenario. Here are examples of uncovered losses from the City’s policy:
• The policy excludes acts -of-war, but this is a common exclusion in insurance policies. Many ransomware attacks are thought to be perpetrated by state or quasi-state actors. If interpreted as an “act of war” the City may not have coverage. The policy goes even further by excluding “Governmental Actions,” which may be intended to exclude the actions of state-sponsored cybercriminal when those actions do not rise to the level of “an act of war.”
• The policy excludes property damage. For example, if a computer virus sabotages physical equipment besides computer hardware, the City may not be covered. Many types of equipment, from vehicles to smart infrastructure, rely on computer syste ms. Sabotage of the computer system could result in physical damage to the asset.
• Betterment Coverage. This is coverage for expenses incurred to update, restore, or improve computer systems to a level beyond what existed before the attack. This might be important, for example, if the old system posed particular security vulnerabilities that could only be eliminated via a substantial

38 Retentions and deductibles not synonyms, but they are close. Retentions can include any source of loss not commercially insured – it is the risk retained by the holder of the policy. In the part of the policy this paragraph refers to, “retentions” are being used in a way that most people understand insurance deductibles.

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upgrade in the system. Note that the policy does not use the term “betterment coverage,” but rather spells out the concept as an exclusion.

That said, GFOA is not suggesting the City should have insurance coverage for all risks that could arise from a cyberattack. Such a policy might be cost prohibitive or even completely unobtainable. The City, though, should be cognizant of wh at risks the City is not commercially insuring because those risks are then being, de facto, self-insured.

Finally, some municipal governments have found cyber policies to be increasingly expensive or hard to get at all in recent years. Insurance companies are becoming more rigorous in their underwriting practices and are increasingly requiring that policyholders have risk -mitigating practices in place, like multi -factor identification and more. This has two implications for the City:
o The City should conti nue to stay up to date with nationally recognized cybersecurity standards.
o The City may need to be prepared to take on higher retentions for cyber policies in the future.

Given the points above, the City might consider the following recommendations that have implication for the City’s reserves:
• The City should remain open to investing in additional cost -effective cyber controls to help mitigate future risks. This is because a dollar invested in prevention is usually going to be more effective than a dollar invested in remediation.
• Be prepared to retain more risk on a cyber insurance policy. If policies were to become substantially more expensive (or, worst case, unavailable), the City could lower the cost by retaining more risk. This could be accounted for in the City’s reserve amount. As we stated above, it is conceivable that a cyberattack could cost the City’s more than the sublimits outlined in the policy. Therefore, “retention” of risk is not just the insurance deductible, but also includes the risk of a catastrophic attack that costs more than the policy limit or that causes damages that are not covered under the policy.

Because the costs of cyber risk are variable it is hard to estimate an amount to hold for a reserve with the available data. Hence, cyb er-attacks are not part of the probabilistic risk model GFOA has developed. The City’s current policy does cover many kinds of cyber risks. The City’s “retained” risks appear to be:
• The deductible costs, especially if the City is responsible for covering multiple deductibles that could arise from a single attack.
• Damages in excess of the sublimits under any of the individual coverages. • Uncovered risks, which should be remote relative to the risks that are covered.

GFOA has observed that $1 million is a comm on limit on cyber policies (the City already has an aggregate limit of $2 million). Given that most risks are covered, a conservative approach might be to add $1 million (or a lesser amount, such as $250,000 which is the high end of the deductibles listed in the policy) to the City’s “critical threshold” for reserves. That has the impact of raising the desired “floor” on reserves. A higher floor provides more flexibility to address risks that are not factored into

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the model. A less conservative approach wou ld be to rely exclusively on the City’s commercial insurance and a strong preventative posture and not hold additional reserves for cyber risk.

C. Manmade Risks like Hazmat and Terrorism
GFOA’s experience with cities that have a substantial presence of hazardous materials in the community is that risk to the general fund reserve is remote. According to City of Berkeley’s Local Hazard Mitigation Plan “over the last 25 years, Berkeley has seen a more than 90 percent reduction in the number of facilities with extremely hazardous materials ”. This means that hazmat risk is even more remote for the City of Berkeley.

With respect to terrorism, the Hazard Mitigation Plan says, “it is not possible to estimate the probability of a terrorist attack”.

For these reasons, we did not quantify hazmat or terrorism risk, specifically. However, the risk model does include the other hazards model, which provides accommodation for losses from unexpected sources, which could include hazmat releases or terrorism.

D. Comparable Analysis
This section compares Berkeley to an outside standard for fund balance . This information provides context for the City in selecting its own reserve levels. Reserves are a subset of fund balance.

Unfortunately, publicly available financial records often do not distinguish between a government’s fund balance and what they are holding in a reserve for the purposes of self-insurance. Therefore, we will look at the entirety of fund balance and compare it to the standards used by Moody’s bond rating agency for assigning credit scores. The scores range from Aaa (the best) to Ca (the worst). The measure Moody’s uses are “Available Fund Balance Ratio”, which compares fund balance to revenues. It is important to note that Moody’s considers fund balance across the entire government, not just general fund. The rationale is that, if it came down to it, a government would use fund balance from anywhere across its holdings to make a debt payment, rather than default. Moody’s assesses creditworthiness based on the lik elihood of repayment of debt. Moody’s basic formula for Available Fund Balance Ratio is:39 Available Fund Balance Ratio: (Available Fund Balance + Net Current Assets) / Revenue The table below shows a summary of the calculations of this Ratio for Berkeley, as the end of fiscal year 2023. The details behind the summary were reviewed with City staff. We can see at the bottom of the table that the ratio across all of City government is 75%. Moody’s standard for a Aaa rating is anything over 35%. So, by that me asure, Berkeley is doing quite well. We see in the table that if we limited our scope to just the governmental funds, then Berkeley would be above the standard for Aaa, though not nearly as much. Our table doesn’t show general fund balances in isolation, b ut the general fund balance is not much different from governmental funds as a group (52% of revenue).

39 Moody’s documentation describes nuances to calculate this formula, which we have included in our calculations.

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We should emphasize that the Moody’s rating system considers the whole government, so the governmental funds’ lower ratio should not impact the City’s rating, under Moody’s standards. Also, fund balances are one of several criteria that Moody’s and other rating agencies consider. This means a local government is not guaranteed a AAA bond rating by virtue of high fund balances alone. GFOA provided a separate report to Berkeley that provides an analysis of the other criteria that go into a bond rating.

We should also emphasize that the table below is a s napshot in time (end of fiscal year 2023). The risk model what we built for Berkely simulates the general fund over a future ten -year period. But the table below does show us that the City’s fund balances are, as of now, in a good position compared to the standard used by Moody’s bond rating agency.

To close this section, let’s summarize:
✓ Moody’s ratio is n ot a perfect proxy for what we are measuring in the GFOA analysis: we are measuring self-insurance capacity of the general fund, while Moody’s is measuring ability to repay bonds.
✓ Nevertheless, the Moody’s ratio and its associated benchmarks for bond ratings provide a clue: both reserves and Moody’s ratio are a product of the City’ fund balance. ✓ We can see that Berkeley’s level of fund balance is healthy when considering all of City government, when compared to rating agency expectations. Even if we limi t our scope to governmental funds (of which the general fund is part), Berkeley still does well. ✓ This analysis is a snapshot in time (the end of fiscal year 2023). Our risk model simulates the 54performance of the general fund over a ten -year period. The n ext section puts together all the previous parts of this report to present the conclusions from the simulation.

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Section 7- Putting it All Together
In Sections 4 and 5 we examined indiv idual risks such as recessions, fires, earthquakes, and more . We examined each of these risks individually in order to best unde rstand the nature of each risk and the financial implications. However, to arrive at a final reserve strategy for the City, we need to consider these risks as a group. Considering the risks as a group has important advantages.

The first advantage is that considering risks as a group recognizes the diversity in the risks that the City faces. This diversity actually is an advantage for City finances! Diversity in risks means we should not simply add together a reserve for each individual risk. This may overstate the amount of reserves that the City really needs. This is because it is unlikely , for example, that the City will experience a deep recession, a severe earthquake, and severe fire all within a short time period.

The second advantage of considering all of the risks together is that not all of the risks have an equal chance of occurring over a given time period. Recessions are more common than a 7.0 magnitude earthquake. The reserve analysis should reflect this fact. We can use relative chance of each of the major risks occurring over a ten-year period to build a model of risks over a long-term time horizon.

The final advantage of considering all the risks together is that we can consider “risk interdependencies.” This simply means that the occurrence of one risk could impact the probability and/or magnitude of a related risk. In Berkeley’s case, a good example an interdependency is revenue performance and pension burden. The worse the economic performance is over a ten -year period, the worse the implications are both for Berkeley’s revenue income and pension burden. There are also interdependencies between revenues during a recession. Some revenues decline right away while others take longer to decline. Other than that, there does not appear to be any critical interdependencies. It is not unusual for local governments GFOA has worked with to not have many interdependencies.

To realize the advantages described above, we built a model that considers the City’s risks over a ten-year time horizon. The GFOA Risk Model runs ten thousand simulations of possible futures for Berkeley. Below are the key assumptions behind the model. Some of these assumptions are user-definable so that the City can explore alternative scenarios to those described in the report. Below, we have italicized user definable variables and described the default values included in the model. • Probability of an undesirable event. The probability of any undesirable event occurring is consistent with the assumptions described in Sections 4 and 5 of this report. • Magnitude of an undesirable event. Should a simulation show that an undesirable event occurs each year, the magnitude is generated randomly in a manner identical to how we described for the risks earlier in this report.
• FEMA / CalOES reimbursement. The City could recoup some of its losses from extreme events, such as floods, fires, and earthquakes from reimbursements from FEMA and CalOES. The model assumes the reimbursements are received two years after the event occurs.40 The model assumes all large natural catastrophes would be assisted by FEMA. Small ones may not. CalOES would supplement FEMA in all the cases above. We also assume the City will be reimbursed at the

40 Our research shows that FEMA reimbursements are completed 18 months after the disaster occurs, on average.

So, this is a conservative assumption.

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customary rate of 75% of incurred costs by FEMA. We assume 18.75% reimbursement from CalOES. We also assume there is some amount of losses that do not fit into FEMA reimbursement (beyond the 25% local share) that the City will need to bear. The amount varies by type of disaster but ranges from 35% to 10%.41
• The City does cut some spending to help offset the impact of a recession or an extreme event.

At least some of the losses from a recession or extreme event could be absorbed by cutting back on the City’s regular spending. The Risk Model provides the user with the ability to set the amount of spending the City is willing to cut and pick between various cost cutting strategies. For the purposes of the discussion in this report, we worked with City staff to select a set of st rategies that amounted to about a 4.5% reduction in the annual budget. We strove to be consistent with past experiences the City has had in balancing its budget. The user of the model can easily select a different set of strategies.
• The City will have a t ough time generating budget surpluses in years when there is not a recession. In the past, the City has usually generated surpluses in years when there is not a recession. However, forecasts by the City staff project deficits for the next few years and continued, though less acute, challenges in balancing the budget for a few years after that. Hence, the risk model simulates continued deficits as the most likely future outcome for the next few years (but not a certain outcome – the model still provides a small chance of surpluses) and then a break-even budget for the next few years, and finally a small surplus for the last few years.

There is possible variation built into the simulation so that any year is capable of generating a surplus or deficit (just like in real life), but the most likely outcome is as described above. • Critical threshold. This is the amount that the City does not want fund balance or reserves to go below. For the purposes of this report , we set the critical threshold for general fund balance at the amount Moody’s bond rating agency looks for in a Aaa credit: 35% of revenues. For reserves, we set the threshold at zero. This would be the point at which the City’s “self-insurance” capacity provided within fund balance is exhausted. The model simulates the interaction between fund balance and reserves as well. So, if reserves are exhausted, then fund balance picks up the slack. • Pension trust fund. The City has a pension trust fund. The pension trust fund is in the model and helps absorb excess pension costs. The pension risk model and the role of the pension trust fund was described in detail in Section 4 of this report.
• City’s starting fund balance and reserve. The starting reserves are $130.7 million. Reserves are a subset of fund balance and are equal to $40.7 million to start. As per conversations with City staff, this is the amount the City has been considering the “reserve” amount within fund balance.

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41 A recent high wind event in the City produced costs that were not reimbursable by FEMA in an amount equal to about 50% of the costs that were. Hence, 50% is not an unrealistic upper limit.

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We combined all the information described above to create a ten-year probabilistic model. The City’s goal for this analysis was to find an amount that can give the City sufficient comfort that its fund balance and reserves will be sufficient. We next present a series of graphics based on this model.

Exhibit 7.1 compares fund balances and reserves to thresholds that the City is concerned about.

For fund balance, the threshold is the amount of fund balance associated with Aaa bond rating, according to the bond rating agency Moody’s: an amount equal to at least 35% of general fund revenue. An important caveat must be noted, however. Moody’s evaluates fund balance across the entire local government, while our analysis is just for the general fund. Thus, our analysis is really asking about the chance that the general fund can carry its “fair share” of the load of meeting rating agency expectations and not if the City, overall, will be able to meet rating agency expectations.

For reserves, the threshold is zero. Zero represents the “self-insurance” aspect of the City’s reserves running out.

In Exhibit 7.1, we see there is a very high chance, approaching 90% (or 9 in 10) that the City’s fund balance will go below the amount associated with a Aaa bond rating. Again, we should draw attention to our caveat that a bond rating is based on the entire City government, while our analysis covers only the general fund. As of this writing, the position of the City’s other funds is currently strong enough to keep the entire City is Aaa territory, but our analysis says nothing about the chances of this continuing. Another important caveat is that fund balance is just one of several criteria that bond rating agencies consider, so a decline in fund balance below the Aaa threshold does not necessarily mean that the Ci ty will be downgraded – perhaps other aspects of the City’ financial condition could balance out a declining fund balance.42
Exhibit 7.1 also addresses reserves, where there is just over a 20% chance that that the reserve will reach zero at the end of ten y ears. This is a greater chance than GFOA has observed most municipalities are comfortable with.

It is important to note that, g enerally, the bars in presentations like 7.1 will get higher the further in the future we look because more bad things can happen. That said, we should also note that a very important cause of the rising height of the bars is the assumption we described earlier about the City having a “tough time generating budget surpluses” in the next few years. For example, if we were to change t he most likely outcome of our surplus -or-deficit simulation to just “zero” or break -even, the chance of the City’s fund balance being below Aaa in year ten improves by around 15 percentage points (about a 75% chance).

The impact in the near term is even gr eater: 5 years out the chances improve by 25 percentage points (from a 65% to 40% chance of going below the critical threshold). The pension risk described in Section 4 of this report also adds a persistent drag on the City’s finances, including its fund balances and reserves.

42 GFOA did a separate analysis on bond rating for the City which goes into the factors Moody’s considers and the City’ relative position on each.

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Exhibit 7.1 – Chance Fund Balance + Reserves is Less than Bond Rating Aaa and Chance Reserve is Less than Zero.

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Exhibit 7.2 shows the average remaining fund balance and reserves each year. Perhaps unsurprising given the rising bars in Exhibit 7.1, Exhibit 7.2 shows the lines on a downward trajectory. It shows that the City’s fund balance falls below the Aaa threshold, on average, in the fourth year of the analysis. On average, reserves stay above zero each year. Note that the threshold for reserves is set to zero, so the dotted red line that represents this threshold may be difficult to see because it overlaps the black line border that is also at the zero position.

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Exhibit 7.2 – Simulated Remaining Fund Balance and Reserve each Year

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Finally, below is Exhibit 7.3. This is a cumulative probability chart. It shows the confidence available from varying levels of reserves. Berkeley’s e xisting reserve intersects the blue line at about 80% confidence, which means there is an 80% chance that the City will have an amount of reserves greater than zero in the tenth year of the analysis. This is the other side of our earlier conclusion that th ere is about a 20% chance of the reserves being less than zero in year ten. This graphic adds an element for GFOA’s rule-of- thumb on the minimum amount of fund balance a City should maintain, which is equal to at least 2 months (16.6%) of revenues.43 Currently, the City is just short of that amount if we focus just on the City’s reserves.

Exhibit 7.3 shows the amount of money that would be needed in the reserve in year 1 to have a given level of confidence that reserves would remain above zero or 16.6% of revenues in year 10.

A key takeaway is that reserves have a diminishing return at a certain point because the flatter the line gets, the less confidence an additional dollar of reserve “buys” you. This is because the further to the right you go on the graph , the more extreme the events are that must be covered by reserves. This graphic shows that the City would still get a good “bang for the buck” from higher reserves than it has today. This City would not be as well served by accumulating reserves past the point where the line starts to flatten.

Exhibit 7.3 – Cumulative Probability Chart

TThe GFOA rule of thumb concerns unrestricted fund balance of which reserves are typically a subset.

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The implication of the line going flat is that not all points on the line are equally cost effective. Let’s examine Exhibit 7.3 to illustrate. According to the graph, to be 90% confident of staying above the zero threshold requires a reserve of $58.7 million. To be 95% confident requires a reserve of $ 72.2 million, a difference of about $ 13.5 million from 90% confidence. To be 99% confident requires $ 104.9 million, which is about $32.7 million more than the amount required to be 95% confident. Thus, it is almost three times as much to “buy” a similar increase in confidence. This is the point where the line in Exhibit 7.3 goes flat, and it is not efficient to build reserves.

The City can use the results of this report to optimize the range of general fund reserves it would like to hold. GFOA recommends the City establish a floor and a ceiling amount of reserves. The ceiling is an amount of reserves the City will try not to exceed and a floor is an amount that the City will try not to go below and will try to replenish the reserves quickly if they do go below the floor. GFOA cannot recommend a precise amount of reserves the City should maintain, but our analysis does provide a clear general direction, and our risk model provides the ability to “stress test” different reserve strategies. The reason we cannot make a precise recommendation is that a big part of determining a desirable reserve amount is the “risk appetite” of City o fficials. Officials who are risk averse may prefer more reserves. Those who are less averse and perhaps more sensitive to the opportunity costs of holding reserves may prefer less.

City officials will also want to think about other factors to finalize the reserve target range. This is because Exhibit 7.3 cannot account for every possible factor that should go into deciding how much Berkeley should keep in its reserve. The numbers shown in the exhibit are what is needed to protect the City from just the risks described in this report and to keep the reserve above zero (and fund balance within Aaa territory). Usually, municipal governments have other concerns they expect their reserves to address.

Here are examples of such concerns:
• There are risks that are s ometimes called “unknown unknowns.” These are risks that are totally unanticipated. Our risk model does include an “other hazards” simulation which should go a long way towards addressing unknown unknowns.
• Our Risk Model is based largely on historical dat a, which, by definition, does not capture the potential future impacts of climate change. It is impossible to say what the future impacts of climate change will be. This might suggest a more “risk averse” approach to reserves (i.e., maintaining more, rather than less).
• The City might wish to use fund balances for purposes other than mitigating risks – for example, building a capital project using cash financing. The Risk Model gives the City the ability to estimate the cost of potential projects to see the financial impact of redirecting reserves to other uses .44 More broadly, City officials should consider opportunity costs of holding reserves: w hat are alternative uses of the funds and how do those benefits compare to self-insuring against the risks described in this report?

44 Note that the City has historically done some level of cash financing of projects. The model already accounts for “normal” spending that takes place in the City’s annual budget, so this feature of the Risk Model would be used for larger projects that exceed what might be considered “typical.”

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The considerations above could be addressed by choosing a robust floor and ceiling level for reserves.

Different floors and ceilings can be “stress tested” by changing thresholds that the model measures against. GFOA’s discussions with the City staff suggested a threshold of zero for reserves is useful for assessing the risk of exhausting the “self -insurance” capacity of its fund balance. We have used the zero threshold the Exhibits show in Section 7 of the report. The City could choose to vary this critical threshold, which would then change the total amount of reserves the City would need to maintain to achieve a given degree of confidence that reserves would stay above the threshold. For example, perhaps the City selects a threshold of 5% or 10% of revenues to provide a buffer against going all the way to zero.

