Beverly Hills City Council
July 25, 2022

AGENDA REPORT
Meeting Date: July 25, 2022
Item Number: C-1
To: Honorable Mayor and City Council
From: Nancy Hunt-Coffey, Assistant City Manager
Subject: REQUEST BY MAYOR BOSSE TO DISCUSS THE PROPOSED

LOS ANGELES COUNTY DEPARTMENT OF HEALTH ORDER

REGARDING INDOOR MASKING THAT MAY COMMENCE ON
JULY 29, 2022
Attachments: 1. Los Angeles Times article, “Indoor mask rules expected next week as L.A. coronavirus wave worsens”, July 21, 2022

2. Science Advances article, “Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience”, December 2, 2021

3. Annals of Internal Medicine article, “Effectiveness of Adding a Mask Recommendation to Other Public Health Measures
to Prevent SARS-CoV-2 Infection in Danish Mask Wearers:
a Randomized Controlled Trial”, March 2021

RECOMMENDATION
Mayor Bosse requests that the City Council discuss and provide any direction regarding the health order from the Los Angeles County Department of Health (LACDPH) about indoor masking that may commence on July 29, 2022.

INTRODUCTION
On July 21, 2022, the LACDPH announced that for the second week in a row the number of COVID cases and the number of COVID related hospitalizations have pushed the county into the “high” level. Unless the hospitalization rate decreases by Thursday July 28, 2022, a new mask order will likely go into effect on Friday July 29, 2022. Mayor Bosse requested this special meeting of the City Council to provide any related direction should the mask order go into effect on July 29th.

DISCUSSION
The Center for Disease Control (CDC) has established the concept of “community level” which uses various criteria to help counties determine the prevention steps to be taken based on the COVID-19 levels in an area. The three different community levels are low, Meeting Date: July 25, 2022

medium and high, and the recommended steps that should be taken at each level are listed in the table below:

Reference: https://www.cdc.gov/coronavirus/2019-ncov/your-health/covid-by-county.html The CDC looks at a combination of metrics to determine the community level.

One of the following:

1. The number of new COVID-19 admissions to health care facilities per 100,000 population in the past 7 days. For Los Angeles the “high” level is greater than or equal to 10 per 100,000 people. The level as of July 21, 2022 is 11.4.

2. The percent of staffed inpatient beds occupied by COVID-19 patients. For Los Angeles the “high” level is greater than or equal to 10 per 100,000 people. The level as of July 21, 2022 is 7.1.

AND

1. The total new COVID-19 cases per 100,000 population in the past 7 days. For Los Angeles the “high” level is greater than or equal to 200 per 100,000 people.

The level as of July 21, 2022 is 481 cases per 100,000 people.

Per the CDC: New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

On July 21, 2022, LACDPH announced that for the second week in a row the number of COVID cases and the number of COVID related hospitalizations have pushed the county into the “high” level. As noted above, the number of cases is generally a leading indicator of subsequent increases in the hospitalization rate. Unless the hospitalization rate decreases below 10 per 100,000 by Thursday July 28, 2022, LACDPH has indicated that a new mask order will go into effect on Friday July 29, 2022. In a telebriefing on July 21, 2022 LACDPH indicated that the county could postpone issuing a health order related to indoor masking if the number COVID cases slows substantially; however, no further details were given on this possibility.

Meeting Date: July 25, 2022

Based on telebriefings, other communications and past health orders from LACDPH, it is expected that a mask mandate would apply indoors to anyone age 2 or older at facilities such as shared office space, manufacturing and retail settings, event spaces, restaurants and bars, gyms and yoga studios, educational settings and children’s programs. Under the possible health order, businesses would be required to offer employees masks and notify them of mask-wearing requirements. Additionally, businesses would be obligated to put up signage letting customers know about indoor masking. Should a masking order be implemented, it would be in effect until the County experienced at least two weeks at the “medium” community level.

It should be noted that there have been numerous studies over the last few years on the effectiveness of masking against the spread of covid-19. Most studies, including one conducted by a number of leading university researchers on a randomized trial in rural Bangladesh (attached to this report) as well as a study earlier this year on California residents1 have demonstrated the efficacy of face coverings, particularly with N95/KN95 masks, against the spread of the COVID-19 virus. There have also been a small number of studies which call into question the reported efficacy levels of masks. For example, a study conducted in 2021 by researchers from the University of Copenhagen (attached) found:
“In this community-based, randomized controlled trial conducted in a setting where mask wearing was uncommon and was not among other recommended public health measures related to COVID-19, a recommendation to wear a surgical mask when outside the home among others did not reduce, at conventional levels of statistical significance, incident SARS-CoV-2 infection compared with no mask recommendation…”
However, the researchers cautioned that the findings from the study:
“…should not be used to conclude that a recommendation for everyone to wear masks in the community would not be effective in reducing SARS-CoV-2 infections, because the trial did not test the role of masks in source control of SARS-CoV-2 infection.”
LACDPH is currently the public health agency for the City of Beverly Hills. However, as the City Council is aware, staff is researching the requirements for the City to form its own health department. A report on these findings will be brought to the City Council in August. As a result, the City and its businesses are subject to the health orders issued by LACDPH at this time. LACDPH has stated that they will work with different business sectors to provide education on their obligations should a new mask mandate go into effect. LACDPH also has the ability to enforce health orders, generally through warnings and citations that are issued through visits to businesses. LACDPH recently reported that less than 1% of the businesses in the county have received citations.

When prior mask orders came from LACDPH, the City provided substantial additional resources related to education and enforcement. For example, a number of City staff in the following classifications were heavily involved in regularly enforcing mask mandates and other COVID violations (e.g. ensuring proper distancing between tables at restaurants):
1 Andrejko KL, Pry JM, Myers JF, et al. Effectiveness of Face Mask or Respirator Use in Indoor Public Settings for Prevention of SARS-CoV-2 Infection — California, February–December 2021. MMWR Morb Mortal Wkly Rep 2022;71:212–216. DOI: http://dx.doi.org/10.15585/mmwr.mm7106e1 Meeting Date: July 25, 2022

• Full-Time:
o Code Enforcement Officer
o Lead Park Ranger
o Environmental Compliance Inspector
o Building Inspector
o Senior Code Enforcement Officer
o Senior Building Inspector
o Park Ranger Supervisor
• Part-Time
o Park Ranger
While some overtime was offered to individuals in these classifications for COVID health order enforcement, generally this work was done by existing City employees during their regular work hours. As a result, some of the regular job duties that these employees would have carried out were paused while enforcement of COVID regulations took place. For example, a code enforcement officer who would normally be called out to investigate a report of illegal construction might instead be assigned to mask enforcement.