Here are some other conclusions we can draw from the graphics presented on the previous pages:
• The City’s ability to generate surpluses has a significant impact on the chances that fund balance and reserves go below thresholds . Later in the report we recommend a “structurally balanced budget policy” to help the City more consistently generate balanced budgets, if not surpluses. • If the City does generate surpluses, it must then choose to direct those surpluses towards building the reserves. A one-time or volatile revenue policy, discussed in the recommendations later, could help in this regard.
• The City should remain mindful of the potential for extreme consequence events. A large earthquake could impair the taxbase. GFOA found that this caused the City’s risk model to produce some extreme results. In Exhibit 7.3 the reader will notice that the red line extends very far to the right, past $200 million. This tells us that there is a small chance of some very extreme outcomes, due to the City’s vulnerability to earthquakes and tax base impairment. Later in this document, we will discuss parametric insurance as an alternative to reserves to protect the City against these extreme cases.

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GFOA discussed all the factors above with the City staff and the conclusion of this discussion was that the City of Berkely would be well served by a policy that calls for general fund reserves equal to between 20% and 30% of the City’s revenues. This gives the City between about 87% and 97% confidence of being able to handle the risks included in our analysis while also keeping the reserve above zero.

We could also compare the policy range to the City chances of staying above 17% of revenues, which is the equivalent of two months of revenues.45 This amount of reserves is a long -standing rule of thumb in public finance. Reserves equal to 20% to 30% of revenue provide between a 26% and 73% chance of handling the risks included in our analysis while also keeping reserves above 17% of revenues. The tables below summarize what we just described.

GENERAL FUND RESERVE SUGGESTIONS RELATIVE TO STAYING ABOVE THE CRITICAL THRESHOLD CRITICAL THRESHOLD = 16.7% of Revenues or $44M
A Reserve Policy typically expresses reserve targets as a percent of expenditures or revenues.

Below we have converted the dollar figures to a percent of revenues.

Dollars Percent of General Fund Revenues
$53.5 Million
26% confident of staying above
critical threshold over ten years 20%
$83.0 Million
73% confident of staying above
critical threshold over ten years 30%

GENERAL FUND RESERVE SUGGESTIONS RELATIVE TO STAYING ABOVE ZERO A Reserve Policy typically expresses reserve targets as a percent of expenditures or revenues.

Below we have converted the dollar figures to a percent of revenues.

Dollars Percent of General Fund Revenues
$53.5 Million
87% confident of staying above zero
over ten years 20%
$83.0 Million
97% confident of staying above zero
over ten years 30%

On the next page, we will discuss the context and rationale for this recommendation.

45 2 months of 12 months is the same as is 1 in 6. 1 in 6 is 16.67%, which rounded up is 17%.

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For context, let’s first recall that the City’s reason for undertaking this study is to update its reserve policy in order ensure that its r eserve targets are appropriate given the risks that the City faces. These recommendations provide that update.

Next, we are suggesting that the City think of its reserves as a range (a ceiling and floor) that it wishes to remain within. This contrasts with identifying a single target for reserves. The dynamic environment the City is within makes it very difficult to hit and maintain a single target number . It is more practical to manage within a range or boundary. The suggested floor is reserves equivalent to 20% of revenues and the ceiling is 30%.

As for rationale, first, the suggested range gives the City a very good chance of staying above zero reserves – an 87% chance, on the low end. As for staying above the two-month rule of thumb (reserves equal 17% of revenues), the chance is substantially less, but we believe this is acceptable for two important reasons.

First, the two-month rule of thumb is loosely based on bond rating agency expectations. As we discussed earlier, the risk model addresses bond rating agency expectations directly. Hence, we’d suggest that the City keep its eye on the chances of missing bond rating agency expectations directly, instead of monitoring them indirectly via this rule of thumb. Secondly, the rule of thumb assumes the user h as no additional knowledge of the exposure to risk. As this report has shown, we have a great deal of knowledge about the City’s exposure to risk. Therefore, the City probably does not need the entire margin against risk that staying above the rule of thumb would provide.

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The other important rationale is the cost-effectiveness of this choice. The reader may recall Exhibit 7.3, which spoke to the cost -effectiveness of various levels of reserves. Exhibit 7.4 reprod uces the same presentation but adds the recommended range of reserves to the curves. The reader may recall that when the curve starts to flatten out , we have reached the point of diminishing returns on the benefit of building reserves. In Exhibit 7.4, t he colored dot that is furthest to the right on each curve is the ceiling and the leftmost dot is the floor. The ceiling dots and floor dots represent the same dollar amount on both curves – the ceilings and floors are at same points on the horizontal axis.

We see that we are starting to reach the flat portion of the blue curve (the reserve needed to stay above zero) but still have plenty of room on the red curve (the reserve needed to stay above 17%). This is a cost- effective range for the City because the City is avoiding the flattest part of the blue curve, while also staying on the steepest points of the red curve. As implied earlier, the red curve likely represents a more conservative standard, so it would be cost ineffective to reach the flat part of the red curve. Conversely, the blue curve is a less conservative standard, so even though the proposed reserve is not on the steepest part of the curve, the marginal benefit of additional reserves is still positive.

Exhibit 7.4 – Cumulative Probability Chart with Proposed Range of Reserves

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To complement the reserve analysis, we offer the following additional recommendations:

The City should update its robust reserves policy. GFOA has conducted extensive research into what it takes for a local government to be financially sustainable. We call this body of work “Financial Foundations for Thriving Communities ” (Financial Foundations) . This research has shown that local governments require clear decision -making boundaries. A policy on the target level of res erves that the City should maintain, and the acceptable use of those reserves provides clear decision -making boundaries for reserves. This City has a robust policy in place to govern reserves. The most important potential refinement to the policy is that, as was discussed earlier, the policy could identify both a floor and ceiling for reserves, rather than just a single target number, as in the case with the current policy. Having a range defines the acceptable tolerances the reserves should stay within.

Another possible refinement is to combine the Stability Reserve and Catastrophic Reserve into a single reserve. The Risk Model treats all risks as part of the same City risk profile, so produces an analysis result that speaks to this comprehensive risk profile. Combining reserves is a form of risk pooling. Risk pooling works when you combine uncorrelated risks. Recessions and natural catastrophes are not highly correlated,46 so the City should be able to realize efficiencies by combining those risks into a single reserve.

The City should adopt a mechanism to monitor its own compliance with the policy. GFOA’s Financial Foundations research suggest s that boundaries (e.g., financial policies) must be monitored to be fully effective.

The City of Tempe, Arizona provides a good example of how a reserve policy can be monitored. Tempe’s policy is to maintain the general fund reserve equal to between 20% and 30% of general fund revenues.

The general fund reserve policy is combined with Tempe’s five -year financial forecast, where the goal is to keep reserves within the 20% to 30% boundary during the five -year forecast period. This approach originated in 2009 when Tempe had a policy to maintain reserves equal to 25% of general fund revenues.

However, Tempe had been maint aining fund balances above 30%, which was causing some to question why Tempe was not in alignment with the policy and whether Tempe had a fund balance that was too large. The City Council and staff agreed to change the policy to set a goal for the reserves to be between 20% and 30% of revenues. This range would provide more discretion, but it would also create clear bounds for what Tempe would consider acceptable maximum and minimum reserves.

Tempe staff developed a presentation of Tempe’s revenue forecast in the context of this new arrangement and informally called it the “Golden Cone of Prosperity.” Exhibit 7.5 shows the presentation as it was in 2009, where the yellow cone representing the range of desired fund balance widens over the forecast horizon as the new policy is phased in and the black line representing actual fund balance gradually enters the cone.

46 We stop short of saying uncorrelated because a big earthquake could impair the tax base, which might be like a hyperlocal “recession”. The Risk Model accounts for this possibility.

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Exhibit 7.5 —Tempe’s Golden Cone of Prosperity in 2009

The meaning of the Golden Cone of Prosperity is straightforward, and its design and name giv e it a memorable character. As of 2020, Tempe staff still present the Golden Cone twice per year to help public officials understand the big picture and to show whether Tempe is staying within agreed -upon boundaries. This is a testament to the communicative power of the Golden Cone. Berkeley could develop a similar presentation to help make sure the City stays within its agreed upon financial boundaries.

Adopt a policy of objective forecasting and conservative budgeting. The City is projected to run deficits for the next few years . This places a stress on reserves . So, the question becomes: how can services be expanded without putting the City’ s finances at excessive risk? There are several budget policies and practices the City could adopt to support good public services while safeguarding its financial position at the same time.
• Understand the risk of increasing on-going expenditures. The risk of adding more services to the City budget is that it makes it more likely the City will run a deficit and need to cut back . So, the balance the City needs to find is: how much can expenditures be increased without incurring unacceptable risk? The City can adopt forecasting methods that highlight the risk of the City budget getting out of balance. The City can als o adopt a range of policies to protect against this risk, as outlined below.
• One-time revenue policy. Limit the use of one -time, non-recurring revenues to one -time, non- recurring expenditures or to pay down liabilities (e.g., catching up on deferred asset maintenance, like a park, road, etc., or making additional discretionary payments to CalPERS to reduce unfunded actuarial pension liability). An example of a one-time, non-recurring revenue would be proceeds from a lawsuit or the sale of an asset.
• Volatile revenue policy. Some revenues, like sales taxes, are recurring, but they can go up and down substantially from year to year . A volatile revenue policy would treat extraordinarily high annual revenues from a volatile source as a one -time revenue. The bulk of the revenue income would be treated like a recurring revenue – it is just the extraordinary amount that would have

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more limited uses. This protects the City from using peak revenues to over -invest in programs that must be supported for many years. The City already has a policy like this for its transfers tax.

We are suggesting that such a policy be extended to cover other volatile revenues as well. This would serve to help the City maintain a stable, dependable set of on-going services over the long- term because it would help the City avoid over -expanding services beyond what is truly affordable.
• Adopt a structurally balanced budget. Cities are required to adopt a balanced budget by law.

However, this just means financial sources must equal uses . So, for instance, City Hall could be sold off (a non -recurring revenue) and the proceeds used to hire more firefighters (a recurring expenditure). This would, of course, be a bad idea. A structurally balanced budget policy commits the City to balancing its recur ring revenues and recurring expenditures and balancing its non - recurring revenues and expenditures, separately.
• Adopt a phased schedule of spending on non-recurring expenditures and condition spending on forecasts being met . As part of its budget, the City could adopt a prioritized list of one -time expenditures, in addition to its regular on-going expenditures. The total of the one-time and on- going expenditures would be equal to or less than the City’s projected revenue. The one -time expenditures would the n be made throughout the year, in priority order, and conditioned on revenues coming in as projected. If revenues underperform the City’s forecasts, then the lower priority expenditures would not be made.
• Adopt flexible strategies for providing on -going services. It is unlikely that all the City’s service goals can be met through one-time expenditures. New on-going services may be needed. The City could look for opportunities to adopt flexible service models, where costs can be scaled up or down. Contracted services often can provide flexibility that in -house staff cannot. This is not to say that in-house staffing is undesirable. There may be situations where in-house staffing is better, but there may also be opportunities where contracts can provide financial flexibility. • Affirmative reauthorization of spending. The conventional approach to budgeting is that once a new service is authorized it is “baked in” to the budget and is funded year after year. This can lead to financial distress when new services ar e layered on top of old services. An alternative is to require affirmative reauthorization for a new service. This could be especially useful where a new service is intended to achieve some clear public policy goal. At the end of some set period, the City Council could be required to explicitly reauthorize funding based on whether the program is achieving its stated goals.

The City should consider further investments in cybersecurity. Cybersecurity is an emerging and growing threat for local governments. As we described earlier, available data suggests several sobering points:
• Local governments are an attractive target for cybercriminals and ransomware attacks against local governments are common.
• The amount of damage from an attack appears to only be weakly correlated to the size of the government. Data suggests that the average attack costs around $ 100,000 but attacks can and have cost local governments many millions of dollars. Even though Berkeley is not as large as cities that have made headlines for multi-million-dollar losses incurred by an attack, Berkeley could still suffer a substantial loss – perhaps more than its policy limits. • Cyber insurance policies can get expensive and hard to come by when insurance markets harden.

Given the points above, the City might consider the following recommendations that have implication for the City’s reserves:

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• Continue planning for enhanced security and make cost -effective investments in cybersecurity controls that both: A) reduce the likelihood of a successful atta ck; and B) reduce the potential damages, if an attack succeeds. Because reserves are ultimately a form of self -insurance there could be a strong case for using some of the City’s reserves to strengthen its cybersecurity. This is because a dollar invested in prevention is usually going to be more effective than a dollar invested in remediation.
• Be prepared to retain more risk on a cyber insurance policy. If policies get substantially more expensive (or, worst case, unavailable), Berkely could lower the cost by retaining more risk. This could be accounted for in the reserve amount. As we stated above, there is a plausible risk of a cyberattack costing the city more than $1 million . Therefore, “retention” of risk is not just the insurance deductible, but also includes the risk of a catastrophic attack that costs more than the policy limit.

For natural hazards c onsider “parametric” insurance in addition to traditional indemnity insurance.

Indemnity insurance is the type of insurance that most governments have traditionally purchased, where the insurance corresponds to the value of the assets being insured and reimbursement is paid out after a certain deductible has been met. The advantage of traditional indemnity insurance is that there is a known damage threshold past which the City is covered.

Parametric insurance is a newer type of insurance for providing coverage for extreme events, having increased in popularity in the last 15 years or so in the public sector but has been in use in the private sector for decades. Parametric coverage provides the policyholder (the City) with a payment amount that is defined ahead of time, should a defined event come to pass (a n earthquake of a certain magnitude).

Parametric insurance could be more useful for providing an injection of liquidity because the policyholder receives the defined payment immediately upon verification by a third -party that the given event occurred, which usually would be within a matter of days. As a simple illustration, a parametric policy might provide the City of Berkeley with $5 million upon the occurrence of an earthquake of some given magnitude, after magnitude is verified by a third -party, such as the USGS . This feature of parametric insurance also eliminates much of the administrative hassle that would be associated with a traditional indemnity policy (e.g., working with claims adjusters). A final advantage is that the proceeds from the policy payout are completely fungible – the City could use them to fund whatever service it deems necessary or to counteract revenue loss from tax base impairment, whereas indemnity policies might require the policyholder to use the funds to repair or replace the asset that was insured. Parametric policies are not without their drawbacks, though, and are not a substi tute for traditional insurance. The City can learn more about parametric policies in the publicly available GFOA research report “Parametric Insurance: An Emerging Tool for Financial Risk Management.”47 A robust insurance strategy could make use of both tr aditional indemnity and parametric insurance. For example, traditional indemnity insurance could be used to protect against loss of the City’s assets, while parametric insurance could be used to compensate the City for the losses in tax revenue it would experience from an impaired tax base, for instance.

47 Available at: https://www.gfoa.org/parametric-insurance/.

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The City could consider a robust internal borrowing policy. There will always be some chance that Berkeley could find that it needs access to more financial resources than are available in its reserves.

GFOA’s research suggests that interfund borrowing could be a practical “last line of defense” in emergency circumstances. Some other funds might be able to make short -term loans to the general fund in case of an emergency. The City could develop policies to provide the flexibility to use these borrowing tools while also providing the necessary guidelines and limitations to ensure that borrowing occurs in a fiscally prudent manner.

Berkeley might consider if a policy could recognize internal borrowing’s role as a supplementary risk management tool. A policy would “pre -position” the City to better respond to an extreme financial catastrophe. A policy could address the following points:
• The rationale for using internal borrowing (reserves may not be able to hand le every possible contingency).
• When internal borrowing may be used (if reserves are ever exhausted by an extreme event). • Differentiate between short -term (to be paid back within the same fiscal year) and long -term borrowing.
• How the interest on the borrow ing will be calculated (can have multiple alternatives to be determined on a case-by-case basis); and
• General repayment terms (e.g., interest only, fully amortized, duration, etc.).

GFOA’s analysis has its limits. It is impossible for any risk analysis to be completely comprehensive of all considerations facing the City. Appendix 1 to this report lists the important limitations of this analysis.

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Appendix 1 – Limitations of GFOA’s Analysis
This section highlights the most important limitations of our analysis.

Our analysis is not predictive. GFOA does not forecast future recessions, natural disasters, or other extreme events. Rather, our model generates hundreds or even thousands of different scenarios to show how the future could unfold. This helps the City think more broadly about risk so that it can be more prepared for whatever future event does eventually come to pass. Finally, it is important to note that low probability events are still possible events. Hence, even if our model says an event has a low probability, then that does not mean it won’t occur.

GFOA is not a risk management consultant. We worked with the City to find out which risks the City believes are most salient and then model ed those risks quantitatively to judge the potential financia l impact. We are not risk managers and it is not our role to tell the City which risks it should be more concerned about or less concerned about or what the best way is to manage those risks.

Our analysis is based on historical records. Historical data is often a good way to model potential future outcomes. However, historical data may not be perfect. For example, global climate change could increase the City’s vulnerability to naturally occurring extreme events. 48 This means that historical data could underestimate the likelihood and/or severity of extreme events in the future. Unfortunately, no one can say precisely what the impact of climate change will be. Hence, GFOA can’t speculate if an upward adjustment to the reserves is necessary and, if so, by how much. However, this does mean that there could be a case for reserving a higher amount than the efficient range described in our report (or pursuing other risk management strategies). Also, GFOA’s Microsoft Excel Risk Model provides the City with the ability to adjust the likelihood and/or magnitude of many types of natural catastrophes. This feature could be used to test different scenarios, including ones where climate change is assumed to increase the likelihood and/or magnitude of extreme events.

Our analysis is not inclusive of every risk the City could possibly face. We examined the City’s history and worked with City staff to identify the risks that posed the most clear and present danger to the City.

However, it is possible that the City could experience a shock that no one was expecting. Hence, there is a case for reserving more than our analysis suggest is efficient. This could provide additional protection against risks that no one can foresee. Being prepared for these “unknowable” events is part of the value of the “red line” or critical threshold that our reserve analysis considered. Our model also includes an “other hazards” simulation to account for completely unanticipated risks. However, this does not mean that the City doesn’t need to prepare for risks that aren’t specifically included in our model.

48 According to the Fourth National Climate Assessment created by the U.S. Global Change Research Program (USGCRP) and released in November 2018: “more frequent and extreme weather and climate-related events, as well as changes in average climate conditions, are expected to continue to damage infrastructure, ecosystems, and social systems.” The report cites climate -related risks to communities “from adverse weather and climate related events such as extreme storms or wildfires.” https://nca2018.globalchange.gov/chapter/1/.

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Our model is focused on general fund reserves as a risk mitigation tool. Other mitigation tools, such as insurance, can provide additional resources to respond to an extreme event. We did not judg e the adequacy of the City’s insurance program.

Good decisions do not always lead to good outcomes . Excel simulation tools can enhances one’s perception and understanding of uncertainty and risk. 49 However, when dealing with uncertainty, even the best deci sion may not lead to a good outcome, if luck goes against you. 50 To illustrate, imagine an insurance company was willing to sell Berkeley an insurance policy against being hit by a meteor for $50 million. A meteor strike is an extremely remote risk, so spending $50 million on an insurance policy would not be a wise decision. Imagine Berkeley does then get hit by a meteor that causes $100 million in damage.

Should you criticize the decision not to buy insurance? No, because the decision was reasonable given the information available at the time and there was no way to predict a meteor hitting the City. Similarly, our model may show that a given amount of reserves is reasonable under most conditions, but Berkeley could encounter a confluence of undesirable events that the reserves are insufficient to address.

49 To survive in an increasingly unpredictable world, we need to train our brains to embrace uncertainty, Emre Soyer, Quartz M agazine, January 9, 2017 https://qz.com/879162/to-survive-in-an-increasingly-unpredictable-world-we- need-to-train-our-brains-to-embrace-uncertainty/.
50 This is one of the primary lessons in: Annie Duke. Thinking in Bets: Making Smarter Decisions When You Don’t Have All the Facts. Portfolio. 2019.

Date Transaction Descriptions Amount
Balance as of
6/30 Amount
Balance as of
6/30
Combined
Reserve Balance
as of 6/30 GF Revenues
Contributions
needed for the
year
7/1/2016 -
5/4/2017 Transfer in from GF 12,421,507 10,163,051 6/30/2017 12,421,507 10,163,051 22,584,558 191,835,406 11.77% 10/1/2017 Transfer in from GF 2,001,415 1,879,430 6/30/2018 14,422,922 12,042,481 26,465,403 198,942,336 13.30% 12/30/2018 Transfer in from GF 5,600,000 4,580,000 6/30/2019 20,022,922 16,622,481 36,645,403 211,942,253 17.29% 12/30/2019 Transfer in from GF 640,000 520,000 6/30/2020 20,662,922 17,142,481 37,805,403 223,687,645 16.90% 7/18/2020 Transfer out to GF (6,900,000) (4,500,000)
1/29/2021 Transfer in from GF 1,836,309 1,502,434 6/30/2021 15,599,231 14,144,915 29,744,146 232,028,202 12.82% 7/28/2021 Transfer in from GF 1,375,000 1,125,000 1/31/2022
Transfer out to Playground
Camp (ERMA 125) (2,700,000)
1/31/2022 Transfer in from GF 2,261,005 1,849,913 6/30/2022 19,235,236 14,419,828 33,655,064 286,618,657 11.74% 7/29/2022 Transfer in from GF 3,025,000 2,475,000 6/21/2023 Transfer in from GF 837,341 685,098 6/30/2023 23,097,577 17,579,926 40,677,503 276,337,325 14.72% 6/12/2024 Transfer in from GF 7,486,574 6,125,380 6/30/2024 30,584,151 23,705,306 54,289,457 273,301,176 19.86% Projected Revenues and Contributions needed (20%)
6/30/2025 54,680,820 273,404,100 20.00% 391,363 6/30/2026 58,316,670 291,583,351 20.00% 3,635,850 6/30/2027 59,436,284 297,181,421 20.00% 1,119,614 6/30/2028 60,468,779 302,343,897 20.00% 1,032,495 6/30/2029 61,549,314 307,746,569 20.00% 1,080,534 Projected Revenues and Contributions needed (30%)
6/30/2025 82,021,230 273,404,100 30.00% 27,731,773 6/30/2026 87,475,005 291,583,351 30.00% 5,453,775 6/30/2027 89,154,426 297,181,421 30.00% 1,679,421 6/30/2028 90,703,169 302,343,897 30.00% 1,548,743 6/30/2029 92,323,971 307,746,569 30.00% 1,620,802 GF-Stabilization Reserves GF-Catastrophic Reserves Combined Reserve
Balance as
Percentage of
GF Revenues

Office of the City Manager
2180 Milvia Street, Berkeley, CA 94704 ● Tel: (510) 981-7000 ● TDD: (510) 981-6903 ● Fax: (510) 981-7099 E-Mail: [email protected] Website: http://www.CityofBerkeley.info/Manager

CONSENT CALENDAR
July 29, 2025
To: Honorable Mayor and Members of the City Council
From: Paul Buddenhagen, City Manager
Submitted by: Henry Oyekanmi, Director, Finance
Subject: Contract No 32400009 Amendment: Stella Courier, LLC. for Mail Services and Mail Room Coverage

RECOMMENDATION
Adopt a Resolution authorizing the City Manager to amend Contract No: 32400009 with Stella Courier, LLC., to provide mail services to the City’s satellite locations, and as- needed mail room coverage, increasing the amount by $180,000 for an amended total amount not to exceed $360,000 over an additional two-year period starting August 1, 2025 through July 31, 2027.

FISCAL IMPACTS OF RECOMMENDATION
Mail delivery and mail room back up services are funded through the mail services internal services fund, budget code 674-33-325-347-0000-000-472-612990. Commission packet delivery is funded in 621-53-584-622-0000-000-474-639130. Costs for the services vary based on actual monthly mail volume and service requests, and are not-to-exceed the amended amount of $360,000.

CURRENT SITUATION AND ITS EFFECTS
The City still has a need for these specific, specialized, services. As such, the City released Request for Proposals #23-11568-C on January 25, 2023.

Staff evaluated the proposal from Stella Courier to provide human-propelled courier and mail services. Stella Courier meets all the RFP requirements, including social responsibility criteria, and has the demonstrated capability to perform the scope of services in the same environmentally friendly manner as the previous firm.

BACKGROUND
The City has historically utilized a contractor to make delivery and pick-up of city mail at satellite office locations, provide mail room coverage, sorting, and internal department mail delivery, in addition to providing needed courier service. The services are still required, and it has been required that the scope of work be completed using bicycles only in order to minimize the City’s carbon footprint while still providing satellite mail services.

Contract with Stella Courier, LLC – Mail room and mail services CONSENT CALENDAR July 29, 2025

ENVIRONMENTAL SUSTAINABILITY AND CLIMATE IMPACTS
Servicing central City locations, satellite locations, and delivery of commission packets is performed without utilizing a gas-powered vehicle, thus reducing the City’s carbon footprint in the execution of these contracted services compared to performing these services using a gas-powered vehicle while making multiple short trips throughout the City. This supports the City Council Strategic Plan Goal for being a global leader in addressing climate change, advancing environmental justice, and protecting the environment.

RATIONALE FOR RECOMMENDATION
Stella Courier was the only respondent to a Request for Proposals issued by the City.

Stella has offered fair rates. There is an ongoing need for mail services to the satellite locations, and for ensuring back-up staffing for the central mail room.

ALTERNATIVE ACTIONS CONSIDERED
Utilizing part-time staffing was previously explored and determined to be cost-prohibitive and difficult to arrange due to the unscheduled nature of the work.

CONTACT PERSON
Henry Oyekanmi, Director of Finance 510-981-7324
ATTACHMENTS:
1: Resolution

RESOLUTION NO. ##,###-N.S.

CONTRACT NO 32400009 AMENDMENT: STELLA COURIER, LLC. FOR HUMAN-

PROPELLED COURIER AND MAIL SERVICES
WHEREAS, one of the City Council Strategic Plan Goals is to be a global leader in addressing climate change, advancing environmental justice, and protecting the environment; and
WHEREAS, use of a human-propelled courier service to provide these services supports that goal by having less of a carbon impact than using a gas-powered vehicle; and WHEREAS, City departments require ongoing and uninterrupted mail services at central and satellite locations, and for commission packet delivery; and WHEREAS, the mail room requires fully-trained, on-call, as-needed coverage in the case of vacation/sick/jury, or other leave by staff; and
WHEREAS, Stella Courier, LLC., responded to City of Berkeley RFP 23-11568-C with fair and reasonable pricing; and
WHEREAS, Stella Courier is fully-capable of providing the required scope of services, and is knowledgeable in mail room and postage machine operations.

NOW THEREFORE, BE IT RESOLVED by the Council of the City of Berkeley that the City Manager is authorized to execute a two-year contract amendment with Stella Courier for the provision of human-propelled courier, mail room coverage, and related mail services, increasing the amount by $180,000 for an amended contract total that is not-to- exceed $360,000.

Office of the City Manager
2180 Milvia Street, Berkeley, CA 94704 ● Tel: (510) 981-7000 ● TDD: (510) 981-6903 ● Fax: (510) 981-7099 E-Mail: [email protected] Website: https://berkeleyca.gov/

CONSENT CALENDAR
July 29, 2025
To: Honorable Mayor and Members of the City Council
From: Paul Buddenhagen, City Manager
Submitted by: Henry Oyekanmi, Director, Finance
Subject: Formal Bid Solicitations and Request for Proposals Scheduled for Possible Issuance After Council Approval on July 29, 2025

RECOMMENDATION
Approve the request for proposals or invitation for bids (attached to staff report) that will be, or are planned to be, issued upon final approval by the requesting department or division.  All contracts over the City Manager’s threshold will be returned to Council for final approval.

FISCAL IMPACTS OF RECOMMENDATION
Total estimated cost of items included in this report is $4,673,159 PROJECT Fund Source Amount
Ohlone Greenway Modernization and
Safety Project
307
134
Capital Grants – Local
Measure BB – Local
Streets and Roads
$4,020,159
$353,000
Transfer Station Scales Maintenance &
Repairs 601 Zero Waste $300,000
Total: $4,673,159

CURRENT SITUATION AND ITS EFFECTS
On May 6, 2008, Council adopted Ordinance No. 7,035-N.S. effective June 6, 2008, which increased the City Manager’s purchasing authority for services to $50,000. As a result, this required report submitted by the City Manager to Council is now for those purchases in excess of $100,000 for goods; and $200,000 for playgrounds and construction; and $50,000 for services. If Council does not object to these items being sent out for bid or proposal within one week of them appearing on the agenda, and upon final notice to proceed from the requesting department, the IFB (Invitation for Bid) or RFP (Request for Proposal) may be released to the public and notices sent to the potential bidder/respondent list.

Formal Bid Solicitations and Request for Proposals CONSENT CALENDAR Scheduled for Possible Issuance After Council July 29, 2025 Approval on July 29, 2025

BACKGROUND
On May 6, 2008, Council adopted Ordinance No. 7,035-N.S., amending the City Manager’s purchasing authority for services

ENVIRONMENTAL SUSTAINABILITY AND CLIMATE IMPACTS
The Finance Department reviews all formal bid and proposal solicitations to ensure that they include provisions for compliance with the City’s environmental policies.  For each contract that is subject to City Council authorization, staff will address environmental sustainability considerations in the associated staff report to City Council.

RATIONALE FOR RECOMMENDATION
Need for the goods and/or services.

ALTERNATIVE ACTIONS CONSIDERED
None.

CONTACT PERSON
Roopreet Walia-Soorma, Senior Buyer, Finance, 510-981-7311 Attachments:
1: Formal Bid Solicitations and Request for Proposals Scheduled for Possible Issuance After Council Approval on July 29, 2025
a. Ohlone Greenway Modernization and Safety Project
b. Transfer Station Scales Maintenance & Repairs
Note: Original of this attachment with live signature of authorizing personnel is on file in General Services.

NEXT 30 DAYS
DATE SUBMITTED: June 17, 2025
Attachment 1

SPECIFICATION
NO.

DESCRIPTION OF

GOODS /

SERVICES BEING

PURCHASED
APPROX. RELEASE
DATE
APPROX. BID

OPENING DATE

INTENDED USE ESTIMATED COST BUDGET CODE TO BE

CHARGED
DEPT. / DIVISION CONTACT NAME &
PHONE
26-11748-C Ohlone Greenway
Modernization and
Safety Project
7/30/25 8/29/2025 Construction to enhance Ohlone
Greenway including: pathway
widening; Updated lightening
along the greenway; Intersection
safety enhancements (RRFBs,
raised crossings, median islands,
curb extension, lightening);
updated signing & striping
$4,373,159 (includes
10% contingency)
$4,020,159
$353,000
307-54-622-668-0000-000-
431-665110
(PWTRBP2204)
134-54-622-668-0000-000-
431-665110
(PWTRBP2204)
Public Works / Transportation Jesse Peoples
510-981-6449
26-11749-C Transfer Station
Scales Maintenance
& Repairs
7/30/25 8/29/2025 Maintenance and repairs of
inbound and outbound Transfer
Station scales
$300,000
Three year contract
with a two optional
1-year extension
601-54-627-734-3023-000-
474-624110-
Public Works /  Zero Waste Keith Morin                      510- 981-6354
Dept Total
TOTAL $4,673,159
1 of  2

Internal
Office of the City Manager
2180 Milvia Street, Berkeley, CA 94704 ● Tel: (510) 981-7000 ● TDD: (510) 981-6903 ● Fax: (510) 981-7099 E-Mail: [email protected] Website: http://www.cityofberkeley.info/manager

CONSENT CALENDAR
July 29, 2025
To: Honorable Mayor and Members of the City Council
From: Paul Buddenhagen, City Manager
Submitted by: Henry Oyekanmi, Director, Finance Department Subject: Contract: InfoSend for Bill Printing and Mailing Services

RECOMMENDATION
Adopt a Resolution authorizing the City Manager to execute a piggyback contract and any amendments with InfoSend in an amount not to exceed $450,000 for bill printing and mailing services from July 30, 2025 through July 30, 2028.

FISCAL IMPACTS OF RECOMMENDATION
The cost will be $150,000 per year over 3 years for a total contract amount NTE $450,000 and will be funded by the General Fund and the Zero Waste Fund. The year one funds are available in the FY2026 budget.

CURRENT SITUATION AND ITS EFFECTS
The Revenue Collection Division is responsible for maintaining customer accounts as well as printing and mailing thousands of bills on a regular basis to a wide range of City customers. Currently, many of these bills—including those for Zero Waste, Environmental Health, the Marina, and the Rental Housing Safety Program—are processed by an outside vendor. In addition, tens of thousands of business license tax forms are mailed to customers annually.

The Finance Department researched vendors that could perform the scope after receiving no adequate response from a formal solicitation. It was determined that InfoSend had numerous contracts with many municipalities that was competitively bid with competitive pricing.

BACKGROUND
The City of Brawley conducted a competitive Request for Proposal (RFP) process that solicited bids for a vendor to provide “Utility Bill Printing & Mailing Services”, which opened on November 1, 2022, and closed on December 2, 2022. InfoSend was selected as the most responsive vendor and was awarded a base contract period that runs from February 7, 2023, through June 30, 2026 with automatic renewals for successive two (2) year

Internal
Contract: InfoSend for Bill Printing and Mailing Service CONSENT CALENDAR July 29, 2025

periods unless either Client or InfoSend provides the other party with at least sixty (60) days’ written notice prior to the end of the current term.

RATIONALE FOR RECOMMENDATION
The Finance Department researched vendors that could perform the scope after receiving no adequate response from a formal solicitation. It was determined that InfoSend had numerous contracts with many municipalities that was competitively bid with competitive pricing.

ENVIRONMENTAL SUSTAINABILITY AND CLIMATE IMPACTS
This program will provide flexibility to the Finance Department to have multiple vendors to print and mail bills to customers. Unlike other print vendors, this one is located in California and has the same operating hours and printing facilities within the Pacific Service Time zone.

As this vendor will mail bills from within California, there will be an increase in environmental sustainability and will help mitigate the effects of climate change.

CONTACT PERSON
Henry Oyekanmi, Director of Finance, Finance Department, 981-7301 Attachments:

1. Resolution

Internal
RESOLUTION NO. ##,###-N.S.

CONTRACT: INFOSEND BILLING PRINTING AND MAILING SERVICES WHEREAS, the Revenue Collection Division in the Finance Department is responsible for maintaining customer accounts as well as printing and mailing thousands of bills on a regular basis to a wide range of City customers; and
WHEREAS, the Finance Department researched vendors that could perform the scope after receiving no adequate response from a formal solicitation and it was determined that InfoSend had numerous contracts with many municipalities that was competitively bid with competitive pricing; and
WHEREAS, unlike many printing companies, InfoSend is located in California. By decreasing the distance the mail will have to travel, it will decrease its effect on climate change; and
WHEREAS, the City of Brawley, in Southern California, conducted a competitive Request for Proposal (RFP) process that solicited bids for a vendor to provide “Utility Billing and Printing Services”, which opened on November 1, 2022 and closed on December 2, 2022.

InfoSend was selected as the most responsive vendor and was awarded a base contract period that runs from February 7, 2023, through June 30, 2026 with automatic renewals for successive two (2) year periods unless either Client or InfoSend provides the other party with at least sixty (60) days’ written notice prior to the end of the current term; and WHEREAS, the Finance Department is requesting to piggyback off the City of Brawley Contract for the same services using funds from the General Fund and the Zero Waste Fund.

NOW THEREFORE, BE IT RESOLVED by the Council of the City of Berkeley that the City Manager or designee is authorized to execute a piggyback contract and any amendments with InfoSend for $150,000 per year, in an amount not to exceed $450,000 for bill printing and mailing services from July 30, 2025 through July 30, 2028

Internal
Office of the City Manager
2180 Milvia Street, Berkeley, CA 94704 ● Tel: (510) 981-7000 ● TDD: (510) 981-6903 ● Fax: (510) 981-7099 E-Mail: [email protected] Website: http://www.CityofBerkeley.info/Manager

CONSENT CALENDAR
July 29, 2025
To: Honorable Mayor and Members of the City Council
From: Paul Buddenhagen, City Manager
Submitted by: David Sprague, Fire Chief of Fire and Emergency Services Subject: Designate the Line of Succession for the Director of Emergency Services

RECOMMENDATION
Adopt a Resolution approving the designated line of succession to the position of Director of Emergency Services in the event of an emergency, and rescinding Resolution No. 70,729-N.S.

FISCAL IMPACTS OF RECOMMENDATION
None.

CURRENT SITUATION AND ITS EFFECTS
The Berkeley Municipal Code (BMC) requires that the City Manager, who is the Director of Emergency Services, designate the order of succession to that office in the event the Director is unavailable to attend meetings and otherwise perform their duties during an emergency. Additionally, the City Council must approve the order of succession. (BMC Section 2.88.040)

BACKGROUND
On March 21, 2023 the City Council adopted Resolution No. 70,729-N.S. designating the line of succession to the position of Director of Emergency Services in the event the Director is unavailable to perform their duties during an emergency. Since that time, changes in personnel necessitate that a new designation be approved as set forth in the attached Resolution.

ENVIRONMENTAL SUSTAINABILITY AND CLIMATE IMPACTS
There are no identifiable environmental opportunities or effects associated with the subject of this report.

CONTACT PERSON
David Sprague, Fire Chief, (510) 981-3473
Attachments:
1: Resolution

Internal
RESOLUTION NO. ##,###-N.S.

APPROVING THE DESIGNATED LINE OF SUCCESSION TO THE DIRECTOR OF EMERGENCY SERVICES POSITION AND RESCINDING RESOLUTION NO. 70,729- N.S.

WHEREAS, Berkeley Municipal Code Section 2.88.030 designates the City Manager as the Director of Emergency Services; and
WHEREAS, Paul Buddenhagen, as City Manager, serves as the Director of Emergency Services; and
WHEREAS, pursuant to Berkeley Municipal Code Section 2.88.040, it is necessary to establish a line of succession for the Director of Emergency Services in the event that the Director is unavailable to attend meetings or otherwise perform their duties during an emergency.

NOW THEREFORE, BE IT RESOLVED by the Council of the City of Berkeley that the following order of succession to the position of Director of Emergency Services in the event the Director is unavailable to attend meetings or otherwise perform their duties during an emergency is hereby confirmed and approved:

1. David White, Deputy City Manager

2. David Sprague, Fire Chief

3. Jennifer Louis, Chief of Police
BE IT FURTHER RESOLVED that Resolution No. 70,729-N.S. is hereby rescinded.

Internal
Office of the City Manager
2180 Milvia Street, Berkeley, CA 94704 ● Tel: (510) 981-7000 ● TDD: (510) 981-6903 ● Fax: (510) 981-7099 E-Mail: [email protected] Website: https://berkeleyca.gov/

CONSENT CALENDAR
July 29, 2025
To: Honorable Mayor and Members of the City Council
From: Paul Buddenhagen, City Manager
Submitted by: David Sprague, Fire Chief, Fire Department Subject: Contract with Wildfire Defense to Serve as the Alameda County Coordinator

RECOMMENDATION
Adopt a Resolution:

1. Authorizing the City Manager or designee to execute a contract with Wildfire Defense to serve as the Alameda County Coordinator for coordination with local agencies, fire safe councils, and wildfire mitigation community groups for the initial period August 1, 2025, through June 30, 2026, in an amount not to exceed $155,500, and to apply for and receive future grant funding in collaboration with Berkeley Fire Department staff to maintain the position through 2028; and

2. Authorizing the City Manager or designee to execute any amendments for not more than $225,000 per year in Fiscal Year (FY) 25, FY26, and FY27, upon receiving additional California Fire Safe Council (CFSC) grants to continue contracting Wildfire Defense to serve Alameda County communities, provide resources and education on wildfire safety, promote collaboration, assist local groups with funding opportunities, and aid multi-jurisdictional planning.