To provide some context for previous health order enforcement, between July 2020 and June 2021, the following activities were conducted by City staff related to COVID-19 health order compliance:

Code Enforcement and Public Works:

Total contacts 18,347
No-Mask Compliance Achieved 15,599
Citations issued 432 (154 related to no-mask)
Police Department
Total contacts 3,441
No-Mask Compliance Achieved 3,247
Citations issued 7 (7 related to no-mask)
Rangers
Total contacts 7,463
No-Mask Compliance Achieved 6,674
Citations issued 25 (22 related to no-mask)
Ambassadors
Total contacts 25,372
No-Mask Compliance Achieved 8,058
Citations issued N/A
City Council is asked to provide direction to staff related to the health order that may go into effect on July 29, 2022 particularly related to the level of education and enforcement that City staff should conduct.

Meeting Date: July 25, 2022

FISCAL IMPACT
The fiscal impact resulting from a possible COVID health order will depend on the level of education and enforcement that City Council directs staff to engage in.

Nancy Hunt-Coffey
Approved By
Attachment
1 7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 1/16

CALIFORNIA
Indoor mask rules expected next week as L.A. coronavirus wave worsens

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Latest: COVID-19 Virus tracker Hospitalizations Vaccines Newsletter 7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 2/16 Hesta Prynn and 7-year-old daughter Zoe shop at Grand Central Market in Los Angeles. Indoor masking in public settings could return to Los Angeles County in a week. (Francine Orr / Los Angeles Times)

BY LUKE MONEY, RONG-GONG LIN II
JULY 21, 2022 UPDATED 6:10 PM PT
Los Angeles County is poised to impose new indoor mask rules next week as data show the hyper-infectious BA.5 Omicron subvariant is pushing coronavirus case counts higher and sending increasing numbers of people to the hospital.

A new mask mandate would mark a significant escalation in the response to the new subvariants, which have fueled a spring-and-summer surge and can cause people to quickly be reinfected with the coronavirus. L.A. County would be the first county in Southern California to bring back masks this year, and it remains unclear whether other areas would join. Alameda County issued a mask mandate June 3 and rescinded it three weeks later.
7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 3/16 Although a final decision is still days away, the likelihood of a mask rule has sparked growing debate in a society weary of both the pandemic and its restrictions.

Proponents say the move is an effective and low-impact way to help stymie soaring coronavirus transmission. L.A. County — the nation’s most populous — is like no other county in California. With its higher rate of poverty and overcrowded housing, it has been hit harder than most parts of the state.
“Of all the tools we have used in this pandemic to counter the spread of COVID, indoor masking is one of the simplest, and turns out to be very effective,” county Public Health Director Barbara Ferrer said Thursday.

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7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 4/16 Still, critics are questioning the need. Hospitals and intensive care units are nowhere near as strained as during the peaks of previous surges and, thanks in part to vaccinations and anti-COVID drugs, the relative overall risk of severe illness is far less than it was a year or two ago.

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Some business groups have also voiced concerns that the mask order could prompt shoppers to take their money elsewhere, or that workers will have to enforce rules many no longer want to follow.

A renewed mandate would apply indoors for anyone age 2 or older at a host of establishments and venues, including shared office space, manufacturing and retail settings, event spaces, restaurants and bars, gyms and yoga studios, educational settings and children’s programs.

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7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 5/16 L.A. County officials long ago set the criteria for this health order revision — saying they would reissue a mask mandate should the region move into the “high” COVID-19 community level, as defined by the U.S. Centers for Disease Control and Prevention, and remain there for two consecutive weeks.

To be in that category, a county must record elevated levels of coronavirus spread as well as at least 10 new weekly coronavirus-positive hospitalizations for every 100,000 residents. L.A. County exceeded that threshold last week and did so again Thursday, recording 11.4 weekly hospitalizations for every 100,000 people. The rate was 10.5 a week ago.

Unless the hospitalization rate drops below 10 next week, a new mask order would go into effect July 29.

Tracking the coronavirus in L.A. County
Ferrer said she hopes L.A. County doesn’t get to that point and that any mandate is short-lived. If issued, a masking order would be lifted when the county exits the high community level and stays out of that category for two consecutive weeks. “It isn’t going to take much to move us back into that ‘medium’ community level if we can get our case numbers to go lower,” she said.

In a new development, Ferrer said Thursday that the county could hold off on a mandate if transmission shows pronounced signs of slowing — as tumbling case counts will lead to corresponding decreases in hospitalizations a week or two later. “Should we start seeing a steep decline in our [case] numbers next week — because we know that hospitalizations are this lagging indicator — we are likely to want to take a 7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 6/16 pause on moving too quickly on universal indoor masking,” she said.

The likelihood of that scenario is unclear, however. L.A. County on Thursday reported nearly 8,700 new cases — one of the highest single-day totals of the current wave.

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Countywide, 1,329 coronavirus-positive patients were hospitalized as of Wednesday — a 34% increase from two weeks ago.

By comparison, the statewide patient count has climbed 23% over that period, to 4,762.

In both L.A. County and California as a whole, hospitalizations remain well below those during prior peaks. And officials note a significant share of those patients — about 57% in L.A. County — are not receiving treatment for COVID-19 but incidentally tested positive on admission for other reasons.

However, a vast majority of coronavirus-positive people in intensive care units — about 71% — are being treated for COVID-19, Ferrer said.

As of Thursday, L.A. County was reporting 6,753 coronavirus cases a day for the past week, up 5% from the prior week and nearly double the peak from last summer’s Delta surge. However, this increase was notably flatter than a week ago, when there was a 25% jump.

On a per capita basis, L.A. County is recording 468 cases a week for every 100,000 residents. A rate of 100 or more is considered high.
7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 7/16 That the patient count, while rising, has remained relatively low in the face of high transmission is a testament to how the pandemic has changed.

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Most of those getting infected now are not falling seriously ill, a trend that officials and experts credit to robust vaccine coverage and ready availability of treatments.

Some have pointed to this disconnect as evidence against imposing a new mask mandate. If hospitals aren’t anywhere close to being overwhelmed, what’s the justification?
“We’re in a much better place, and people should enjoy their lives,” Ferrer said. But there are a number of worrisome signs about the latest surge that would warrant a mask requirement next week unless conditions improve, she said.

The percent of emergency room visits related to COVID-19 has doubled since Memorial Day, from 5% to 10%. Worksites are seeing major disruptions, and some are short on staffing. L.A. County reported 429 worksites with clusters of coronavirus cases per week, more than double from the start of June. There were 33 nursing homes in the last week with newly reported outbreaks, a figure that has doubled over the same period. “High community transmission also leads to preventable and avoidable deaths, primarily among those most vulnerable,” Ferrer said. “If we can slow down transmission, we have a good chance of preventing some people from dying in the upcoming months.”
7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 8/16 COVID-19 deaths remain elevated. L.A. County has been reporting 86 to 100 deaths a week, up from about 50 a week.

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Some may be confident they won’t be seriously harmed when getting COVID-19, but there is still uncertainty around who will experience a serious illness. Some patterns are still holding: Hospitalization rates have grown much faster in recent weeks for older residents.
“When people pass along misinformation that the current COVID surge is not affecting or hurting anyone, these are the people they are dismissing: our elders,” Ferrer said.

It’s also important to reduce the number of people who could otherwise develop long COVID, she said, in which symptoms of fatigue, brain fog and difficulty breathing can persist for months or years and can be so debilitating that people can no longer work.

Reinfections also add risk: One study of mostly white veterans, who were on average in their early 60s — who were infected with the coronavirus more than once — had a two times higher risk of death and 2½ times higher risk of developing heart or lung disease or problems with blood vessels and blood clotting, compared to those who were infected once.

And a high level of coronavirus transmission only increases the risk of new mutations that could cause more harm.
“It’s very attractive to minimize what in fact is happening now … and I think that’s a mistake,” Ferrer said. She said requiring masks when hospitalization rates rise is a “nice middle ground.”
7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 9/16 “I know people are sort of saying, putting masks on is really asking a lot of folks. We asked a lot more of everybody — for a much longer time — for much of the past two years,” Ferrer said.

Some critics don’t see the justification.
“For two years straight, Californians wore masks inside. They got vaccinated at high rates. Many got boosted. The rates of severe disease are so decoupled from hospitalizations, and that’s so obvious to the public,” said Dr. Monica Gandhi, an infectious-disease expert at UC San Francisco.

That’s been the experience at the Los Angeles County-USC Medical Center, the largest of four county-run public hospitals. During an internal town hall last week that was posted online, Chief Medical Officer Dr. Brad Spellberg said about 90% of the hospital’s coronavirus-positive patients were admitted for other issues and “virtually none of them go to the ICU.”
The number of COVID-19 deaths in the last 6 ½ months in L.A. County — nearly 4,500 — far exceeds the death toll the county typically saw from the flu in an entire prepandemic year, about 1,500.

The CDC recommends public indoor masking for counties in the “high” community level. As of Thursday, that included 50 of California’s 58 counties, home to a combined

38.6 million people. Riverside and San Bernardino counties entered the high COVID-19 community level Thursday for the first time since spring.

But L.A. County stands alone in pursuing a renewed mask order. When asked about differing approaches, Ferrer pointed to factors that have left L.A. particularly vulnerable, including its size and population of 10 million, 2 million of whom remain unvaccinated.
7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 10/16 The county is also home to many older residents generally at higher risk of severe health outcomes from COVID-19, as well as nursing homes and industrial work settings where transmission can be particularly problematic.

Data also continue to show that COVID-19 is taking a disproportionate toll on Black and Latino residents, as well as people living in poorer areas of L.A. County. “Getting transmission levels down low benefits everybody, but it particularly reduces risks for those most vulnerable,” Ferrer said.

While universal mask orders have been off the books for months, many officials have continually urged the use of face coverings in indoor public places. The California Department of Public Health strongly recommends the practice.

As anyone who’s out and about can attest, though, many Californians are not heeding that call. That’s led some to question who exactly would enforce a new L.A. County order and what sort of compliance can be expected.

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Should the mandate go into effect, Ferrer said her department will remind businesses that they’re obligated to offer employees masks and notify them of the mask-wearing requirement.
“Businesses are required to put up signage so that those coming in — as customers or as visitors — know that there is in fact universal indoor masking at their sites,” Ferrer said. 7/22/22, 1:16 PM L.A. County COVID mask mandate expected next week - Los Angeles Times https://www.latimes.com/california/story/2022-07-21/l-a-county-mask-mandate-likely-a-week-away 11/16 She said the county will not ask businesses “to be enforcers” of the mandate and said, “we understand, as there has been throughout the pandemic, that there are some people who will go ahead and … not be in compliance.”
But she said she hopes most people will wear masks at businesses that have good signage.
“I think we’re tired of this, and masks have come to symbolize lots of other things that we really would like to put aside,” Ferrer said. “I would urge people to think of your mask as an act of kindness, respect and consideration for others, and help us get back to slowing the spread, which is what will benefit everybody.” Times staff writer Hailey Branson-Potts contributed to this report.

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2 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 1/28

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HOME  SCIENCE  VOL. 375, NO. 6577  IMPACT OF COMMUNITY MASKING ON COVID-19: A CLUSTER-RANDOMIZED TRIAL IN BANGLADESH  | RESEARCH ARTICLE | CORONAVIRUS     󡀆 
Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh
, , , , , , , , ,
[...]  +13 authors Authors Info & Affiliations
Persuading people to mask
Even in places where it is obligatory, people tend to optimistically overstate their compliance for mask wearing. How then can we persuade more of the population at large to act for the greater good? Abaluck et al. undertook a large, cluster-randomized trial in Bangladesh involving hundreds of thousands of people (although mostly men) over a 2-month period. Colored masks of various construction were handed out free of charge, accompanied by a range of mask-wearing promotional activities inspired by marketing research. Using a grassroots network of volunteers to help conduct the study and gather data, the authors discovered that mask wearing averaged 13.3% in villages where no interventions took place but increased to 42.3% in villages where inperson interventions were introduced. Villages where in-person reinforcement of mask wearing occurred also showed a reduction in reporting COVID-like illness, particularly in high-risk individuals. —CA Structured Abstract

INTRODUCTION
Mask usage remains low across many parts of the world during the COVID-19 pandemic, and strategies to increase mask-wearing remain untested. Our objectives were to identify strategies that can persistently increase mask-wearing and assess the impact of increasing mask-wearing on symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections.