FISCAL IMPACTS OF RECOMMENDATION
Funding for this contract is provided by the California Fire Safe Council (CFSC) County Coordinator Grant Program for FY 2025–2026 [Fund Number: 336-72-741-831-0000- 000-422-612990-]. As there are no matching funds required, there is no impact to the City’s General Fund. Staff will seek additional grant funding to sustain the position beyond July 2026.

CURRENT SITUATION AND ITS EFFECTS
Alameda County faces persistent and significant wildfire risk, particularly in the wildland- urban interface areas such as the Berkeley, Oakland Hills, and Hayward. Recent years have seen increased wildfire activity across California, highlighting the urgent need for coordinated, countywide mitigation and preparedness efforts. While the region is home to a number of active wildfire mitigation groups and agencies, these efforts have historically been fragmented, with limited formal collaboration or shared strategic planning.

Internal
Contract with Wildfire Defense to Serve as the Alameda County Coordinator CONSENT CALENDAR July 29, 2025

The California Fire Safe Council funds county coordinator positions, and Alameda County is one of six counties that did not have a Coordinator position prior to FY25. The position is housed within Fire Department and actively coordinates and collaborates with county-wide community groups, fire councils, HOAs, and other mitigation support groups. The City of Berkeley issued a Request for Proposals (RFP) to contract with an individual that will serve as the Alameda County Coordinator. The chosen vendor will work in partnership with all Alameda County jurisdictions to complete the required deliverables as set forth by the grantor and develop a work plan to further coordinate wildfire mitigation activities with a budget not to exceed $155,500 for the current period of performance ending in July 2026. The City Council approved the formal bids and solicitation request for Specification No. 25-11738-C at the June 3, 2025, City Council meeting. The RFP was then posted on the City's Bids and Solicitation site on June 17, 2025. Responses to questions were made available on the City’s website on June 23, 2025. The deadline for proposal submissions was July 8, 2025, resulting in 2 complete proposals being received. The selection committee included leaders and staff from the Berkeley Fire Department, Alameda County Fire Department, Fremont Fire Department, and Hayward Fire Department. The committee reviewed the proposals and interviewed bidders on July 10, 2025, making their final selection on July 11.

This initiative directly supports the City’s strategic goals to:
 Create a resilient, safe, connected, and prepared city.  Provide efficient and effective government services.
 Champion and demonstrate social and racial equity by protecting the most vulnerable communities from wildfire risk.
 Advance environmental justice and protect the environment through proactive hazard mitigation planning.

BACKGROUND
The County Coordinator program, funded by the California Fire Safe Council (CFSC), is designed to address the need for countywide collaboration and strategic alignment. The Coordinator will serve as a central point of contact, connecting wildfire mitigation groups, supporting grant applications, and facilitating the use of advanced planning tools such as the pathways analysis. The Coordinator will also be responsible for fulfilling specific grant deliverables and building regional capacity while developing a sustainable framework for ongoing collaboration.

During the previous County Coordinator grant period, the City of Berkeley was unable to hire a full-time County Coordinator due to delays in funding availability, resulting in only interim, volunteer-based coordination. This gap limited the county’s ability to build sustained relationships, leverage data-driven planning tools, and increase the flow of mitigation funding to high-risk communities. There remains a clear need for a

Internal
Contract with Wildfire Defense to Serve as the Alameda County Coordinator CONSENT CALENDAR July 29, 2025

professional, dedicated County Coordinator to unify wildfire mitigation groups, facilitate project implementation, and ensure compliance with state and federal grant requirements.

ENVIRONMENTAL SUSTAINABILITY AND CLIMATE IMPACTS
Ensuring the Department is maximizing available resources and working with other county coordinators to collaborate on regional mitigation activities will help sustain the local environment and mitigate the potential of fire, mudslides, and other catastrophic impacts associated with the overgrowth of vegetation and loss of habitat post-wildfire.

RATIONALE FOR RECOMMENDATION
Wildfire Defense is uniquely qualified to coordinate countywide wildfire mitigation efforts, having demonstrated expertise in wildfire planning, grant administration, and stakeholder engagement. This contract ensures continuity of critical wildfire resilience work and positions the City and County to secure future funding.

ALTERNATIVE ACTIONS CONSIDERED
None.

CONTACT PERSON
Shanalee Gallagher, Principal Program Manager, Fire Department (510) 981-3473 Attachments:
1: Resolution

Internal
RESOLUTION NO. ##,###-N.S.

CONTRACT: WILDFIRE DEFENSE TO SERVE AS THE ALAMEDA COUNTY

COORDINATOR
WHEREAS, the City of Berkeley and Alameda County have prioritized wildfire mitigation and resilience; and
WHEREAS, Alameda County Board of Supervisors provided City of Berkeley support to apply for and manage a county-wide position; and
WHEREAS, the California Fire Safe Council (CFSC) County Coordinator Grant Program provides funding to support countywide wildfire mitigation coordination; and WHEREAS, Wildfire Defense has been selected and is qualified to serve as County Coordinator, facilitating partnerships, ensuring deliverables, and securing future grant funding.

NOW THEREFORE, BE IT RESOLVED by the Council of the City of Berkeley that the City Manager or designee is authorized to execute a contract with Wildfire Defense to serve as the Alameda County Coordinator for coordination with local agencies, fire safe councils, and wildfire mitigation community groups for the initial period August 1, 2025, through June 30, 2026, in an amount not to exceed $155,500, [Fund Number: 336-72- 741-831-0000-000-422-612990-]. and to apply for and receive future grant funding in collaboration with Berkeley Fire Department staff to maintain the position through 2028.

BE IT FURTHER RESOLVED that the City Manager or designee is authorized to execute any amendments for not more than $225,000 per year in Fiscal Year (FY) 25, FY26, and FY27, upon receiving additional California Fire Safe Council (CFSC) grants to contract Wildfire Defense to serve Alameda County communities, provide resources and education on wildfire safety, promote collaboration, assist local groups with funding opportunities, and aid multi-jurisdictional planning.

Office of the City Manager
2180 Milvia Street, Berkeley, CA 94704 ● Tel: (510) 981-7000 ● TDD: (510) 981-6903 ● Fax: (510) 981-7099 E-Mail: [email protected] Website: https://berkeleyca.gov/

CONSENT CALENDAR
July 29, 2025
To: Honorable Mayor and Members of the City Council
From: Paul Buddenhagen, City Manager
Submitted by: Scott Gilman, Director, Health, Housing, and Community Services Subject: Submitting Application for Permanent Local Housing Allocation Program

RECOMMENDATION
Adopt a Resolution authorizing the City Manager or designee to apply for and accept funds from the State of California's Permanent Local Housing Allocation Program, in an amount not to exceed $849,945.

FISCAL IMPACTS OF RECOMMENDATION
The City of Berkeley is currently eligible to apply for one year of funds through the State’s Permanent Local Housing Allocation (PLHA) program, not to exceed $849,945, Fund #302. The funding would be used for Housing and Community Services (HCS) programs in support of lower income and/or unhoused residents.

CURRENT SITUATION AND ITS EFFECTS
The City will apply for up to $849,995 in PLHA funds through California Department of Housing and Community Development’s (HCD) Notice of Funding Availability released in October 2024. The funding ($849,995) represents Year 5 of the City’s five-year PLHA plan amendment submitted in 2024 and the agreement signed in early 2025. This application includes a Year 5 spending plan for a continued application of funds to support existing HCS programs, including the Housing Trust Fund (HTF) program and homeless services.

PLHA funds can be used to support a variety of planning or implementation activities related to housing and community development carried out by HCS staff within the Department of Health, Housing, and Community Services. HCS staff anticipate using the funds for the following eligible activity categories: 1) The predevelopment, development, acquisition, rehabilitation, and preservation of multifamily, residential live- work, or rental housing that is affordable to extremely low-, very low-, low-, and moderate-income households, including necessary operating subsidies; and/ or 2) Assisting persons who are experiencing or at risk of homelessness, including providing rapid rehousing, rental assistance, navigation centers, emergency shelters, and the new construction, rehabilitation, and preservation of permanent and transitional housing, along with grant administration (within the established limit of funds).

Submitting Application for Permanent Local Housing Allocation Program CONSENT CALENDAR July 29, 2025

BACKGROUND
PLHA is intended to provide a permanent, ongoing source of funding to local governments for eligible housing-related activities and programs that assist in increasing the supply of affordable homes in California and addressing the unmet housing needs of their local communities. Funds are generated from a $75 recording fee on certain real estate transaction documents, so the amount allocated through the program varies year to year. PLHA is noncompetitive, with funds allocated to cities based on the Community Development Block Grant (CDBG) distribution formula.

HCD allocated a total of $7,475,827 to the City during the five-year period. To access the funds, the City is required to have a five-year PLHA Plan, amend it when needed, and submit streamlined applications for each year of funding. The City used funds from Years 1 and 2 to support the operating of the navigation center (STAIR) and for Golden Bear Homes – a Homekey project. For Years 3 and 4, the City allocated a total of $965K to operating subsidies for homeless households such as shelter operations and navigation services and allocated an estimated $2.2M to the HTF program and will be used to support rehabilitation of occupied projects in the HTF portfolio. Up to 5% of each year’s PLHA allocation is available to the City for admin to support program implementation.

For Year 5, consistent with the amended and signed PLHA plan, the City will allocate 45% of the funds (approximately $382K) to operating subsidies for homeless households and 50% (approximately $425K) to the HTF program. The remaining 5% (approximately $42K) will be used to reimburse staffing costs.

The City is required to use HCD’s resolution template for the application and the plan amendment for this Council item.

ENVIRONMENTAL SUSTAINABILITY AND CLIMATE IMPACTS
There are no environmental sustainability and climate impacts directly associated with the recommendations in this report.

RATIONALE FOR RECOMMENDATION
If approved, an application for PLHA funds will make up to $849,995 available for Berkeley to support City programs that serve lower income or unhoused populations

ALTERNATIVE ACTIONS CONSIDERED
The City could decline to participate in the PLHA Program. Since that would not be consistent with the City’s Strategic Plan to increase affordable housing opportunities, staff are recommending participation as described above.

CONTACT PERSON
Asavari Devadiga, Community Development Project Coordinator, HHCS, (510) 981-5426

Submitting Application for Permanent Local Housing Allocation Program CONSENT CALENDAR July 29, 2025

Attachments:
1: Resolution

RESOLUTION NO. ##,###-N.S.

A RESOLUTION OF THE CITY COUNCIL OF THE CITY OF BERKELEY

AUTHORIZING APPLICATION FOR AND ADOPTING THE PERMANENT LOCAL

HOUSING ALLOCATION PLAN FOR THE PERMANENT LOCAL HOUSING

ALLOCATION PROGRAM
WHEREAS, the California Department of Housing and Development (“Department”) is authorized to provide up to $296 million under the SB2 Permanent Local Housing Allocation Program Formula Component from the Building Homes and Jobs Trust Fund for assistance to Cities and Counties (as described in Health and Safety Code section 50470 et seq. (Chapter 364, Statutes of 2017 (SB 2)); and WHEREAS, the State of California (the “State”) Department issued a Notice of Funding Availability (“NOFA”) dated 10/15/2024 under the Permanent Local Housing Allocation (PLHA) Program; and
WHEREAS, the City of Berkeley (the “Applicant”), is an eligible Local government who has applied for program funds to administer one or more eligible activities, or a Local or Regional Housing Trust Fund to whom an eligible Local government delegated its PLHA formula allocation; and
WHEREAS, the Department may approve funding allocations for PLHA program, subject to the terms and conditions of the Guidelines, NOFA, Program requirements, the Standard Agreement, and other contracts between the Department and PLHA grant recipients.

NOW THEREFORE, BE IT RESOLVED by the Council of the City of Berkeley THAT:

SECTION 1. If Applicant receives a grant of PLHA funds from the Department pursuant to the above referenced PLHA NOFA, it represents and certifies that it will use all such funds in a manner consistent and in compliance with all applicable state and federal statutes, rules, regulations, and laws, including without limitation all rules and laws regarding the PLHA Program, as well as any and all contracts Applicant may have with the Department;
SECTION 2. Applicant is hereby authorized and directed to receive a PLHA grant, in an amount not to exceed the five-year estimate of the PLHA formula allocations, as stated in Appendix B of the current NOFA $7,761,504 in accordance with all applicable rules and laws; and
SECTION 3. Applicant hereby agrees to use the PLHA funds for eligible activities as approved by the Department and in accordance with all Program requirements, Guidelines, other rules, and laws, as well as in a manner consistent and in compliance with the Standard Agreement and other contracts between the Applicant and the Department; and

SECTION 4. Pursuant to Section 302(c)(4) of the Guidelines, Applicant’s PLHA Plan for the 2019-2023 Allocations is attached to this resolution, and Applicant hereby adopts this PLHA Plan and certifies compliance with all public notice, public comment, and public hearing requirements in accordance with the Guidelines; and SECTION 5. If applicable, Applicant certifies that it was delegated by the City Council to submit an application on its behalf and administer the PLHA grant award for the formula allocation of PLHA funds, pursuant to Guidelines Section 300(c) and 300(d), and the legally binding agreement between the recipient of the PLHA funds and the Applicant is submitted with the PLHA application; and
SECTION 6. If applicable, Applicant certifies that it has or will subgrant some or all of its PLHA funds to another entity or entities. Pursuant to Guidelines Section 302(c)(3), “entity” means a housing developer or program operator, but does not mean an administering Local government to whom a Local government may delegate its PLHA allocation; and SECTION 7. If applicable, Applicant certifies that its selection process of these subgrantees was or will be accessible to the public and avoided or shall avoid any conflicts of interest; and
SECTION 8. If applicable, pursuant to Applicant’s certification in this resolution, the PLHA funds will be expended only for eligible Activities and consistent with all program requirements; and
SECTION 9. If applicable, Applicant certifies that, if funds are used for the acquisition, construction or rehabilitation of for-sale housing projects or units within for-sale housing projects, the grantee shall record a deed restriction against the property that will ensure compliance with one of the requirements stated in Guidelines Section 302(c)(6)(A), (B) and (C); and
SECTION 10. If applicable, Applicant certifies that, if funds are used for the development of an Affordable Rental Housing Development, the Local government shall make PLHA assistance in the form of a low-interest, deferred loan to the Sponsor of the Project, and such loan shall be evidenced through a Promissory Note secured by a Deed of Trust and a Regulatory Agreement shall restrict occupancy and rents in accordance with a Local government-approved underwriting of the Project for a term of at least 55 years; and SECTION 11. Applicant shall be subject to the terms and conditions as specified in the Standard Agreement, the PLHA Program Guidelines and any other applicable SB 2 Guidelines published by the Department; and
SECTION 12. The City Manager or the City Manager’s designee is authorized to execute the PLHA Program Application, the PLHA Standard Agreement and any subsequent amendments or modifications thereto, as well as any other documents which are related

to the Program or the PLHA grant awarded to Applicant, as the Department may deem appropriate.

Office of the City Manager
2180 Milvia Street, Berkeley, CA 94704 ● Tel: (510) 981-7000 ● TDD: (510) 981-6903 ● Fax: (510) 981-7099 E-Mail: [email protected] Website: https://berkeleyca.gov/

CONSENT CALENDAR
July 29, 2025
To: Honorable Mayor and Members of the City Council
From: Paul Buddenhagen, City Manager
Submitted by: Scott Gilman, Director, Health, Housing & Community Services Department
Subject: Mental Health Services Act Fiscal Year 2026 Annual Update

RECOMMENDATION
Adopt a Resolution approving the Mental Health Services Act (MHSA) Fiscal Year 2026 Annual Update, which identifies uses of funds for mental health programming, and forwarding the Annual Update to appropriate State officials.

SUMMARY
California MHSA revenues are allocated to mental health jurisdictions across the state on an annual basis to transform the mental health system into one that is consumer and family driven, culturally competent, wellness and recovery oriented, collaborative with community partners, and inclusive of integrated services. MHSA includes five defined funding components: Community Services and Supports; Prevention and Early Intervention; Innovations, Workforce, Education & Training; and Capital Facilities Technological Needs.

The City utilizes MHSA funds to address the various needs of the residents of Berkeley.

Some of the highlights of MHSA programming have included: A reduction in psychiatric inpatient hospital and/or incarceration days for severely mentally ill clients; a decrease in the number of days severely mentally ill clients experience homelessness; step down to a lower level of care for some clients; services and supports for family members; Wellness Center services; consumer driven wellness recovery activities; housing, and benefits advocacy services and supports for clients; augmented prevention and intervention services for Transition Age Youth, Adults, and Older Adults and individuals in unserved, underserved and inappropriately served cultural and ethnic populations; and free access for a limited time to the MyStrength and HeadSpace Mental Health Apps for anyone who lives, works, or goes to school in Berkeley.

Additionally, an outcome of the implementation of the MHSA is that mental health consumers, family members and other stakeholders now regularly serve on several of the Mental Health Division’s internal decision-making committees. These individuals share their “lived experience” and provide valuable input which has become an integral

Mental Health Services Act (MHSA) CONSENT CALENDAR
Fiscal Year 2026 Annual Update July 29, 2025

component that informs the Mental Health Division on the implementation of MHSA services and supports. In order to utilize MHSA funds, stakeholder informed MHSA Three Year Program and Expenditure Plans and Annual Updates are required to be developed and locally approved.

This is the last Annual Update under the current MHSA regulations, prior to Fiscal Year 2027 when the Proposition 1, Behavioral Health Services Act (BHSA), guidelines and regulations will become applicable for Three Year Plans and Annual Updates.

FISCAL IMPACTS OF RECOMMENDATION
Approval of the MHSA Fiscal Year 2026 (FY2026) Annual Update enables funding for MHSA programs and services. The City of Berkeley receives funding from MHSA revenues (Fund 315) on a monthly basis from the State of California. The total MHSA funding amount the city will receive in any given year is unknown until the end of the year. Therefore, MHSA Three Year Plans and Annual Updates must approximate revenues and expenditures for each year. Funding in the amount of $11,265,993 will be available in the FY2026 adopted budget in the MHSA Fund (Fund 315). Funding in the amount of $430,002 will be recommended for appropriation through the first amendment to the FY2026 appropriations ordinance in the MHSA Fund (Fund 315) resulting in a total funding of $11,695,995 in FY2026. This Annual Update includes the following estimated revenue and expenditures in each MHSA component:
2026

MHSA FUNDING

COMPONENT
Estimated Unspent
Funds
Estimated New
Funding
Estimated
Expenditures
Community Services &
Supports
$14,683,671 $4,371,317 $8,275,495
($1,644,426
transfer to WET
and CFTN)
Prevention & Early
Intervention
$3,072,640 $1,092,829 $1,903,291
Innovations $2,336,621 $287,587 $600,000
Workforce Education &
Training
$253,073 $344,426
(Transfer from CSS)
$167,209
Capital Facilities &
Technological Needs
$0 $1,300,000
(Transfer from CSS)
$1,000,000
TOTALS $20,346,005 $7,396,159 $11,695,995
The budget provides estimated revenues and expenditures for this Annual Update. The Division obtains financial projections from the state on the amount of MHSA revenue to be allocated in a given year. Financial projections for this FY26 Annual Update reflect a

Mental Health Services Act (MHSA) CONSENT CALENDAR
Fiscal Year 2026 Annual Update July 29, 2025

decrease in MHSA funds, to what was previously estimated in the approved FY2024- 2026 Three-Year Plan.