RATIONALE
We conducted a cluster-randomized trial of community-level mask promotion in rural Bangladesh from November 2020 to April 2021 (N = 600 villages, N = 342,183 adults). We cross-randomized mask promotion strategies at the village and household level, including cloth versus surgical masks. All intervention arms received free masks, information on the importance of masking, role modeling by community leaders, and inperson reminders for 8 weeks. The control group did not receive any interventions. Participants and surveillance staff were not informed of treatment assignments, but project materials were clearly visible. Outcomes included symptomatic SARS-CoV-2 seroprevalence (primary) and prevalence of proper mask-wearing, physical JASON ABALUCK LAURA H. KWONG ASHLEY STYCZYNSKI ASHRAFUL HAQUE MD. ALAMGIR KABIR ELLEN BATES-JEFFERYS EMILY CRAWFORD JADE BENJAMIN-CHUNG SHABIB RAIHAN

AHMED MUSHFIQ MOBARAK
SCIENCE 2 Dec 2021 Vol 375, Issue 6577 DOI: 10.1126/science.abi9069 104,761 1    
       
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7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 2/28 distancing, social distancing, and symptoms consistent with COVID-19 illness (secondary). Mask-wearing and distancing were assessed through direct observation at least weekly at mosques, markets, the main entrance roads to villages, and tea stalls. Individuals were coded as physically distanced if they were at least one arm’s length from the nearest adult; social distancing was measured using the total number of adults observed in public areas. At 5- and 9-week follow-ups, we surveyed all reachable participants about COVID-19–related symptoms. Blood samples collected at 10- to 12-week follow-ups for symptomatic individuals were analyzed for SARS-CoV-2 immunoglobulin G (IgG) antibodies.

RESULTS
There were 178,322 individuals in the intervention group and 163,861 individuals in the control group. The intervention increased proper mask-wearing from 13.3% in control villages (N = 806,547 observations) to 42.3% in treatment villages (N = 797,715 observations) (adjusted percentage point difference = 0.29; 95% confidence interval = [0.26, 0.31]). This tripling of mask usage was sustained during the intervention period and for 2 weeks after. Physical distancing increased from 24.1% in control villages to 29.2% in treatment villages (adjusted percentage point difference = 0.05 [0.04, 0.06]). We saw no change in social distancing. After 5 months, the impact of the intervention on mask-wearing waned, but mask-wearing remained 10 percentage points higher in the intervention group. Beyond the core intervention of free distribution and promotion at households, mosques, and markets; leader endorsements; and periodic monitoring and reminders, several elements had no additional effect on mask-wearing, including text reminders, public signage commitments, monetary or nonmonetary incentives, and altruistic messaging or verbal commitments.

The proportion of individuals with COVID-19–like symptoms was 7.63% (N = 12,784) in the intervention arm and 8.60% (N = 13,287) in the control arm, an estimated 11.6% reduction after controlling for baseline covariates. Blood samples were collected from consenting, symptomatic adults (N = 10,790). Adjusting for baseline covariates, the intervention reduced symptomatic seroprevalence by 9.5% (adjusted prevalence ratio = 0.91 [0.82, 1.00]; control prevalence = 0.76%; treatment prevalence = 0.68%). We find that surgical masks are particularly effective in reducing symptomatic seroprevalence of SARS-CoV-2. In villages randomized to surgical masks (N = 200), the relative reduction was 11.1% overall (adjusted prevalence ratio = 0.89 [0.78, 1.00]). The effect of the intervention is most concentrated among the elderly population; in surgical mask villages, we observe a 35.3% reduction in symptomatic seroprevalence among individuals ≥60 years old (adjusted prevalence ratio = 0.65 [0.45, 0.85]). We see larger reductions in symptoms and symptomatic seropositivity in villages that experienced larger increases in mask use. No adverse events were reported.

CONCLUSION
A randomized-trial of community-level mask promotion in rural Bangladesh during the COVID-19 pandemic shows that the intervention increased mask usage and reduced symptomatic SARS-CoV-2 infections, demonstrating that promoting community mask-wearing can improve public health.

Impact of intervention on mask use and biological outcomes. 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 3/28 Abstract
We conducted a cluster-randomized trial to measure the effect of community-level mask distribution and promotion on symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in rural Bangladesh from November 2020 to April 2021 (N = 600 villages, N = 342,183 adults). We cross-randomized mask type (cloth versus surgical) and promotion strategies at the village and household level. Proper maskwearing increased from 13.3% in the control group to 42.3% in the intervention arm (adjusted percentage point difference = 0.29; 95% confidence interval = [0.26, 0.31]). The intervention reduced symptomatic seroprevalence (adjusted prevalence ratio = 0.91 [0.82, 1.00]), especially among adults ≥60 years old in villages where surgical masks were distributed (adjusted prevalence ratio = 0.65 [0.45, 0.85]). Mask distribution with promotion was a scalable and effective method to reduce symptomatic SARS-CoV-2 infections.

As of September 2021, the COVID-19 pandemic has taken the lives of more than 4.7 million people. Inspired by the growing body of scientific evidence that face masks have the potential to slow the spread of the disease and save lives (1–10), we conducted a cluster-randomized controlled trial covering 342,183 adults in 600 villages in rural Bangladesh with the dual goals of (i) identifying strategies to increase community-wide mask-wearing and (ii) tracking changes in symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections as a result of our intervention. Although vaccines may constrain the spread of SARS-CoV-2 in the long-term, it is unlikely that a substantial fraction of the population in low- and middle-income countries will have access to vaccines before the end of 2021 (11). Developing scalable and effective means of combating COVID-19 is thus of firstorder policy importance.

The World Health Organization (WHO) declined to recommend mask adoption until June 2020, citing the lack of evidence from community-based randomized-controlled trials as well as concerns that mask-wearing would create a false sense of security (12). Critics argued that those who wore masks would engage in compensating behaviors, such as failing to physically distance from others, resulting in a net increase in transmission (13). We directly test this hypothesis by measuring physical distancing.