In this FY2026 Annual Update, due to changes in the projected revenue/budget in the 5- year forecast, the Division proactively paused the hiring for some previously approved staff positions out of caution, so that funds would not be expended as quickly.

Departmental Fiscal staff were able to run revenue analyses earlier than in previous years, resulting in the ability to shift some personnel costs to other mental health funding sources. These shifts will enable the Division to use all of its appropriate revenue sources more evenly and prevent any funds from running out too soon.

Beginning in FY2027, MHSA will shift to the new BHSA fiscal and program requirements. MHSA unspent fund balance amounts at the end of FY2026, will be critical in future years in supporting the City’s transition from MHSA to BHSA.

CURRENT SITUATION AND ITS EFFECTS
The MHSA FY2026 Annual Update provides an update to the City Council approved MHSA FY2024-2026 Three Year Program and Expenditure Plan. Informed by area stakeholders, this Annual Update details current mental health programs and services, proposes a few program changes, and includes the state required MHSA FY2022-2024 Prevention and Early Intervention Three Year Evaluation Report and the MHSA FY2024 Innovation Annual Evaluation Report. Per state legislation, MHSA Three Year Plans and Annual Updates must include the following steps: Conducting a community program planning process with the involvement of are stakeholders; writing a draft plan; initiating a 30-day Public Review on the Draft Plan; and conducting a Public Hearing at a Mental Health Commission meeting.

This City of Berkeley MHSA FY2026 Annual Update included a community program planning process to obtain input via multiple meetings; drafting a plan; incorporating feedback from the planning process; a 30-day Public Review from May 27 through June 26; and a Public Hearing on the evening of June 26 before the Mental Health Commission.

The Division received public comments on the MHSA FY2026 Annual Update during the community program planning process which included engaging the public prior to the Draft Annual Update was written, the 30-day Public Review, and the Public Hearing. All public comments were recorded regardless of topic. Some of the public comments received were regarding programs and services that are not currently funded through MHSA and/or are executed through other City programs or through community-based organizations. Input received included questions around MHSA funded and area services, local housing, and the upcoming changes with BHSA; comments regarding safety issues around placing individuals who have been homeless, at Senior Citizen housing sites; ensuring individuals who have experienced homelessness are placed at a housing site that includes services to support them with acclimating to being housed;

Mental Health Services Act (MHSA) CONSENT CALENDAR
Fiscal Year 2026 Annual Update July 29, 2025

and to implement a program that provides individuals with the necessary services and supports to assist them in breaking the cycle of experiencing recurrent 5150 (hospitalization) events. An additional concern was around whether the Division has the appropriate level of staff resources for outreach, specifically to engage marginalized individuals and communities. During the Public Hearing input was provided around a couple of errors in the “FY2026 Projected Numbers To be Served and Estimated Cost Per Person” chart within the Annual Update. Written input was also submitted around the need for restored prevention funding from the State. The written input was read at the Public Hearing and is included in Appendix E of the Annual Update.

After the close of the Public Hearing the Mental Health Commission passed the following motion: M/S/C (Krishnan, Sol) Motion to approve the annual update with the stipulations of the figures being re-calculated on page 129.

Ayes: Gu, Krishnan, Opton, Sol, Teague, Turner; Noes: None; Abstentions: None;

Absent: Tregub, Prichett, Jones
The Mental Health Commission motion refers to figures in the “FY2026 Projected Numbers To be Served and Estimated Cost Per Person” chart, which was originally on page 129 in the Draft FY2026 Annual Update.

There were three substantive comments or necessary edits that were found that warranted changes to the FY2026 Annual Update as follows:
 Provide additional funding for Insight Housing to help defray increased costs at the Russell Street Residence.
 Correct two errors that were found on page 129, in the calculations of the “FY2026 Projected Numbers to Be Served and Estimated Cost Per Person Chart”.
 Change the amount to be allocated for the African American Holistic Resource Center in FY2026, to $300,000.
 Update the Budget pages, a portion of the expenditures on the Workforce, Education and Training Budget page was not carried forward to the Budget Summary page.

The Annual Update and Budget pages in this final version of the Annual Update have been edited to reflect these additions and changes. Additionally, some of the formatting within the Annual Update has been further modified from the original version, for Accessibility purposes.

Mental Health Services Act (MHSA) CONSENT CALENDAR
Fiscal Year 2026 Annual Update July 29, 2025

BACKGROUND
California voters adopted the Mental Health Services Act (Proposition 63 – MHSA) on November 2, 2004. The Act places a 1% tax on every dollar of personal income over $1 million. MHSA revenues are allocated to mental health jurisdictions across the state to transform the mental health system into one that is consumer and family driven, culturally competent, wellness and recovery oriented, collaborative with community partners, and inclusive of integrated services. MHSA includes the following five funding components:
 Community Services and Supports: Primarily for treatment services and supports for Severely Mentally Ill Adults and Seriously Emotionally Disturbed Children.
 Prevention & Early Intervention: For strategies to prevent mental illnesses from becoming severe and disabling.
 Innovation: For short-term pilot projects designed to increase new learning in the mental health field.
 Workforce, Education & Training: Primarily for strategies to identify and remedy mental health occupational shortages, promote cultural competency, and promote the employment of mental health consumers and family members.  Capital Facilities and Technological Needs: For capital projects on owned buildings and on mental health technology projects.

MHSA has also provided funding for local housing development; collaborative programs for suicide prevention, school mental health, and to combat stigma and discrimination; and training and technical assistance in the areas of cultural competency.

As required by the State, this MHSA FY2026 Annual Update provides an update to the City Council approved MHSA FY2024-2026 Three Year Program and Expenditure Plan.

Since the inception of MHSA, funds have been utilized to transform the mental health service delivery system to better meet the needs of underserved and inappropriately served communities, among others. This initiative has also provided the opportunity for the City of Berkeley Mental Health Division to further develop and expand the system of care by adding new programs within the Division and utilizing non-profit providers in the planning and delivery of comprehensive mental health services.

Past Council Item
Since the inception of the MHSA Program in 2006, Council has taken actions to approve all MHSA Plans and Annual Updates. The most recent actions taken over the past five years on MHSA Three Year Plans and Annual Updates are as follows:

Mental Health Services Act (MHSA) CONSENT CALENDAR
Fiscal Year 2026 Annual Update July 29, 2025

 December 1, 2020, approval of the MHSA FY2021 – 2023 Three Year Program and Expenditure Plan.
 September 14, 2021, approval of the MHSA FY2022 Annual Update.  July 26, 2022, approval of the MHSA FY2023 Annual Update.  July 25, 2023, approval of the MHSA FY2024 – 2026 Three Year Program and Expenditure Plan.
 September 10, 2024, approval of the MHSA FY2025 Annual Update.

Council has also previously approved the initial MHSA component plans, Innovation Plans, the uses of funding for local housing development projects, and contracts with community-based agencies to implement mental health services and supports, housing and vocational services, and translation services.

ENVIRONMENTAL SUSTAINABILITY AND CLIMATE IMPACTS
There are no identifiable environmental effects, climate impacts, or sustainability opportunities associated with the subject of this report.

RATIONALE FOR RECOMMENDATION
State legislation requires mental health jurisdictions to create MHSA Three Year Plans and to provide updates on MHSA Plans on an annual basis. The legislation also requires local approval of MHSA Plans and Annual Updates. Approval of this MHSA FY2026 Annual Update will fulfill state requirements and enable MHSA funded programs and services to continue to be implemented.

ALTERNATIVE ACTIONS CONSIDERED
As obtaining approval on MHSA Plans and Annual Updates by the local governing body is a state requirement, there were no other alternative actions considered.

CONTACT PERSON
Karen Klatt, Community Services Specialist III, HHCS, (510) 981-7644 Jeff Buell, Manager of Mental Health Services, HHCS, (510) 981-7682 Attachments:
1: Resolution
Exhibit A: MHSA Fiscal Year 2026 Annual Update

RESOLUTION NO. ##,###-N.S.

MENTAL HEALTH SERVICES ACT (MHSA) FISCAL YEAR 2026 ANNUAL UPDATE WHEREAS, Mental Health Services Act funds are allocated to mental health jurisdictions across the state for purposes of transforming the mental health system into one that is consumer and family member driven, culturally competent, wellness and recovery oriented, includes community collaboration, and implements integrated service; and WHEREAS, MHSA includes five funding components: Community Services & Supports; Prevention and Early Intervention; Innovation; Workforce, Education and Training; and Capital Facilities and Technological Needs; and
WHEREAS, the City’s Department of Health, Housing & Community Services, Mental Health Division, receives MHSA Community Services & Supports, Prevention & Early Intervention, and Innovation funds on an annual basis and received one-time funding distributions for Workforce, Education & Training, and Capital Facilities and Technological Needs; and
WHEREAS, in order to utilize funding for programs and services, the Mental Health Division must have a locally approved MHSA Three Year Program and Expenditure Plan, or Annual Update in place for the funding timeframe; and WHEREAS, since the initial MHSA Plan in 2006, City Council has approved all MHSA Plans and Annual Updates, most recently on September 10, 2024 by Resolution No. 71,488-N.S., approving the MHSA FY2025 Annual Update; and WHEREAS, City Council has also previously approved Innovation Plans, the uses of MHSA funding for local housing development projects, and contracts with community- based agencies to implement mental health services and supports, housing and vocational services, and translation services; and
WHEREAS, in order to comply with State requirements, the MHSA FY2026 Annual Update must be approved by City Council
NOW THEREFORE, BE IT RESOLVED by the Council of the City of Berkeley that the MHSA FY2026 Annual Update that, incorporated herein as Exhibit A, is hereby approved.

BE IT FURTHER RESOLVED that the City Manager is authorized to forward the MHSA FY2026 Annual Update to appropriate State officials.

Exhibits
A: MHSA Fiscal Year 2026 Annual Update

CITY OF BERKELEY

MENTAL HEALTH

MENTAL HEALTH SERVICES ACT
(MHSA)

FISCAL YEAR 2025-2026

ANNUAL UPDATE

TABLE OF CONTENTS
BACKGROUND AND OVERVIEW 1
M
ESSAGE FROM THE MENTAL HEALTH MANAGER 7
DEMOGRAPHICS 8
MHSA FISCAL YEAR 2025/2026 ANNUAL UPDATE 16
P
ROPOSED PROGRAM CHANGES 18
PROGRAM DESCRIPTIONS AND FY24 DATA 20
COMMUNITY SERVICES & SUPPORTS (CSS) 20
PREVENTION & EARLY INTERVENTION (PEI) 69
INNOVATION (INN) 115
WORKFORCE, EDUCATION & TRAINING (WET) 117
CAPITAL FACILITIES AND TECHNOLOGICAL NEEDS (CFTN) 119
FY2026 PROJECTED COSTS PER PERSON 100 BUDGET NARRATIVE 121
APPENDIX A – BUDGETS 1A APPENDIX B – RESULTS-BASED ACCOUNTABILITY DATA 1B APPENDIX C – PEI FY2021/2022 – FY2023/2024 THREE-YEAR EVALUATION REPORT 1C APPENDIX D – INN FY2024 ANNUAL EVALUATION REPORT 1D

BACKGROUND AND OVERVIEW
California voters passed Proposition 63, the Mental Health Services Act (MHSA), in November 2004, to expand and transform the public mental health system. This legislation places a 1% tax on personal incomes above $1 million dollars. Funds are deposited into the MHSA State Treasury Fund and allocations per each mental health jurisdiction are determined based on the total population in a given area.

Through the following five funding components, the MHSA was designed to create the capacity for a broad continuum of prevention, early intervention and treatment services along with the necessary infrastructure, technology, and training elements to support effective mental health system transformation:
• C
ommunity Services & Supports (CSS): Primarily provides treatment services and supports for Severely Mentally Ill Adults and Seriously Emotionally Disturbed Children and Youth.
• Prevention & Early Intervention (PEI): For strategies t o recognize early signs of mental illness and to improve early access to services and programs, including the reduction of stigma and discrimination, and for strategies to prevent mental illness from becoming severe and disabling.
• Innovation (INN): For short-term pilot projects designed to increase new learning in the mental health field.
• Workforce, Education & Training (WET): Primarily for strategies to identify and remedy mental health occupational shortages, promote cultural competency and the employment of mental health peers and family members in the workplace. • Capital Facilities and Technological Needs (CFTN): For capital projects on owned buildings and on mental health technology projects.

Among other things, the MHSA was designed to provide enhanced services and supports for seriously emotionally disturbed children,
youth and Transition Age Youth
(TAY), adults, and older adults suffering from severe mental illness through a “no wrong door” approach and aims to move public mental health service delivery from a “disease oriented” system to one that is culturally responsive, consumer informed, and wellness recovery oriented. This is accomplished through implementing programs that focus on the following major components:
● W ellness, recovery and resilience
● Cultural competency
● Consumer/family member driven services
● Consumer/family member integration in the mental health system; and ● Community collaboration.

The MHSA also strives to improve and increase services and supports for individuals and families from cultural and ethnic populations that are traditionally unserved and

underserved in the mental health system. In Berkeley these have included: Asian Pacific Islanders (API); Latinos/Latinas/Latinx (Latino/a/x); Lesbian, Gay, Bi-Sexual, Transgender, Queer/Questioning, Inter-Sexed, Agender, Plus others (LGBTQIA+); Older Adults; and Transition Age Youth (TAY). African Americans have been an additional population of focus as data indicates they are overrepresented in the mental health system and hence “inappropriately served”, which could be due to being provided services that are not culturally responsive and/or appropriate.

In order to access MHSA funds, a stakeholder informed plan outlining how funds will be utilized must be developed and locally approved. Development of an MHSA Plan includes: community program planning with the involvement of area stakeholders, writing a draft plan, initiating a 30-day public review, conducting a public hearing at a Mental Health Commission meeting, and obtaining approval on the plan from City Council.

The Community Services & Supports, Prevention & Early Intervention, and Innovation funding components are the only re-occurring MHSA monies that are allocated annually and may be spent over a five-year period. Workforce, Education & Training and Capital Facilities and Technological Needs funds had initial expenditure time periods of 10 years each and were to be utilized by the end of Fiscal Year 2018 or 2019. Per the City Council approved
MHSA AB114 Reversion Expenditure Plan (which is posted on the City of Berkeley MHSA webpage), some CFTN and WET projects were continued past the original timeframes.

MHSA legislation requires mental health jurisdictions to provide updates on MHSA Plans on an annual basis, and an i
ntegrated Program and Expenditure Plan must also
be developed every Three-Years. Currently, the City of Berkeley Mental Health (BMH) Division has a City Council approved MHSA Fiscal Years 2023/2024 - 2025/2026 Three-Year Program and Expenditure Plan in place as well as Annual Updates for the fiscal year 2024/2025.

City of Berkeley MHSA Services
Since 2006, MHSA funding has been utilized to provide mental health services and supports in Berkeley. Additionally, from Fiscal Year 2011 (FY2011) through FY2020, the City of Berkeley also utilized a portion of MHSA funds to provide services in the City of Albany, although Albany is a part of the Alameda County total population. Beginning in FY2021, per agreement with Alameda County Behavioral Health Care Services (BHCS), the Division transitioned to only using MHSA funds for services and supports in Berkeley, and BHCS now provides MHSA funded services in Albany.

As a result of the City’s approved MHSA Plans and Annual Updates, a number of services and supports have been implemented to address the various needs of the residents of Berkeley. Some of the many programs include the following:
● Intensive services for Children, TAY, Adults, and Older Adults ● Multi-Cultural Outreach engagement, trainings, projects, and events

● Increased mental health services and supports for homeless individuals ● Wellness Recovery services and activities
● Family Advocacy, Housing services and supports, and Benefits Advocacy ● Case management and mental health services and supports for TAY ● Trauma support services for unserved, underserved, and inappropriately served populations
● I ncreased mental health prevention, and intervention services for children and youth in area schools and communities
● A Wellness Recovery Center in collaboration with Alameda County Behavioral Health Care Services (BHCS)
● Funding for increased services for older adults and the API population; and ● Services for individuals experiencing co-occurring disorders.

Additionally, an outcome of the implementation of the MHSA is that mental health peers, family members and other stakeholders now regularly serve on several of the BMH internal decision-making committees. These individuals share their “lived experience” and provide valuable input which has become an integral component that informs the Division on the implementation of MHSA services and supports. Even prior to the passage of Proposition 63, BMH convened (and has since maintained) an MHSA Advisory Committee which serves in an advisory role on MHSA programs and is comprised of mental health peers, family members, and community stakeholders.

This City of Berkeley MHSA Fiscal Year 2025/2026 (FY2026) Annual Update is a stakeholder informed plan that provides an update to the previously approved FY2024- 2026 Three-Year Program and Expenditure Plan (Three-Year Plan). This Annual Update summarizes proposed program changes, descriptions of MHSA services that will be continued in FY2026, through the approved FY2024-2026 Three-Year Plan, and a reporting of FY2024 program data. This Annual Update outlines the funding and programming for the last year of operation of the MHSA prior to transitioning to the funding and programming requirements of the voter approved Behavioral Health Services Act.

The Behavioral Health Services Act
In 2023 Senate Bill 326 (SB326), the Modernization of the Mental Health Services Act (MHSA) and Assembly Bill 531, a Behavioral Health Infrastructure Bond for treatment facilities and supportive housing were linked and signed by the Governor. On March 5, 2024 the linked bill was on the ballot as one measure, Proposition 1, which was narrowly passed by the voters.

This legislation renames the Mental Health Services Act (MHSA) to the Behavioral Health Services Act (BHSA) as it includes an allowance to utilize funding for services for individuals who have Substance Use Disorders. Beginning July 1, 2026, through the BHSA, the current five MHSA funding allocations will change to the following three components:

● Housing: For children and families, youth, adults and older adults living with severe mental illness or serious emotional disturbance and/or Substance Use Disorders who are experiencing homelessness or are at risk of homelessness, with 50% being prioritized for interventions for the chronically homeless. ● Full Service Partnership (FSP): Includes the use of funds for mental health, supportive services, and substance use disorder treatment services for Severely Mentally Ill Adults, Seriously Emotionally Disturbed Children and Youth, and individuals who experiences Substance Use Disorders.
● Behavioral Health Services and Supports: Includes early intervention, outreach and engagement, workforce education and training, capital facilities, technological needs, and innovative pilots and projects. A majority (51%) of funds must be used for Early Intervention services to assist in the early signs of mental illness or substance misuse, and 51% of the Early Intervention services and supports must be for individuals who are 25 years and younger.

Among other things, the BHSA will also make changes to the planning process and Three-Year Plans an
d Annual Updates. These changes will require the demonstration of coordinated behavioral health planning around all behavioral health funding received, and an integrated plan that includes all local behavioral health funding, services, and program outcomes. The Department of Health Care Services (DHCS) has recently released the new BHSA regulations. In preparation, the City has started pre-planning around the changes to MHSA and will begin engaging the community in the upcoming months to share information on the BHSA requirements and obtain input on local mental health needs.

MESSAGE FROM THE MENTAL HEALTH MANAGER
The City of Berkeley continues to face serious and evolving challenges that impact the behavioral health and well-being of its residents. Persistent racial and economic inequities, housing instability, and health disparities remain core concerns, while broader structural and policy shifts at the local, state, and federal levels further complicate the landscape. This Annual Update outlines how Berkeley’s Behavioral Health Division will respond to these realities with a continued focus on equity, community engagement, and innovation.

In these last few years, significant changes to funding streams and cost structures have i
ncreased pressure on behavioral health services. Budget constraints at loc al, state, and
federal levels of government, combined with policy shifts and rising service demands, are impacting how services are planned and delivered. Proposition 1 fundamentally shifts how the Behavioral Health Services Act (BHSA) will serve our local communities, and what the future will hold with respect to the services they support.