We designed our trial to encourage universal mask-wearing at the community level, rather than mask-wearing among only those with symptoms. We encouraged even healthy individuals to wear masks because a substantial share of COVID-19 transmission stems from asymptomatic or presymptomatic individuals (14) and masks may protect healthy wearers by reducing the inhalation of aerosols or droplets (15–17).

After performing pilot studies, we settled on a core intervention package that combined household mask distribution with communication about the value of mask-wearing; mask promotion and in-person reminders at mosques, markets, and other public places; and role-modeling by public officials and community leaders. We also tested several other strategies in subsamples, such as asking people to make a verbal commitment, creating opportunities for social signaling, text messaging, and providing village-level incentives to increase mask-wearing. The selection of strategies to test was informed by both our pilot study results and research in public health, psychology (18–20), economics (21–23), marketing (24–26), and other social sciences (27) on product promotion and dissemination strategies. We tested many different strategies because it was difficult to predict in advance which ones would lead to persistent increases in mask-wearing. Prediction studies we conducted with policy-makers and public health experts at the WHO, India’s National Council of Applied Economic Research, and the World Bank suggested that even these experts with influence over policy design could not easily predict which specific strategies would prove most effective in our trial.

The figure shows the raw means of mask-wearing (left), COVID-19 symptoms (middle), and symptomatic seropositivity (right) in the control and treatment arms. The estimated change in each outcome, confidence intervals, and p values adjust for preregistered covariates (and thus are not computable from the raw values). Individuals who were symptomatic but did not consent to blood collection were dropped from the sample; measured symptomatic seropositivity thus understates the true fraction of the population that was symptomatic seropositive. 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 4/28 We powered our intervention around the primary outcome of symptomatic seroprevalence. During our study, we collected survey data on the prevalence of WHO-defined COVID-19 symptoms from all available study participants and then collected blood samples at endline from those who reported symptoms at any time during the 8-week study. Our trial is therefore designed to track the fraction of individuals who are both symptomatic and seropositive. We chose this as our primary outcome because (i) the goal of public health policy is ultimately to prevent symptomatic infections (even if preventing asymptomatic infections is instrumentally important in achieving that goal) and (ii) symptomatic individuals are far more likely to be seropositive so powering for this outcome required conducting an order of magnitude fewer costly blood tests. As secondary outcomes, we also report the effects of our intervention on WHO-defined symptoms for probable COVID-19 infection and mask-wearing.

Bangladesh is a densely populated country with 165 million inhabitants; reported infections reached 15,000 per day during our study period, but reported cases and deaths are likely underestimated by one to two orders of magnitude (28–32). The evolution of mask use over time in Bangladesh is discussed in greater detail in (33). In Bangladesh, the government strongly recommended mask use from early April 2020. In an April 2020 telephone survey, more than 80% of respondents self-reported wearing a mask and 97% self-reported owning a mask. The Bangladeshi government formally mandated mask use in late May 2020 and threatened to fine those who did not comply, although enforcement was weak to nonexistent, especially in rural areas. During in-person surveillance between 21 and 25 May 2020 in 1441 places in 52 districts, we observed 51% of about 152,000 individuals wearing a mask. Another wave of surveillance was conducted between 19 and 22 June 2020 in the same 1441 locations, and mask-wearing dropped to 26%, with 20% wearing masks that covered their mouth and nose and 6% wearing masks improperly. An August 2020 phone survey in rural Kenya found that although 88% of respondents claim to wear masks in public, direct observation revealed that only 10% actually did (34). These observations suggest that mask promotion interventions could be useful in rural areas of low- and middle-income countries, which are home to several billion people at risk for COVID-19.

Results
Our analysis followed our preregistered analysis plan (https://osf.io/vzdh6/) except where indicated. Our primary outcome was symptomatic seroprevalence for SARS-CoV-2. We also analyzed the impact of our intervention on mask-wearing, physical distancing, social distancing, and COVID-19–like symptoms. No adverse events were reported during the study period.

Sample selection
The unions where we conducted our intervention are geographically dispersed throughout rural Bangladesh, as shown in Fig. 1. (Appendix C discusses in more detail how these unions were selected.) Tables S1 and S2 summarize sample selection for our analysis. We initially approved 134,050 households, of which 125,053 provided baseline information. From these 125,053 households, we collected baseline information from 342,183 individuals. Of these, 336,010 (98%) provided symptom data at week 5 and/or 9. Of these, 27,160 (8.0%) reported COVID-19–like symptoms during the 9 weeks since the study began. We attempted to collect blood samples from all symptomatic individuals. Of these, 10,790 (39.7%) consented to have blood collected (40.2% in the treatment group and 39.3% in the control group; p = 0.24). We show in table S3 that consent rates are about 40% across men and women and among adults of different age groups in both treatment and control villages.

As such, the sample of individuals for whom we have symptom data is much larger than the sample for whom we have serology data. We tested 9512 (88.2%) of the collected blood samples to determine seroprevalence for SARSCoV-2 immunoglobulin G (IgG) antibodies. Untested samples (<12%) either lacked sufficient quantity for our test or could not be matched to individuals from our sample because of a barcode scanning error. In our primary outcome analysis, we drop individuals for whom we are missing symptom data or who did not consent to blood sample collection. For the analyses where symptomatic status is the outcome, we report results using both this smaller sample as well as the larger sample of all individuals who provided symptom data. In the baseline, we collected blood samples from a random sample of individuals (N = 10,085), of whom 339 had COVID-19–like symptoms. We use these to check balance with respect to baseline symptomatic seropositivity (as well as baseline symptomatic status).
7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 5/28 Of the 600 villages initially recruited for the study, the analysis sample excludes four villages where interventions could not be performed owing to a lack of local government cooperation. We exclude an additional 11 villages and their village-pairs (where a village and its village-pair are a control-treatment pair) because we did not observe them in the baseline period before the intervention and one village and its pair for lack of observational data throughout the intervention period, for a total analysis sample of 572 villages.

Primary analyses
Our primary outcomes are balanced at baseline
Although our stratification procedure should have achieved balance with respect to variables observed at the time of randomization, given the many possible opportunities for errors in implementation, we confirm in appendix L that our control and treatment villages are balanced with respect to our primary outcome variables. This assessment was not preregistered. We investigated several other covariates and found a few small imbalances. We checked whether these affect the main results that we report in this paper. For example, we found more 18- to 30- year-olds in the treatment group than in the control group, perhaps because households reported teenagers as 18 years old to receive more masks; our results are robust to dropping this age range.

Our intervention increased mask-wearing
The first column in the top panel of Table 1 reports coefficients from a regression of mask-wearing on a constant, an intervention indicator (based on the assigned groups), baseline mask-wearing, the baseline symptom rate, and indicators for each control-intervention pair. More details of our statistical methods and standard error construction are available in appendix K. Mask-wearing was 13.3% in control villages and 42.3% in treatment villages. Our regression adjusted estimate is an increase of 28.8 percentage points (95% confidence interval = [0.26, 0.31]; numbers in brackets represent 95% confidence intervals throughout the text and tables). If we omit all covariates (except fixed effects for the strata within which we randomized), our point estimate is identical (table S5).

Considering only surveillance conducted when no mask distribution was taking place, mask-wearing increased 27.9 percentage points, from 13.4% in control villages to 41.3% in intervention villages (regression adjusted estimate =

0.28 [0.26, 0.30]). We also run our analysis separately in mosques, markets, and other locations such as tea stalls, the entrance of restaurants, and the main road in the village. The increase in mask-wearing was largest in mosques (37.0 percentage points), whereas in all other locations it was 25 to 29 percentage points.

Parameter Full
No active
promotion Mosques Markets
Other
locations
Surgical mask
villages
Cloth mask
villages
Proper mask-wearing
Intervention coefficient 0.288***
(0.012)

0.279***
(0.011)

0.370***
(0.016)

0.287***
(0.012)

0.251***
(0.012)

0.301***
(0.015)

0.256***
(0.019)
Physical distancing
Intervention coefficient 0.051***
(0 005)

0.056***
(0 005)

0.000
(0 000)

0.074***
(0 007)

0.068***
(0 006)

0.054***
(0 006)

0.044***
(0 011)
Expand for more 
Table 1. Mask-wearing and physical distancing, controlling for baseline variables.

All regressions include an indicator for each control-intervention pair and baseline symptom rates. The analyses in the top panel control for baseline rates of proper mask-wearing, and the analyses in the bottom panel control for baseline rates of physical distancing. “Baseline symptom rate” is defined as the rate of surveyed individuals in a village who report symptoms coinciding with the WHO definition of a probable COVID-19 case. We assume that (i) all reported symptoms were acute onset, (ii) all people live or work in an area with a high risk of transmission of virus, and (iii) all people have been a contact of a probable or confirmed case of COVID-19 or are linked to a COVID-19 cluster. “No active promotion” refers to any time that surveillance was conducted while promotion was not actively occurring (regardless of the week of the intervention). This excludes surveillance during the Friday Jumma Prayers in the mosque, when promoters were present and actively encouraged mask-wearing. “Other locations” include tea stalls, at the entrance of the restaurant as patrons enter, and the main road to enter the village. “Surgical villages” refer to all treatment villages that received surgical masks as part of the intervention and their control pairs. “Cloth villages” refer to all treatment villages that received cloth masks as part of the intervention and their control pairs. The surgical and cloth subsamples include surveillance from all available locations, equivalent to the column labeled “Full” but run separately for each subgroup. Of the 572 villages included in the analysis sample, we exclude an additional village and its pair in the mosque and market subsamples and two villages and their pairs in the other location subsample because we did not observe them in the baseline period before the intervention. There are 190 treatment villages that received surgical masks as part of the intervention and 96 treatment villages that received cloth masks. Standard errors are in parentheses.***Significant at the 1% level.**Significant at the 5% level.*Significant at the 10% level.
7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 6/28 Our intervention increased physical distancing
Contrary to concerns that mask-wearing would promote risk compensation, we did not find evidence that our intervention undermines distancing behavior. In the bottom panel of Table 1, we report identical specifications to the top panel but with physical distancing as the dependent variable. In control villages, 24.1% of observed individuals practiced physical distancing compared with 29.2% in intervention villages, an increase of 5.1% (regression adjusted estimate = 0.05 [0.04, 0.06]). Evidently, protective behaviors like mask-wearing and physical distancing are complements rather than substitutes: Endorsing mask-wearing and informing people about its importance encouraged rural Bangladeshis to take the pandemic more seriously and engage in another form of self-protection.

The increases in physical distancing were similar in cloth and surgical mask villages.

Physical distancing increased 5.1 percentage points overall, but there was substantial heterogeneity across locations. In markets, individuals were 7.4 percentage points more likely to physically distance. By contrast, there was no physical distancing practiced in any mosque, in either treatment or control villages, probably as a result of the strong religious norm of standing shoulder-to-shoulder when praying.

Our intervention had no impact on social distancing
It is possible that physical distancing increases because our intervention results in fewer total people being present in public spaces. If socializing increased in the intervention group, but only among risk-conscious people, then we might see physical distancing increase despite people engaging in overall riskier behavior. To assess this, as well as to assess directly if the intervention increased socializing, we studied the effects of our intervention on the total number of people observed at public locations. Although surveillance staff were not able to count everyone in busy public areas, the total number of people they were able to observe gives some indication of the crowd size. We found no difference in the number of people observed in public areas between the treatment and control groups overall (table S6). The social distancing analysis was not preregistered, although the specification exactly parallels our analysis of physical distancing.

Our intervention reduced symptomatic seroprevalence
Among the 336,010 participants who completed symptom surveys, 27,160 (8.1%) reported experiencing COVID19–like illnesses during the study period. More participants in the control villages reported incident COVID-19– like illnesses (N = 13,853; 8.6%) compared with participants in the intervention villages (N = 13,307; 7.6%). More than one-third (39.7%) of symptomatic participants agreed to blood collection. After omitting symptomatic participants who did not consent to blood collection, symptomatic seroprevalence was 0.76% in control villages and

0.68% in the intervention villages. Because the fractions we are reporting omit nonconsenters from the numerator but not the denominator, it is likely that the true rates of symptomatic seroprevalence are substantially higher (perhaps by 2.5 times, if nonconsenters have similar seroprevalence to consenters).

In Table 2 (and table S7), we report results from a regression of symptomatic seroprevalence on a treatment indicator, clustering at the village level and controlling for fixed effects for each pair of control and treatment villages. In the tables, we report results with and without additional controls for baseline symptoms and mask-wearing rates.