BHSA funding continues to serve as a vital source of support for a range of innovative and equity-focused mental health initiatives. Investments include the expansion of community-based outreach teams and new models of care that support crisis response, enhance connections to peer support and recovery services, and strengthen pathways to culturally responsive care.

While economic uncertainty and funding changes remain challenges across the behavioral health field, Berkeley’s Behavioral Health Division remains focused on stability, equity, and innovation. We are closely monitoring evolving conditions and adjusting as needed to sustain core services and meet emerging needs.

The City of Berkeley presents this Annual Update with appreciation for the necessary collaboration and partnerships that are vital to support this work—community members, providers, staff, and peers alike. This dedication, hard work, and insight are essential as we move forward together.

Jeff Buell, LCSW
Manager of Mental Health Services

DEMOGRAPHICS
Description
Situated in the heart of the San Francisco Bay area, and home to the University of California, Berkeley is an urban city, located in northern Alameda County. With a combined land mass of around 12.2 miles and a total population of approximately 118,962 (updated estimates since the 2020 census), the City of Berkeley is densely populated and larger than 23 of California’s small counties.

Race/Ethnicity
Berkeley is a diverse community with changing demographics. The African American population has decreased in recent years while the Latinx and Asian populations have both increased. Berkeley has a large student population, which provides housing for many of University of California’s foreign students and their families. Threshold languages include English, Spanish, Farsi, Cantonese, and Vietnamese, and approximately 30% of Berkeley residents speak a language other than English at home.

Berkeley is comprised of the following racial and ethnic demographics: African American; Asian; Latino/Latina/Latinx; White; American Indian/Alaska Native; and Native Hawaiian/Pacific Islander (P.I.). Demographics are outlined below:

African
American 8%
Asian 21%
White
56%
Latinx
13%
Am. Indian/
Alaska Native
1%
N. Hawaiian/
P. I., <1%
City of Berkeley Race/Ethnicity

Age/Sex
As depicted in the table below, a large percentage of individuals in Berkeley are over the age of eighteen:

Sex demographics are as follows:

12%
88%
U
nder 18 18 & Over
City of Berkeley
Age
Females
Males
51%
49%
City of Berkeley
Sex

Lesbian, Gay, Bisexual, Transgender, Queer/Questioning, Intersexed, Agender, Plus (LBGTQIA+) Population
Per a brief by the Williams Institute, UCLA, entitled “LGBT Adults in Large US Metropolitan Areas” the LGBT population is 6.7% in the San Francisco Bay Area.

According to the Brief, the estimated percentages of adults age 18 and older who identify as LGBT was derived from the Gallup Daily Tracking Survey which is an annual list-assisted random digit dial (70% cell phone, 30% landline) survey, conducted in English and Spanish, of approximately 350,000 U.S. adults ages 18 and up who reside in the 50 states and the District of Columbia. LGBT identity is based on response to the question, “Do you, personally, identify as lesbian, gay, bisexual, or transgender?” Respondents who answered “yes” were classified as LGBT. Respondents who answered “no” were classified as non-LGBT. Estimates derived from other measures of sexual orientation and gender identity may yield different results. (Conron,K.J, Luhur.W., Goldberg, S.K. Estimated Number of US LGBT Adults in Large Metropolitan Statistical Areas (MSA), (December 2020). The Williams Institute, UCLA. Los Angeles, CA.)
Income/Housing
With some of the highest housing costs in the Bay Area, the Berkeley median household income is $104,716. Nearly 18% of Berkeley residents live below the poverty line and approximately 27% of Berkeley children qualify for free and reduced lunches. While 43% of Berkeley residents own their own homes, there are many individuals experiencing homelessness including women, TAY, and Older Adults.

In order to measure the prevalence and characteristics of homelessness, a comprehensive street count of individuals experiencing homelessness is conducted in communities across the country every two years. According to the 2024 Alameda County Everyone Home Point-in-Time Count, which included a detailed assessment of the City of Berkeley, approximately 844 individuals were experiencing homelessness.

Of this amount 47% were in some form of shelter, and 53% were unsheltered (as defined by someone whose primary residence is a car, park, abandoned building, or another place that isn’t designed to be housing). These numbers represent a 20% decrease in the overall homeless population, and a 45% decrease in individuals who are unsheltered in Berkeley since the 2022 Alameda County Everyone Home Point-in- Time Count. Since 2021, there have been several initiatives to support individuals who are experiencing homelessness, and funding for new housing in the City, which has had a direct impact on individuals who are unhoused.

Education
Berkeley has a highly educated population: 9% of individuals aged 25 or older are high school graduates; and approximately 75% possess a bachelor’s degree or higher.

System Organization
Berkeley Mental Health (BMH), one of two city-based public mental health programs in the state, provides services for residents in Berkeley. It is a Division of the City of Berkeley Health, Housing & Community Services (HHCS) Department. Services are provided at multiple clinic sites and in the field. BMH provides the following services:

Crisis; Family, Youth & Children; High School Mental Health, Full Service Partnership Services, and Adult Services. Services include: assessment, assertive community treatment, individual and group therapy, case management, and crisis intervention. In addition to offering treatment, outreach, and support, some services are provided through a variety of community-based agencies and at school sites. As part of Crisis services, a Mobile Crisis Team operates seven days a week when fully staffed. The majority of mental health services provided by BMH are aimed towards the Medi-Cal and uninsured population; as such it is important to note the ways in which the Medi-Cal population demographics differ from the overall demographics in Berkeley. Per available data for the reporting timeframe, the Medi-Cal population was as follows:

Al.Nat./Am.

In. 1%
AAPI
3%
African
American
30%
Latino
11%
White
22%
Other/Unkown
33%
Alaska Native/American Indian AAPI African American Latino White Other/Unknown

COMMUNITY PROGRAM PLANNING
During the Community Program Planning (CPP) process one MHSA Advisory Committee meeting was held on Tuesday, April 29th, and four Community Input Meetings were held on the following dates/times:
● T uesday, May 6th: 6:00pm-7:30pm
● Thursday, May 8th: 3:30pm-5:00pm
● Monday, May 12t
h: 6:00pm-7:30pm
● Wednesday, May 14th: 1:00-2:30pm
Announcements of the meetings were sent to MHSA Advisory Committee members, mental health peers, family members, representatives from community-based organizations, individuals from unserved, underserved and inappropriately served populations, HHCS Staff, City Commissioners, and other MHSA stakeholders.

During the MHSA Advisory and Community Input Meetings a presentation was conducted to provide information on MHSA background, funding, program requirements, the CPP process, and on upcoming changes to the funding requirements as a result of Proposition 1. The presentation also covered detailed information on the proposed MHSA FY2026 Annual Update and provided opportunities for input from the community.

An anonymous voluntary survey through Survey Monkey to obtain demographic information on individuals who participated in the CPP process, was administered during each meeting and to individuals who reached out by phone or email. Results of 19 individuals who voluntarily participated in the Survey were as follows:

DEMOGRAPHICS N = 19
(Numbers that are 11 or less are displayed as <11 and/or have been combined or masked to protect the privacy and confidentiality of individual participants. **Many participants were in more than one category ). ● Age Category
Transition Age Youth - <11
Transition Age Youth - <11
Adult - <11
Older Adult - <11
Declined to Answer to Answer (or Unknown) - <11
● Gender Identity
Male - <11
Female - <11
Declined to Answer (or Unknown) - <11
● Race/Ethnicity
Black or African American - <11
White - <11

Latino/a/x - <11
Declined to Answer (or Unknown) - <11
● Sexual Orientation
Heterosexual - <11
Declined to Answer (or Unknown) - <11
● Veteran Status
Veteran - <11
Non-Veteran - <11
Declined to Answer (or Unknown) - <11
● Disability Status
Declined to Answer (or Unknown) – 19
● Representative Categories
Consumer - <11
Family Member of Consumer - <11
Community Member or MHSA Stakeholder - <11
Veteran - <11
Representative of Mental Health Commission - <11
Representative of Mental Health or Social Services Agency - <11 Representative of Substance Use Disorder Agency - <11
Representative of a Health Care Organization - <11
Student, Staff, Representative or Parent of Student of Berkeley Unified School District - <11
Student, Staff, Representative or Parent of UC Berkeley or Berkeley City College - <11
Declined to Answer (or Unknown) - <11

As a method to continue to gather input from the community on this Annual Update, two additional Community Input meetings will be scheduled during the 30-Day Public Review. As with previous MHSA Plans and Annual Updates, a methodology utilized for conducting CPP for this Annual Update was implemented to enable a collaborative process to occur between BMH staff, MHSA Advisory Committee members, Community members and other MHSA stakeholders. Development of this Annual Update began with an internal examination of existing programs, unaddressed needs, and available funding which included a review of input received over the prior year and during previous MHSA planning processes. Following an internal review, proposed new additions were vetted through the MHSA Advisory Committee prior to engaging community members and other MHSA stakeholders.

Proposed program changes in this Annual Update include the following:
● Move an Assistant Management Analyst position that was previously approved for the Mental Health Manager, to the Adult Full Services Partnership.

● Transfer a portion of unspent CSS Funds to the WET Component, to provide future funding for the Workforce Development Coordinator position, and for stipends to support two student administrative interns, and six clinical interns. ● Transfer a portion of CSS Funds to the CFTN Component to support the future acquisition of a Mental Health facility, and/or mental health facility needs. ● Utilize previously approved funding to support the African American Holistic Resource Center, Sankofa Project.

The following program addition was also added as a result of input received during the 30-Day Public Review:
● Allocate an additional amount of funds for Insight Housing, to support the Russell Street Residence.

Details are outlined in the “Proposed Program Changes” section of this Annual Update.

During the Community Program Planning process, questions received were primarily around MHSA funded and area services, local housing, and the upcoming changes with BHSA. A concern was voiced regarding safety issues around placing individuals who have been homeless, at Senior Citizen housing sites and input received included:

Ensuring individuals who have experienced homelessness are placed at a housing site that includes services to support them with acclimating to being housed; and to implement a program that provides individuals with the necessary services and supports to assist them in breaking the cycle of experiencing recurrent 5150 (hospitalization) events. An additional concern was around whether the Division has the appropriate level of staff resources for outreach, specifically to engage marginalized individuals and communities.

A 30-Day Public Review was held from Wednesday, May 28
th through Thursday, June
26th to invite input on this Annual Update. A copy of the Annual Update was posted on the BMH MHSA website, and announcements of the 30-Day Public Review were mailed and/or emailed to community stakeholders and City staff. Individuals interested in providing input on this Annual Update were also able to attend two community meetings that were held during the 30-Day Public Review:
● Thursday, June 12th: 6:00pm-7:30pm
● Tuesday, June 17th: 5:00pm-6:30pm
Information on the Community Input Meetings were posted on the MHSA webpage and on the City’s event calendar. Announcements of the meeting were also mailed and/or emailed to community stakeholders and City staff. For information regarding the Community Input Meetings, the Public Hearing, or the to provide input on the FY2026 Annual Update the public was invited to contact Karen Klatt, MHSA Coordinator, by phone (510) 981-7644, or email at: [email protected] A Public Hearing on the Annual Update was held at 7:00pm on Thursday, June 26th, during the Mental Health Commission meeting. During the Public Hearing various

questions were asked and answered regarding some of the funding and programs within the FY2026 Annual Update. The Executive Director of Pacific Center for Human Growth submitted written input that was read during the Public Hearing. Written input is included in Appendix E of this Annual Update.

Following the Public Hearing the Mental Health Commission passed the following motion: M/S/C (Krishnan, Sol) Motion to approve the annual update with the stipulations of the figures being re-calculated on page 129.

Ayes: Gu, Krishnan, Opton, Sol, Teague, Turner; Noes: None; Abstentions:

None; Absent: Tregub, Prichett, Jones
Note that the Mental Health Commission motion refers to figures in the “FY2026 Projected Numbers To be Served and Estimated Cost Per Person” chart, which was on page 129 in the Draft FY2026 Annual Update.

There were four substantive comments received that warranted changes to the FY2026 Annual Update as follows:
● Provide additional funding for Insight Housing to help defray increased costs at the Russell Street Residence.
● Correct two errors that were found in the calculations of the “FY2026 Projected Numbers to Be Served and Estimated Cost Per Person Chart”. ● Change the amount of funds to be utilized in FY2026 for the African American Holistic Resource Center.
● Update the expenditures from the Workforce, Education & Training Budget page, that were not previously carried forward to the Budget Summary page.

The Annual Update and Budget pages in this final version of the Annual Update have been edited to reflect these additions and changes.

MHSA FISCAL YEAR 2025-2026 ANNUAL UPDATE
This City of Berkeley MHSA Fiscal Year 2025/2026 (FY2026) Annual Update is a stakeholder informed plan that provides an update to the previously approved MHSA FY2023/2024 – 2025/2026 Three-Year Program and Expenditure Plan (Three-Year Plan). This Annual Update summarizes proposed program changes, includes descriptions and updates of currently funded MHSA services that will be continued in FY2026 through the previously approved Three-Year Plan, and provides a reporting on FY2024 program data. Additionally, per state regulations, this Annual Update includes the Prevention and Early Intervention (PEI) Fiscal Year 2021/2022 – 2023/2024 Three- Year Evaluation Report (Appendix C). Although there were not any INN Programs in operation in FY2024, in order to comply with state regulations, an Innovation Fiscal Year 2023/2024 Annual Evaluation Report has also been included in Appendix D of this Annual Update.

As reported in previous MHSA Plans and Annual Updates, the Division has engaged in s
everal initiatives over the past several years to increase data collection and evaluation efforts including the following:
● I mpact Berkeley : In 2018, the Health Housing and Community Services (HHCS) Department implemented “Impact Berkeley”. Central to this initiative is using a highly regarded framework called Results Based Accountability (RBA) to account for the work of the Department. RBA provides a new way of understanding the quality and impact of services provided by collecting data that answer three basic questions:

1. How much did you do?

2. How well did you do it?

3. Is anyone better off?
RBA has been incorporated into selected programs within the Department. This has included community agency programs funded t
hrough the MHSA Prevention
& Early Intervention (PEI) Community Education & Supports program. Through this initiative the Department worked with each contractor to envision, clarify and develop measures on the outcomes and results each program is seeking to achieve, and used a rigorous framework to measure and enhance progress towards these results. The results of this initiative are outlined in the PEI Community Education & Supports program section of this Annual Update. ● R esults Based Accountability f or all BMH Programs: Through a previously approved MHSA Annual Update the Division hired Resource Development Associates (RDA) to conduct a Results Based Accountability (RBA) Evaluation for all programs across the Division. RDA worked with the Division from FY2021- FY2024 to implement the RBA research methodology. An update of the activity’s RDA conducted in FY2024 on this evaluation is included in this Annual Update.

RBA outcomes in FY2024 are outlined throughout this Annual Update for the following MHSA funded internal programs: Children/Youth FSP; TAY, Adult and

Older Adult FSP; Homeless FSP; Wellness Recovery Services; Crisis Services; Transitional Outreach Team; Social Inclusion Project; and the High School Prevention Project. The complete set of RBA outcomes for all BMH programs is located in Appendix B.

● P rogram Evaluator : Per the approved FY2023 Annual Update, the Division hired a Program Evaluator who provided work and oversight through FY2024 on the RBA Evaluation. Since the ending of the RDA contract the Project Evaluator has directly taken over RBA Evaluation work, as well as other various data collection, analysis, and evaluation work within the Division.
● P
er State requirements, Evaluation Reports for PEI and INN programs are also included in the Appendix of this Annual Update as follows:
• PEI Data Outcomes: Per MHSA PEI regulations, all PEI funded programs are required to collect state identified outcome measures (specific to the category of services provided) as well as detailed demographic information. PEI Evaluations are required to be included in each MHSA Annual Update or Three-Year Plan.

See Appendix C for the Prevention & Early Intervention (PEI) Fiscal Year 2021/2022–2023/2024 (FY22-24) Three-Year Evaluation Report. • INN Data Outcomes: Per MHSA INN regulations, all INN funded programs ar e
required to collect state identified outcome measures and detailed demographic information. INN Evaluations are required to be included in each MHSA Annual Update or Three-Year Plan. Although there were not any INN Programs in operation in FY2024, in order to comply with state regulations, an Innovation (INN) Fiscal Year 2023/2024 Annual Evaluation Report has been included in Appendix D of this Annual Update.

PROPOSED PROGRAM CHANGES
The Division is proposing the following changes through this Annual Update:

Move Assistant Management Analyst position to A dult Full Services Partnership:

Through the previously approved Three-Y
ear Plan, the Division received approval to
hire an Assistant Management Analyst to support the Mental Health Manager. In an effort to support the need for administrative support, the Division is proposing to move this position to the Adult Full Services Partnership Program.

Provide previously approved MHSA funds for the African American Holistic Resource Center:

The African American/Black Professionals & Community Network (AABPCN) crafted a report titled “A Community Approach for African American/Black Culturally Congruent Services.” This report identified challenges that the African American community faces in areas of education, employment, health, and mental health, housing, and community relationships. A vision and framework were provided in the report for the development of an African American Holistic Resource Center (AAHRC) in South Berkeley. The center will include the use of culturally congruent practices, embedded in an integrated service delivery system, which will help to decrease inequities and disparities in the African American community in Berkeley. The delivery of culturally congruent services at the AAHRC will provide African Americans with the support they need to decrease inequities and disparities, and build community.

One of the various components of the AAHRC will be Project Sankofa. Project Sankofa is focused on promoting mental wellness and is a campaign that aims to eradicate the stigma around mental health through love and compassion. It uses Black affirming methodologies to bring about a paradigm shift in how mental health and wellness are approached and communicated within communities of color. Deliverables include group/family/community mental health and wellness workshops and healing circles; community engagement activities; online social media campaign.

Through the MHSA FY2024-2026 Three-Year Plan, the Division received approval to provide $300,000 of Community Services and Supports (CSS) System Development Funds in FY2024 to support the AAHRC, Project Sankofa. Since FY2024, the allocation of funding, and implementation of the AAHRC Project Sankofa, has experienced some unexpected delays. However, in FY2026, the Division will allocate the previously approved $300,000 in funds for the AAHRC to implement Project Sankofa. It is envisioned that a contract with Healthy Black Families will be executed, who will serve as the fiscal administrator to the AAHRC for this project.

Provide a one-time funding Increase to support the Russell Street Residence:

Operated through Insight Housing, the Russell Street Residence provides permanent supportive housing for 17 formerly homeless adults who have experienced severe and persistent mental illness. Residents receive the following: supportive services; meals; therapeutic groups, activities and outings; transportation to medical appointments; and assistance with daily activities including laundry and personal hygiene.

Costs have increased since the contract was planned and executed, resulting in a shortfall of funds prior to the end of the planned contract. As such through this Annual Update the Division is proposing to allocate a one-time amount of $250,000 of CSS System Development funds for Insight Housing to help defray the increased costs at the Russell Street Residence.

Transfer Community Services and Supports funds to the Workforce, Education and Training component: For each year of the previously approved Three-Year Plan, the Division is able to transfer a portion of Community Services and Supports (CSS) System Development Funds to the Workforce, Education and Training (WET) component to fund the Workforce Development Coordinator position through the following process: Per MHSA Statute, (Welfare and Institutions Code, Section 5892 (b)): “In any year after 2007-08, programs for services pursuant to Part 3 (commencing with Section 5800), and Part 4 (commencing with Section 5850) of this division may include funds for technological needs and capital facilities, human resource needs, and a prudent reserve to ensure services do not have to be significantly reduced in years in which revenues are below average of previous years. The total allocation for purposes authorized by this subdivision shall not exceed 20 percent of the average amount of funds allocated to that county for the previous five years pursuant to this section.” Through this Annual Update the Division is proposing to transfer $344,426 of unspent CSS Funds to the WET Component. Once transferred, approximately $167,116 of funds will be used to support the Workforce Development Coordinator position. The remainder of funds, approximately $177,310 are being proposed to be utilized in the upcoming years on a Stipend Program to incentivize Student Interns to provide Clinical or Administrative work within the Division over a given period of time.

Transfer Community Services and Supports Funds to the Capital Facilities and Technological Needs component: Through this Annual Update the Division is proposing to transfer $1,300,000 of unspent Community Services and Supports (CSS) funds to the Capital Facilities and Technological Needs (CFTN) component through the following process:

Per MHSA Statute, (Welfare and Institutions Code, Section 5892 (b)): “In any year after 2007- 08, programs for services pursuant to Part 3 (commencing with Section 5800), and Part 4 (commencing with Section 5850) of this division may include funds for technological needs and capital facilities, human resource needs, and a prudent reserve to ensure services do not have to be significantly reduced in years in which revenues are below average of previous years.

The total allocation for purposes authorized by this subdivision shall not exceed 20 percent of the average amount of funds allocated to that county for the previous five years pursuant to this section.”
Once funds have been transferred to CFTN, they will be utilized in the upcoming years to support various BMH facility needs, and/or as a match for the Department of Healthcare Services, Behavioral Health Continuum Infrastructure Program (BHCIP) should the City choose to apply. Uses of funds for facility needs may include but not be limited to the following: acquiring a new building, remodeling or renovating existing structures, and/or repairs, among other allowable CFTN related expenditures.

PROGRAM DESCRIPTIONS AND FY2021 DATA

BY FUNDING COMPONENT
Outlined in this section per each funding component are descriptions of current City of Berkeley MHSA services that were continued through the previously approved Three- Year Plan and FY2024 program data. In FY2024, across all MHSA funded programs, approximately 5,208 individuals participated in some level of services and supports.

Some of the FY2024 MHSA funded program highlights included: A reduction in psychiatric emergency services usage and/or incarceration days, and increased access to primary care services for severely mentally ill clients; step down to a lower level of care for some clients; services and supports for family members; increased services for individuals who are experiencing homelessness; Wellness Center services; co- occurring services for individuals who are experiencing both mental health needs and substance use disorders; community-based support group services; consumer driven wellness recovery activities; housing and benefits advocacy services; augmented prevention and early intervention services for children and youth in the schools and community; and supportive services for TAY, Adults and Older Adults in unserved, underserved and inappropriately served cultural and ethnic populations.

COMMUNITY SERVICES & SUPPORTS (CSS)
The Community Services & Supports (CSS) funding component primarily provides treatment services and supports for Severely Mentally Ill Adults and Seriously Emotionally Disturbed Children and Youth. Funding is provided in three areas of programming: Full Services Partnerships; Multicultural Outreach & Engagement; and System Development.

Following a year-l
ong community planning and plan development process, the initial City of Berkeley Community Services & Supports (CSS)
Plan was approved in
September 2006. Since the approval of the original plan, Three-Year Plans or Annual Updates outlining proposed CSS funding and programming have been developed and approved on an annual basis. From the original CSS Plan and/or through subsequent plan updates, some of the many services the City of Berkeley has provided through CSS funding are as follows:
● Wrap-around Services for Children and their families
● TAY, Adult and Older Adult Intensive Treatment Services ● Supportive Services for Individuals experiencing homelessness ● Diversity & Multi-cultural Services
● TAY Case Management and Support Services
● Consumer Advocacy
● Wellness and Recovery Services
● Family Advocacy
● Transitional Outreach Team
● Support Groups for individuals

● A Wellness Recovery Center; and
● Benefits Advocacy.

Descriptions of each CSS funded program that were continued through the previously approved Three-Year Plan, and FY2024 data are outlined on the following pages.

Throughout all CSS programs, demographic data representing numbers that are 11 or less are displayed as <11 and/or have been combined or masked to protect the privacy and confidentiality of individual participants.

Full Service Partnerships (FSP)
Children/Youth Intensive Support Services Full Service Partnership The Children/Youth Intensive Support Services Full Service Partnership (CFSP) is for children ages 0-21 and their families. This program is for children, youth and their families who would benefit from, and are interested in participating in a program designed to address the total needs of a family whose child (and possibly other family members) is experiencing significant emotional, psychological or behavioral problems that are interfering with their wellbeing.

Priority populations include children and youth who:
● H ave substantial impairment in self-care, school functioning, family relationships, the ability to function in the community, and are at risk of or have already been removed from the home and have a mental health disorder and/or impairments that have presented for more than six months or are likely to continue for more than one year without treatment;
OR
● D isplay psychotic features, or a history of hospitalization due to Danger to Self, Danger to Others, Grave Disability or a recent suicide attempt within the last six months from the date of referral.

The CFSP program utilizes wraparound as the treatment model. Wraparound differs from many service delivery strategies, in that it provides a comprehensive, holistic, youth and family-driven way of responding when children or youth experience serious mental health or behavioral health challenges. The model puts the child or youth and family at the center. With the help of the CFSP team, the family and young person take the lead in deciding their vision and goals. Team member’s work together to put the goals into an action plan, monitor how well it is working, and make changes to it as needed.

In FY2024, a total of 14 children/youth and their families were served through this program. Demographics on those served were as follows:

DEMOGRAPHICS N = 14
*Numbers that are 11 or less are displayed as <11 and/or have been combined or masked to protect the privacy and confidentiality of individual participants.
● Age Category
6 – 25 years – 14
● Gender Identity
Male - <11
Female - <11
Declined to Answer - <11

● Race/Ethnicity
Asian Pacific Islander - <11
Black or African American - <11
Latino/a/x - <11
Other - <11
● Sexual Orientation
Heterosexual - <11
Lesbian/Gay/Bisexual/Queer/Questioning or Unknown - <11 Flex funds are used to provide various supports for FSP program participants and/or the families of program participants. In FY2024, flex funds were utilized as follows: 31 individuals/families received funding for food/groceries; 6 individuals/families received funds for clothing/hygiene; 2 individuals/families received funds for pharmacy needs; 14 individuals/families received funds for furniture/household items; 3 individuals/families received funding for Bus Passes or transportation; and 9 individuals/family members received funding for other various needs.

The CFSP team had staff turnover this fiscal year: The current Sr. Behavioral Health Clinician was hired during the fiscal year and has been working to grow in her role as the lead clinician on the team. Fortunately, she was hired from within the program and was aware of many aspects of the team and their work with our clients.

Program Successes:
• Increased referrals accepted due to having a fully staffed team. • Opened cases and provide care to mono-lingual Spanish speaking families. • Increased access to psychiatric medication services and the provision of individual/family therapy.
• Continued to reduce psychiatric hospitalizations and the usage of crisis services due to the care provided by the team and system coordination with the clients extended treatment team.
• Services continued to be provided by clinicians who mirrored the racial/ethnic identity of the populations served.
• Successfully, transitioned a TAY youth to an FSP program in Oakland and supported their transition to independent housing in the community. • Continued to provide flex funding to support the needs of clients; this was extremely important as there was an increase in needs due to parent’s loss of employment, the increase cost of goods and services, and parents continued to struggle with unresolved trauma. These funds supported the purchase of birthday/holiday gifts, food, household items, car repairs, hotel stays for unhoused families, pro-social activities for clients/their siblings, legal fees, summer camp attendance for a family, and clothing.
• Successfully supported client families to use the After-Hours service to reduce the need for emergency/crisis services.

Program Challenges:
• The primary challenge was to consistently engage caregivers who had multi- faceted stressors in the family system which made it difficult for them to meet with the clinician. This made it difficult for the family system to improve as most of the focused work was directed toward the youth rather than both supporting the youth’s needs along with the changes that could help the entire system.

In FY2026 the projected number of individuals to be served per each age category is as follows: Children (0-15) years = 10; Transition Age Youth (16-25 years) = 11; Adults/Older Adults (26-60+) = 0.

The RBA Measures that were established for this FSP were as follows:

Process Measures
How much did we do?
Quality Measures
How well did we do it?
Impact Measures
Is Anyone Better off?
• # of clients served
• # of new clients opened
for ongoing services
• A verage # of days in
FSP for client
• Average # of services
hours per client per
month
• A
verage # of services
per client per month
• % of clients who have at
least completed one
CANS/ANSA for each six-
month period that they are
in the program
• % of clients and/or their
caregivers who receive an
average of four or more
face-to-face outpatient visits
per month
• %
of discharges from
hospitalization or subacute
who had a follow-up visit
with CFSP staff within 7
business d
ays
• % of clients with no service
gap of over 30 days
• #/% of clients closed, by
reason closed
• % of clients or family
members who participate in
the survey**
• % of clients with a primary
care visit in the last 12 months
• % of clients who had a
reduction in psychiatric care
emergency services/inpatient/
crisis stabilization units in the
l
ast 12 months compared to
the 12 months before
enrollment**
• % of clients with a decrease in
hospitalizations/hospitalization
days
*Demographic data was reported at the program level, where available **Data not available for baseline reporting period, will be included in future rounds of reporting.

RBA Outcomes in FY2024 for this FSP are outlined on the following pages.

14 Clients Served
New Clients
Process Outcomes ("How much did we do?")
BMH RBA Report FY 2024
Reporting Period July 2023 - June 2024
Child Full Service Partnership (CFSP)
*De-identified
(n<11)
Program Description: This team provides wrap around services to children and families with acute needs, who meet the following criteria: child is at risk of/has been removed from their parent/guardian; child is involved with the Juvenile Justice System or at risk of that; has been recently had a psychiatric hospitalization or is at risk of a hospitalization.100%
6-25
Demographics (Age)
Jul '23 - Jun '24 (n=14)
<11 <11 <11 <11
Black or
African
American
Hispanic or
Latino
Asian or
Pacific
Islander
Unknown
Demographics (Ethnicity)
Jul '23 - Jun '24 (n=14)
<11 <11 <11
Female Male Other*
Demographics
(Gender Identity )
Jul '23 - Jun '24 (n=14)
*LGBQ+ includes individuals who identify as lesbian, gay, bisexual,questioning, or other diverse sexual orientations.

Other includes prefer not to answer or
<11
<11
Heterosexual
LGBQ+ or
Other*
Demographics
(Sexual Orientation)
Jul '23 - Jun '24 (n=14)
*Other includes any identity that doesn't fit within
the traditional male/female binary.

NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted, and may not visually reflect actual counts. 19

Quality Outcomes ("How well did we do it?")
Service Consistency
Clients Spend 300 days
in FSP on average
5 7
A
verage # of service hours per
client per month
Average # of services per client
per month
Average Monthly Services per
Client
Jul '23 - Jun '24 (n=14)
Retention and Stability
90-100% n<15
Clients with at least
one completed
CANS assessment
every six months
while in the program
60-70% n<15
Clients receive an
average of 4+
face-to-face visits
per month
90-100% n<15
Discharges from
hospitalization or
subacute who had a
follow up visit with
within 7 days
70-80% n<15
Clients with no
service gap of over
30 days
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted, and may not visually reflect actual counts. 20

Impact Outcomes ("Is anyone better off?")
Client Outcome Improvements
50-60% n<15
Clients with a Primary
care visit
90-100% n<15
Client reduction in
psychiatric
emergency
services/inpatient/
crisis stabilization
units
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted, and may not visually reflect actual counts. 21

Measure Definition Data Source
# clients served Total clients served Y ellowfin
# of new clients Clients who were not served by the program in the previous fiscal year Yellowfin
Average # of service hours per client
per month
Average of hours of service in a month divided by
clients served in a month. Includes all services
recorded for clients. Does not include medcation
services (MAA).

Yellowfin
Average # of services per client per
month
Average services in a month divided by clients served
in a month. Includes all services recorded for clients.

Note: more than one service can be provided during
a single contact. Does not include MAA
Yellowfin
% of clients with no service gap of over
30 days
Maximum days each Level 1 client went without
service during their episode(s) in the reporting period.

Only considered clients open to a provider for at least a total of three months during the reporting fiscal year.

Yellowfin
% of clients who have at least one
completed CANS/ANSA for each six-
month period that they are in the
program
Of clients with a completed Child or Adult Needs and
Strengths Assessment (CANS/ANSA), what percentage
of them had an assessment at least every six months?
Objective Arts
% of clients and/or their caregivers
who receive an average of four or
more face-to-face outpatient visits per
month
Clients must be been open to a provider for at least 30 days in order to be included in this metric. Phone
contacts are included during the pandemic. Days in
subacute or jail not counted, but services are
counted.

Yellowfin
Yellowfin
Follow-up rates for individuals open to Level 1
providers at the time of mental health hospital
discharge.
*note: clients used to calculate follow up rates include those who didn’t receive outreach and those who
were lost to follow up (e.g. not contactable, not
% of discharges from hospitalization or
subacute who had a follow up visit
with FSP staff within 7 business days
% of clients with a primary care visit
Of clients who completed 6 consecutive months
during the fiscal year, percentage who had an
appointment with a Anthem/Alliance/Community
Health Center Network (CHCN) primary care provider
during the fiscal year. Metric excludes individuals with six or more months out of the community (in Subacute,
MH hospital, and/or jail).

Yellowfin
#/% of clients closed, by reason closed Discharge reason for clients discharged during the reporting period
Yellowfin
*Not presented
due to delays in
the reporting
system
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted, and may not visually reflect actual counts. 22

% of clients with a decrease in
hospitalization days/admissions
Decrease in hospital days/admissions in the years that
a client was active in the program compared to the
year prior to program admission. Includes clients who
had at least one hospital day in the 12 months prior to admission and remained in the program for at least 1
year. Only available for fiscal years.

Yellowfin
Note: Data
Suppressed (<11
clients)
Average # of days in FSP per client The average number of days a client remains enrolled in the Full-Service Partnership (FSP) program. Yellowfin NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted, and may not visually reflect actual counts. 23

Adult Full-Service Partnership
The Adult Full-Service Partnership (AFSP) offers dedicated support services to individuals aged 18 and older (Transitional Age Youth, Adults, and Older Adults) facing severe mental illness. Grounded in the Assertive Community Treatment (ACT) approach, the program is designed to assist individuals encountering challenges in obtaining or sustaining housing, enduring frequent and/or prolonged psychiatric hospitalizations, and experiencing repeated or extended periods of incarceration.

Priority populations include those from unserved, underserved, and culturally and ethnically marginalized communities.

The ACT approach maintains a low staff-to-client ratio of 10:1, enabling frequent and intensive support services to clients. Clients receive assistance in securing suitable housing, with the potential for temporary financial aid. The primary objectives of the program are to actively involve clients in their treatment and to reduce the instances of homelessness, hospitalization, and incarceration. In tandem, it seeks to improve employment and educational preparedness, encourage self-sufficiency, and support overall wellness and recovery. Through a targeted commitment to these goals, the Adult Full Services Partnership endeavors to significantly improve the lives of its participants.

In FY2024 a total of 66 TAY, Adults, and Older Adults participated in the program for all or part of the fiscal year. Demographics on those served include the following:

DEMOGRAPHICS N = 66*
*Numbers that are 11 or less are displayed as <11 and/or have been combined or masked to protect the privacy and confidentiality of individual participants.
● Age Category
18 – 24 or Unknown - <11
25 – 44 years – 21
45 – 64 years – 20
65 years and older – 20
● Gender Identity
Male - 40
Female - 26
● Race/Ethnicity
Asian Pacific Islander - <11
Black or African American - 38
Latino/a/x - <11
White – 23
Decline to Answer or Unknown - <11
● Sexual Orientation
Heterosexual - 54
Lesbian/Gay/Bisexual/Queer/Questioning or Unknown – 12

Flex funds are used to provide supports for FSP program participants. In FY2024, 17 partners received rental and housing assistance; 44 received food and groceries; 6 received In-Home Assistance (cleaning, activities of daily living); and 32 partners were provided with clothing, furniture, hygiene products, and assistance with utility bills tr; and 24 partners received bus passes or other transportation assistance.

In FY2024 this program experienced an increase in clients served, improved service engagement, and better continuity of care. However, 7-day hospital follow-up rates declined, and clients continue to experience financial hardship, increasing the need for flex fund assistance. Overall, client outcomes improved, especially in reducing jail days, psychiatric emergency services use, and increasing primary care access. There were demographic shifts in the individuals served including the following: African American clients increased from 54% to 58%; White clients decreased from 40% to 35%; Latinx and Asian Pacific Islander clients remained stable; and a slightly higher proportion of clients declined to report their sexual orientation 15% in FY2024 vs. 13% in FY2023.

Program Successes:

Increase in the number of clients served:
• The total number of clients served increased slightly from 63 in FY2023, to 66 in FY2024.
• The number of new clients opened for ongoing services grew from 11 to 17, which reflected increased outreach and program engagement.

Higher Client Retention and Engagement:
• 67% of clients received 4 or more face-to-face outpatient visits per month, up from 60% in FY2023, which indicated stronger client participation. • 56% of clients had no service gap over 30 days, compared to 39% in the previous year, which demonstrated improved care continuity.

Changes in hospitalization follow-up rates:
• 7- day follow-up rates after hospitalization declined from 88% in FY2023 to 63% in FY2024.
• 30-day follow-up rates remained strong at 88%, though slightly lower than 100% in FY2023.

Reduction in Incarceration and Psychiatric Emergency Services:
• 80% of clients had a reduction in jail days, a major improvement from 53% in FY23.
• 100% of clients saw a reduction in psychiatric emergency services/inpatient/crisis stabilization use, up 77% from the previous year.

Greater Access to Primary Care:
• 83% of clients had a primary care visit, compared to 76% in FY2023, showing better overall health engagement.

High 30-Day Hospital Follow-Up Rate:
• 88% of clients had a follow-up visit within 30 days post-hospitalization, ensuring continuity of care.

Flex Funds Helped Address Client Needs:
• 129 instances of flex fund support were provided, mainly for food, housing, transportation, and hygiene needs.

Program Challenges:

Decline in 7-Day Hospitalization Follow-Up Rates:
• The 7-day follow-up rate after hospitalization dropped from 88% in FY2023 to 63% in FY2024, suggesting a need for improvement in early post-hospitalization engagement.

Maintaining Client Engagement for Some Populations:
• Despite improved overall service engagement, some clients continue to struggle with consistent participation.

Increased Financial Hardship Among Clients:
• High demand for flex funds, particularly for food (44 instances), transportation (36 instances), and housing (17 instances), reflected continued financial instability.

Limited Staff Resources for Growing Service Needs:
• With increasing client engagement and service demand, staff balanced meeting client needs with maintaining quality care.

Based on previous years, in FY2026 the projected number of individuals to be served per each age category is as follows: Children/Youth (0-15 years): 0; Transition Age Youth (16-25 years): 3; Adults (26-59 years): 12; Older Adults (60+ years): 41.

The RBA measures that were established for this FSP were as follows:

Process Measures
How much did we do?
Quality Measures
How well did we do it?
Impact Measures
Is Anyone Better off?
• # clients served
• # of new clients opened
for ongoing services
• A verage #
of days in
FSP per client
• Average # of service
hours per client per
month
• Average # of services
per client per month
• % of clients who have at
least completed one
CANS/ANSA for each six-
month period that they are
in the program
• % of clients and/or their
caregivers who receive an
average of four or more
face-to-face outpatient visits
per month
• % of clients with no se
rvice
gap of over 30 days
• % of discharges from
hospitalization or subacute
who had a follow up visit
with FSP staff within 7 and
within 30 calendar days
• #/% of clients closed, by
reason closed
• #/% of clients transferred to
another level of care
• % of clients who were satisfied
with services**
• % of clients who had a
reduction in jail days in the
last 12 months compared
to the 12 months before
enrollment
• % of clients who had a
reduction in psychiatric
emergency
services/inpatient/crisis
stabilization units in the last
12 months compared to the
12 months before enrollment
• %
of clients with a
decrease in
hospitalizations and
hospitalization day
s
• % of clients with a primary
care visit in the last 12
months
• % of clients who moved out of
homelessness**
*Demographic data was reported at the program level, where available **Data not available for baseline reporting period, will be included in future rounds of reporting

RBA Outcomes in FY2024 for this FSP are outlined on the following pages.