In table S7, we report results from our prespecified linear model, and in Table 2, we report results from a generalized linear model with a Poisson family and log-link function. Here, we discuss the latter results (which are in units of relative risk); the linear model implies results of an almost identical magnitude. The prevalence ratios and accompanying confidence intervals reported in the text correspond to the specifications with baseline controls (hence, “adjusted” prevalence ratio).

Parameter
Intervention effect Intervention effect by mask type
No baseline controls
Intervention prevalence ratio 0.905**
[0.815, 0.995]
Intervention prevalence ratio for surgical mask villages 0.894* [0.782, 1.007]
7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 7/28 P t
Intervention effect I t ti ff t b k t
Expand for more 
Table 2. Symptomatic seroprevalence, expressed in prevalence ratios.

All regressions include an indicator for each control-intervention pair. The regressions “with baseline controls” include controls for baseline rates of proper mask-wearing and baseline symptom rates. “Baseline symptom rate” is defined as the rate of surveyed individuals in a village who report symptoms coinciding with the WHO definition of a probable COVID-19 case. We assume that (i) all reported symptoms were acute onset, (ii) all people live or work in an area with a high risk of transmission of virus, and (iii) all people have been a contact of a probable or confirmed case of COVID-19 or are linked to a COVID-19 cluster. The analysis includes all people surveyed in the baseline household visits, excluding individuals for whom we did not collect midline or endline symptoms, symptomatic individuals from whom we did not collect blood, and individuals from whom we drew blood but did not test their blood. The regressions exclude an additional 17,377 individuals in 34 villages because there are zero people who are symptomatic-seropositive in their village pairs. To check robustness to the type of clustering, in panels 2 and 3 of fig. S2, we show the histogram of effect sizes under “randomization inference” if we randomly reassign treatment within each pair of villages and then estimate our primary specification. We find that our estimated effect size is smaller than 7.0% of the simulated estimates with controls and 7.4% of the simulated estimates without controls (these are the corresponding p values of the randomization inference t test). Blank spaces indicate variables not included in the regression specification reported in each column.***Significant at the 1% level.**Significant at the 5% level.*Significant at the 10% level.†We report the mean rate of symptomatic seroprevalence at endline. This is not equivalent to the coefficient on the constant due to the inclusion of the pair indicators as controls.
7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 8/28 The results in all specifications are the same: We estimate a roughly 9% decline in symptomatic seroprevalence in the treatment group (adjusted prevalence ratio = 0.91 [0.82, 1.00]) for a 29 percentage point increase in mask-wearFig. 1. Map of 600 treatment and control unions.

The figure shows the location of the 600 treatment and control unions in the study. RCT, randomized controlled trial; 1 mile = 1.6 km. 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 9/28 ing over 8 weeks. In the second column of Table 2 and table S7, we split our results by mask type (surgical versus cloth). We find clear evidence that surgical masks lead to a relative reduction in symptomatic seroprevalence of

11.1% (adjusted prevalence ratio = 0.89 [0.78, 1.00]; control prevalence = 0.81%; treatment prevalence = 0.72%).

Although the point estimates for cloth masks suggests that they reduce risk, the confidence limits include both an effect size similar to surgical masks and no effect at all (adjusted prevalence ratio = 0.94 [0.78, 1.10]; control =

0.67%; treatment = 0.61%).

In appendix N, we investigate the robustness of these results to alternative methods of dealing with missing data from nonconsenters. In the main text, following our prespecified analysis plan, we drop nonconsenting symptomatic individuals. If we instead impute seropositivity for symptomatic nonconsenters based on the population average seropositivity among symptomatic individuals, our pooled estimate of the impact of masking becomes larger and more precise. Notably, with this alternative imputation, we find effects for both cloth and surgical masks on symptomatic seroprevalence.

Not all symptomatic seroprevalence is necessarily a result of infections occurring during our intervention; individuals may have had preexisting SARS-CoV-2 infections and then became symptomatic (perhaps caused by an infection other than SARS-CoV-2). In appendix I, we show that if either (i) masks have the same proportional impact on COVID and non-COVID symptoms or (ii) all symptomatic seropositivity is caused by infections during our intervention, then the percentage decline in symptomatic seroprevalence will exactly equal the decline in symptomatic seroconversions. More generally, the relationship between the two quantities depends on whether masks have a greater impact on COVID or non-COVID symptoms, as well as the proportion of symptomatic seropositivity that is a result of infections preexisting at baseline.

Our intervention reduced WHO COVID-19 symptoms
In Table 3 and table S8, we report results from the same specifications with WHO-defined COVID-19 symptomatic status as the outcome. This is defined as any of following:
1) Fever and cough.
2) Any three of the following: fever; cough; general weakness and/or fatigue; headache; muscle aches; sore throat; coryza (nasal congestion or runny nose); dyspnoea (shortness of breath or difficulty breathing); anorexia (loss of appetite), nausea, and/or vomiting; diarrhea; or altered mental status. 3) Anosmia (loss of smell) and ageusia (loss of taste).

Parameter
Intervention effect Intervention effect by mask type
No baseline controls
Intervention prevalence ratio 0.885***
[0.834, 0.934]
Intervention prevalence ratio for surgical mask villages 0.865*** [0.803, 0.928]
Intervention prevalence ratio for cloth mask villages 0.922* [0 838 1 005]
Expand for more 
Table 3. WHO-defined COVID-19 symptoms, expressed in prevalence ratios.

All regressions include an indicator for each control-intervention pair. The regressions “with baseline controls” include controls for baseline rates of proper mask-wearing and baseline symptom rates. “Baseline symptom rate” is defined as the rate of surveyed individuals in a village who report symptoms coinciding with the WHO definition of a probable COVID-19 case. We assume that (i) all reported symptoms were acute onset, (ii) all people live or work in an area with a high risk of transmission of virus, and (iii) all people have been a contact of a probable or confirmed case of COVID-19 or are linked to a COVID-19 cluster. The analysis includes all people surveyed in the baseline household visits, excluding individuals for whom we did not collect midline or endline symptoms. Blank spaces indicate variables not included in the regression specification reported in each column.***Significant at the 1% level.**Significant at the 5% level.*Significant at the 10% level.†We report the mean rate of symptomatic status at endline. This is not equivalent to the coefficient on the constant due to the inclusion of the pair indicators as controls. 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 10/28 We find clear evidence that the intervention reduced symptoms: We estimate a reduction of 11.6% (adjusted prevalence ratio = 0.88 [0.83, 0.93]; control = 8.60%; treatment = 7.63%). Additionally, when we look separately by cloth and surgical masks, we find that the intervention led to a reduction in COVID-19–like symptoms under either mask type (p = 0.000 for surgical; p = 0.066 for cloth), but the effect size in surgical mask villages was 30 to 80% larger depending on the specification. In table S9, we run the same specifications using the smaller sample used in our symptomatic seroprevalence regression (i.e., those who consented to give blood). In this sample, we continue to find an effect overall and an effect for surgical masks but see no statistically significant effect for cloth masks.