66 Clients Served
17 New Clients
Adult Full Service Partnership (AFSP)
BMH RBA Report FY 2024
Reporting Period July 2023 - June 2024
Process Outcomes ("How much did we do?")
Program Description: The Full-Service Partnership (FSP) team provides services to clients who are considered the highest need within our adult mental health service system. The FSP team is based on an Assertive Community Treatment (ACT) Model which involves low staff-to-client ratios at approximately 10:1 and a focus on providing care as a team rather than individual case load assignments. Services are primarily provided in the community rather than in an office setting.
<11 40-45 15-25
Transition Age
Youth (16-25)
Adult (26-59) Older Adult (60+)
Demographics (Age)
Jul '23- Jun '24 (n=66)
30-40 20-30 <11 <11 <11
Black or
African
American
White Asian or
Pacific
Islander
Hispanic
or Latino
Other
Demographics (Ethnicity)
Jul '23 - Jun '24 (n=66)
61%
39%
Ma
le Female
Demographics
(Gender Identity)
Jul '23 - Jun '24 (n=66)
82%
1 8%
Heterosexual
LGBQ+ or Other*
Demographic
(Sexual Orientation)
Jul '23 - Jun '24 (n=66)
*LGBQ+ includes individuals who identify as lesbian, gay, bisexual, questioning, o
r other diverse sexual orientations.

Other includes prefer not to answer, or unknown.

NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted and may not visually reflect actual counts. 27

Quality Outcomes ("How well did we do it?")
5 5
A
verage # of service hours
per client per month
Average # of services per
client per month
Average Monthly Services
per Client
Jul '23 - Jun '24 (n=66)
56% n=66
Clients with no
service gap of
over 30 days
67% n=66
Clients receive an
average of 4+
face-to-face
outpatient visits
per month
Clients Spend 4 years in
FSP on average
Service Consistency
63%
88%
7 days follow up 30 days follow up
Discharges from
hospitalization or subacute
who received FSP follow up
within 7 and 30 days
Jul '23 - Jun '24 (n=20)
Retention and Stability
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted and may not visually reflect actual counts. 28

Impact Outcomes ("Is anyone better off?")
Client Outcome Improvements
81%
86%
Hos
pitalizations Hospitalization days
Clients with a decrease in
hospitalizations/hospital days
Jul '23 - Jun '24 (n=20)
80-90% n<11
Clients who
had a
reduction in jail
83%n=48
Clients with a
Primary care visit
100% n<11
Client reduction in
psychiatric
emergency
services/inpatient/
crisis stabilization
units
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted and may not visually reflect actual counts. 29

Yellowfin
Yellowfin
Y
ellowfin
Yellowfin
Data Source
# of clients transferred to another
level of care
Of clients discharged in the reporting period, #
who were transferred to a full service partnership
program, service team, or outpatient services in
Alameda County within 90 days of discharge.

Measure
# clients served Total clients served
Definition
Yellowfin
Not presented due to
delays in the reporting
system
Yellowfin
Data Suppressed (n<11)
Yellowfin
Yellowfin
Yellowfin
# of new clients Clients who were not served by the program in the previous fiscal year
Maximum days each Level 1 client went without
service during their episode(s) in the reporting
period. Only considered clients open to a provider
for at least a total of three months during the
reporting fiscal year.
% of clients and/or their caregivers
who receive an average of four or
more face-to-face outpatient visits
per month
Clients must be been open to a provider for at
least 30 days in order to be included in this metric.

Phone contacts are included during the
pandemic. Days in subacute or jail not counted,
but services are counted.
% of clients with no service gap of
over 30 days
Average # of service hours per client
per month
Average of hours of service in a month divided by
clients served in a month. Includes all services
recorded for clients. Does not include medical
services (MAA)
Average # of services per client per
month
Average services in a month divided by clients
served in a month. Includes all services recorded
for clients. Note: more than one service can be
provided during a single contact. Does not include
MAA
% of discharges from hospitalization or
subacute who had a follow up visit
with FSP staff within 7 and within 30
calendar days
Follow-up rates for individuals open to Level 1
providers at the time of mental health hospital
discharge.
*note: clients used to calculate follow up rates
include those who didn’t receive outreach and
those who were lost to follow up (e.g. not
contactable, not responsive)
#/% of clients closed, by reason
closed
Discharge reason for clients discharged during the
reporting period
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted and may not visually reflect actual counts. 30

% of clients who have at least one
completed CANS/ANSA for each six-
month period that they are in the
program
Of clients with a completed Child or Adult Needs
and Strengths Assessment (CANS/ANSA), what
percentage of them had an assessment at least
every six months?
% of clients with a decrease in
hospitalizations/hospitalization days
Decrease in hospital days/admissions in the years
that a client was active in the program compared
to the year prior to program admission. Includes
clients who had at least one hospital day in the 12
months prior to admission and remained in the
program for at least 1 year. Only available for fiscal
years.
% of clients with a primary care visit
Of clients who completed 6 consecutive months
during the fiscal year, percentage who had an
appointment with a Anthem/Alliance/Community
Health Center Network (CHCN) primary care
provider during the fiscal year. Metric excludes
individuals with six or more months out of the
community (in Subacute, MH hospital, and/or jail).

Of clients who completed six consecutive months
during the 12-month fiscal year, percentage with a
reduction in psychiatric emergency services,
inpatient or crisis stabilization unit other than
Amber House, when comparing unduplicated days
from the 12 months prior to the fiscal year to the
current 12-month fiscal year. Excludes clients if out
of community (in jail and/or subacute) for six or
more months during the current fiscal year or the
prior fiscal year.
% of clients who had a reduction in
jail days
Of clients who completed six consecutive months
during the 12-month fiscal year, percentage with a
reduction in jail days, when comparing
unduplicated days from the 12 months prior to the
fiscal year to the current 12-month fiscal year.

Excludes clients if out of community (in hospital
and/or subacute) for six or more months during the
current fiscal year or the prior fiscal year.
% of clients who had a reduction in
psychiatric emergency
services/inpatient/crisis stabilization
units
Yellowfin
Yellowfin
Yellowfin
Yellowfin
No ANSA data is
available for FY24
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted and may not visually reflect actual counts. 31

Homeless Full-Service Partnership
The Homeless Full Services Partnership (HFSP) provides services to individuals primarily in the community, and in any temporary housing placement (e.g. shelter, unhoused encampment) who meet the following criteria:
● Adults (18 years and older);
● Unhoused and those at risk of being unhoused;
● Severe Mental Illness; and
● Significant impairments in functioning (e.g., frequent psychiatric hospital utilization, involvement in the criminal justice system, domestic violence survivors, trauma, severe co-occurring disorders).

The HFSP utilizes a team model for providing intensive treatment, meeting people up to several times per week. In FY2024, 47 individuals were served. Demographics on individuals served are as follows:

DEMOGRAPHICS N = 47*
*Numbers that are 11 or less are displayed as <11 and/or have been combined or masked to protect the privacy and confidentiality of individual participants.
● Age Category
25 – 44 years and Unknown – <11
45 – 64 years – 30
65 years and older – 15
● Gender Identity
Male - 34
Female - 13
● Race/Ethnicity
Asian Pacific Islander - <11
Black or African American - 26
Latino/a/x - <11
White – 18
Other - <11
● Sexual Orientation
Heterosexual - 34
Lesbian/Gay/Bisexual/Queer/Questioning or Unknown - 18
Flex funds are used to provide supports for HFSP program participants. During FY2024, 4 partners received rental and housing assistance; 20 received food and groceries; 28 partners received bus passes or transportation; 28 partners were provided with assistance with clothing/hygiene; and 4 partners were provided with other types of assistance.

Program Successes:

The HFSP program has demonstrated consistent growth and progress over the years.

The number of clients served has increased from 36 in FY2022 to 47 in FY2024, reflecting a steady rise in demand and capacity. This growth also reflects the program’s robust outreach and ability to meet community needs.

Client demographic trends show that the program effectively serves diverse populations, with notable increases in serving male clients (from 69% to 72%) and consistent engagement with Black or African American clients (remaining over 50% across all years). Additionally, the program has maintained a strong focus on service continuity, as evidenced by reduced service gaps over 30 days (maintained at 32% in the most recent year).

Noteworthy quality improvements included follow-up visits after discharges from hospitalization, with 50% of clients receiving timely follow-up care within both 7 and 30 days. Furthermore, impact measures indicated positive outcomes, including a 63% reduction in jail days and a 75% decrease in hospitalizations among clients, showcasing the program's effectiveness in stabilizing clients and reducing institutionalization.

The program’s ability to achieve consistent levels of client satisfaction, maintain high engagement in face-to-face visits, and facilitate primary care connections in FY2024 further highlighted its holistic approach to client wellness.

Program Challenges:

While the program had significant success in FY2024, there were also areas in need of improvement to enhance client care and operational efficiency. One challenge was maintaining a consistent number of new clients opened for ongoing services. After a high intake of 35 new clients in FY2023, the number declined to 13 in FY2024, suggesting potential barriers to new client engagement or referral processes. This could also be due to issues with vacancies in the team bandwidth. The program also experienced a gradual decline in the average number of service hours from 8 to 6 hours per client per month. This trend may reflect the staffing constraints, increased caseloads, or challenges in maintaining intensive service delivery, that were experienced during the reporting timeframe.

Another concern was the reason for client closures. Often times the closures were due to non-engagement. This highlighted an opportunity to implement clearer tracking and reporting processes to understand client withdrawal patterns better and identify trends for early intervention. Finally, while progress in reducing hospitalization days was commendable, sustaining and expanding these improvements require continued investment in preventive care, crisis response, and collaboration with community partners.

Based on previous years, in FY26 the projected number of individuals to be served per each age category is as follows: Children/Youth (0-15 years): 0; Transition Age Youth (16-25 years): 2; Adults (26-59 years): 43; Older Adults (60+ years): 6.

The RBA Measures that were established for this FSP were as follows:

Process Measures
How much did we do?
Quality Measures
How well did we do it?
Impact Measures
Is Anyone Better off?
• # of clients served
• # of new clients
opened for ongoing
services
• A
verage # of days in
FSP for client
• Average # of services
hours per client per
month
• A
verage # of services
per client per month
• % of clients who have at
least one completed
CANS/ANSA for each six-
month period that they are
in the program
• % of clients and/or their
caregivers who receive an
average of four or more
face-to-face outpatient
visits per month
• %
of discharges from
hospitalization who had a
follow up visit with HFSP
staff within 7 and within 30
calendar days
• % of clients with no se
rvice
gap of over 30 days
• #/% of clients closed, by
reason closed
• % of clients who were
satisfied with services**

• # of clients housed**
• # of clients who gained or
maintained housing since
enrollment**
• %
of clients who had a
reduction in jail days in the
last 12 months compared to
the 12 months before
enrollment
• % of clients with a primary
care visit in the last 12 months
• % of clients who had a
reduction in psychiatric care
emergency services/inpatient/
crisis stabilization units in the
last 12 months compared to
the 12 months before
enrollment
• %
of clients with a decrease in
hospitalizations/hospitalization
days
• % of clients with an increase
in the number of days in
community living compared to
12 month period before
enrollment**
*Demographic data was reported at the program level, where available **Data not available for baseline reporting period, will be included in future rounds of reporting RBA Outcomes in FY2024 for this FSP are outlined on the following pages.

47 Clients Served
13 New Clients
BMH RBA Report FY 2024
Reporting Period July 2023 - June 2024
Process Outcomes ("How much did we do?")
Homeless Full Service Partnership (HFSP)
Program Description: HFSP serves unhoused residents of Berkeley in an Assertive Community Treatment (ACT) model at high staff to client ratios, providing intensive case management and mental health services in a multi-disciplinary team approach. This team serves those with the highest level of need, supporting a population that is primarily unhoused and has multiple severe functional impairments. 35-45 <11
A
dult (26-59) Older Adult (60+)
Demographics (Age)
Jul '23 - Jun '24 (n=47)
25-30 15-20 < 11 <11 <11
Black or
African
American
White Asian or
Pacific
Islander
Hispanic or
Latino
Other
Demographics (Ethnicity)
Jul '23 - Jun '24 (n=47)
72%
28%
Ma
le Female
Demographics
(Gender Identity)
Jul '23 - Jun '24 (n=47)
72%
28%
H
eterosexual
LGBQ+ or Other*
Demographics
(Sexual Orientation)
Jul '23 - Jun '24 (n=47)
*LGBQ+ includes individuals who identify as lesbian, gay, bisexual, questioning, or other diverse sexual orientations.

Other includes prefer not to answer or
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted, and may not visually reflect actual counts. 35

Quality Outcomes ("How well did we do it?")
Service Consistency
Clients spend 1.9 years
in FSP on average
6 5
A
verage # of service hours
per client per month
Average # of services per
client per month
Average Monthly Services
per Client
Jul '23 - Jun '24 (n=47)
51% n=47
Clients receive an
average of 4+
face-to-face
outpatient visits per
month
32% n=47
Clients with no
service gap of
over 30 days
40-60% 40-60%
7 days follow up 30 days follow up
Discharges from
hospitalization or
subacute who received
FSP follow up within 7 and
30 days
Jul '23 - Jun '24 (n<11)
Retention and Stability
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted, and may not visually reflect actual counts. 36

Impact Outcomes ("Is anyone better off?")
Client Outcome Improvements
60-70%
80-90 %
Hospitalizations Hospitalization days
Clients with a decrease in
hospitalizations/hospital days
Jul '23 - Jun '24 (n<11)
63% n<11
Clients who had a
reduction in jail days
68%n=38
Clients with a Primary
care visit
71% n<11
Client reduction in
psychiatric
emergency
services/inpatient/
crisis stabilization
units
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted, and may not visually reflect actual counts. 37

Average # of service hours per client
per month
Average of hours of service in a month divided by
clients served in a month. Includes all services
recorded for clients. Does not include medical services (MAA)
Yellowfin
Average # of services per client per
month
Average services in a month divided by clients served
in a month. Includes all services recorded for clients.

Note: more than one service can be provided during a
single contact. Does not include MAA
Yellowfin
Discharge reason for clients discharged during the
reporting period
Yellowfin
*Not presented
due to delays in
the reporting
system
% of clients and/or their caregivers
who receive an average of four or
more face-to-face outpatient visits per
month
Clients must be been open to a provider for at least 30 days in order to be included in this metric. Phone
contacts are included during the pandemic. Days in
subacute or jail not counted, but services are counted.

Yellowfin
% of clients with no service gap of over
30 days
Maximum days each Level 1 client went without
service during their episode(s) in the reporting period.

Only considered clients open to a provider for at least a total of three months during the reporting fiscal year.

Yellowfin
% of discharges from hospitalization or
subacute who had a follow up visit
with FSP staff within 7 and within 30
calendar days
Follow-up rates for individuals open to Level 1 providers at the time of mental health hospital discharge.
*note: clients used to calculate follow up rates include those who didn’t receive outreach and those who
were lost to follow up (e.g. not contactable, not
responsive)
Yellowfin
#/% of clients closed, by reason closed
# clients served Total clients served Yellowfin
# of new clients opened for ongoing
services
Clients who were not served by the program in the
previous fiscal year Yellowfin
Measure Definition Data Source
# of clients transferred to another level
of care
Of clients discharged in the reporting period, # who
were transferred to a full service partnership program, service team, or outpatient services in Alameda
County within 90 days of discharge.

Yellowfin
Note: Data
Suppressed (<11
clients)
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted, and may not visually reflect actual counts. 38

% of clients who have at least one
completed CANS/ANSA for each six-
month period that they are in the
program
Of clients with a completed Child or Adult Needs and
Strengths Assessment (CANS/ANSA), what percentage
of them had an assessment at least every six months?
No data
available; ANSA
discontinued in
Alameda County
in FY24
% of clients who had a reduction in jail
days
Of clients who completed six consecutive months
during the 12-month fiscal year, percentage with a
reduction in jail days, when comparing unduplicated
days from the 12 months prior to the fiscal year to the current 12-month fiscal year. Excludes clients if out of community (in hospital and/or subacute) for six or
more months during the current fiscal year or the prior fiscal year.

Yellowfin
% of clients with a decrease in
hospitalizations/hospitalization days
Decrease in hospital days/admissions in the years that
a client was active in the program compared to the
year prior to program admission. Includes clients who
had at least one hospital day in the 12 months prior to admission and remained in the program for at least 1
year. Only available for fiscal years.

Yellowfin
% of clients with a primary care visit
Of clients who completed 6 consecutive months during
the fiscal year, percentage who had an appointment
with a Anthem/Alliance/Community Health Center
Network (CHCN) primary care provider during the fiscal
year. Metric excludes individuals with six or more
months out of the community (in Subacute, MH
hospital, and/or jail).

Yellowfin
% of clients who had a reduction in
psychiatric emergency
services/inpatient/crisis stabilization
units
Of clients who completed six consecutive months
during the 12-month fiscal year, percentage with a
reduction in psychiatric emergency services, inpatient or crisis stabilization unit other than Amber House, when comparing unduplicated days from the 12 months
prior to the fiscal year to the current 12-month fiscal year. Excludes clients if out of community (in jail
and/or subacute) for six or more months during the
current fiscal year or the prior fiscal year.

Yellowfin
NOTE: Due to privacy protections, data representing fewer than 11 individuals have been combined, masked, suppressed, or reported in ranges. The graphs have been adjusted, and may not visually reflect actual counts. 39

Multicultural Outreach and Engagement
Diversity & Multicultural Services
The Diversity & Multicultural Coordinator (DMC) provides leadership in identifying, developing, implementing, monitoring, and evaluating services and strategies that lead to continuous cultural, ethnic, and linguistic improvements within the organization’s system of care, with a special emphasis on unserved, underserved, inappropriately served, and emerging populations. The DMC also collaborates with the state, regional counties, other city divisions, local agencies, and community groups in order to address mental health inequities and disparities for targeted populations and communities, and the community-at-large in Berkeley.

The Diversity & Multicultural Coordinator accomplishes these goals by:
● Providing cultural humility competency training to all behavioral health, community partners, and all stakeholders in Berkeley and other geographic locations in the region as a collaborative partner
● Performing outreach and engagement to unserved, underserved, inappropriately served and emerging communities and populations
● Developing long and short-term goals and objectives to promote cultural/ethnic and linguistic competency within the system of care
● Developing an annual training plan and budget
● Chairing the agency’s Diversity and Multicultural Committee ● Attending continuous trainings in the areas of cultural competency ● Monitoring Interpreter and Translation Services for the agency ● Collaborating with State, Regional, County, and local groups and organizations, and
● Developing and updating BMH’s Cultural Humility Competency Plan as needed.

In FY2024, this position was filled for a short period of time. As such, there is no data available during the reporting timeframe.

Transition Age Youth (TAY) Support Services
The Transition Age Youth (TAY) Support Services program provides outreach, services, supports, and/or referrals to TAY with serious mental health issues who are homeless or marginally housed and not currently receiving services. Priority is given to youth coming out of foster care and/or the juvenile justice system and particular outreach strategies are utilized to engage youth from various ethnic communities, including African Americans, Asian and Latino/a/x populations, among others. Program services include: Culturally appropriate outreach and engagement; peer counseling and support; assessment; individual and group therapy; family education; case management, coaching, ancillary program referrals and linkages. Also provided are services in housing attainment and retention, financial management, employment, schooling, and community involvement. Services are designed to be culturally relevant, tailored to each individual’s needs, and delivered in multiple, flexible environments. The main goals of the program are to increase outreach, treatment services, and supports for