In-person reinforcement is crucial to our intervention
Our core intervention package combined multiple distinct elements: We provided people with free masks and information about the importance of mask-wearing, we had mask promoters reinforce mask-wearing by stopping individuals in public places who were not wearing masks and reminding them to do so, and we partnered with local leaders to encourage mask-wearing at mosques and markets. Additionally, in some villages, we provided a variety of reminders, commitment devices, and incentives for village leaders. In appendix J, we attempt to disentangle the role played by these different elements in encouraging mask use.

We find no evidence that any of our village-level or household-level treatments, other than mask color, affected mask-wearing. For mask color, we see marginally significant differences that are small in magnitude. In surgical mask villages, blue masks were more likely to be observed than green masks (adjusted percentage point difference = 0.03 [−0.00, 0.06]), and in cloth mask villages, red masks were more likely to be observed than purple masks (adjusted percentage point difference = −0.02 [−0.04, −0.00]). Text message reminders, incentives for village-leaders, or explicit commitment signals explain little of the observed increase in mask-wearing. Compared with self-protection messaging alone, altruistic messaging had no greater impact on mask-wearing, and twice-weekly text messages and a verbal commitment had no significant effects. We saw no significant difference in the rates of maskwearing in the village-level randomization of surgical versus cloth masks.

We do find nonexperimental evidence that in-person mask promotion and reinforcement is a crucial part of our intervention. Our first pilot study contained all elements of our intervention except in-person reinforcement. Our second pilot study (1 week later) and the full intervention (several months later) added in-person reinforcement.

Under the assumption that treatment effects would otherwise be constant over time, we find that in-person reinforcement accounts for 19.2 percentage points of our effect (regression adjusted estimate = 0.19 [−0.33, −0.05]), or 65% of the total effect size. In table S10, we show that this difference is statistically significant whether or not we include baseline controls. This was not a prespecified analysis.

Our intervention yields persistent increases in mask-wearing In appendix M, we present results on mask-wearing after our intervention ended. Even though the door-to-door free mask distribution occurred in the first week only, there was almost no attenuation of mask-wearing over the initial 10 weeks of surveillance. Notably, mask-wearing remained comparably increased in the treatment group during the 2 weeks we continued surveillance after the end of all intervention activities in the village. Three to 4 months later, mask-wearing waned but remained 10 percentage points higher in treatment regions.

Subgroup analyses
Women wear masks more often, but men respond more to the intervention In table S11, we analyze the impact of our intervention on mask-wearing and physical distancing separately by gender, as well as by whether baseline mask-wearing was above or below the median. Gender was recorded in 65% of observations; age was not recorded during the direct observation surveillance of mask-wearing in public places, and thus we do not conduct an age-stratified assessment. This observed sample is representative of the rural Bangladeshi population that is present in crowded public places during the day; this population is largely composed of men, who have more social contacts outside the home than women. In the gender results, we drop surveillance observations for mosques because in rural Bangladesh it is rare for women to attend mosque. We found that the intervention increased mask-wearing by 27.1 percentage points for men ([0.25, 0.30]) and 22.5 percentage points for women ([0.20, 0.25]). Although we do not have the variation to test this, the gendered difference in effect size may be because our mask promoters were predominantly men or because the mask-wearing rate in control villages was so much higher for women (31% for women versus 12% for men). We intentionally hired predomi- 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 11/28 nantly men because most staff interactions would be with men. Men constituted 88.2% of all observed adults. We also found a larger increase in mask-wearing in villages with below-median baseline mask-wearing (where maskwearing increased from 8.7 to 41.9% at endline) than in those with above-median baseline mask-wearing (where the increase was from 17.5 to 42.6%).

The effect on symptomatic seroprevalence is especially large among the elderly In Table 4 and table S12, we report results from our primary specification separately by age. Table S12 reports our preregistered specification, a linear model run separately for each decade of age, pooling cloth mask and surgical mask villages. Table 4 synthesizes these results, collapsing by categories of <40, 40 to 49, 50 to 59, and ≥60 years old, reporting results as a relative risk reduction, and showing results separately for surgical and cloth masks. We generally find that the impact of the intervention is concentrated among individuals over age 50. In surgical mask villages, we observe a 22.8% decline in symptomatic seroprevalence among individuals aged 50 to 59 years (adjusted prevalence ratio = 0.77 [0.60, 0.95]) and a 35.3% decline among individuals ≥60 years old in our baseline specification (p = 0.000) (adjusted prevalence ratio = 0.65 [0.45, 0.85]). For cloth masks, we find an insignificant (5%) reduction overall but some evidence of a reduction in symptomatic seroprevalence among 40- to 49-yearolds; we investigate more deeply in appendix N and find that the age gradient appears to be sensitive to how we deal with missing values. In the bottom panel of Table 4, we report results where we impute the population average seroprevalence among all nonconsenters rather than dropping them. This alternative approach yields more precise overall estimates and suggests that both cloth and surgical masks have greater impacts on symptomatic seroprevalence at older ages, although the impact of surgical masks among those ≥60 years old is smaller than in our baseline specification. Ex ante, it is not obvious to us which imputation method should be preferred, although the second approach makes our results less sensitive to differential consent rates that we observe in some waves of our intervention, as discussed in appendix N.

The effect on WHO COVID-19 symptoms is larger among the elderly In tables S13 and S14 (the latter being our preregistered specification), we perform the same analysis using the larger sample of individuals who reported symptom information. In this sample, we continue to find larger effects at older ages, although the differences are not as stark as those for the symptomatic seroprevalence outcome. In table S15, we show that the age gradient is steeper for surgical masks.

Men and women have similar reductions in symptoms and symptomatic seroprevalence Parameter All <40 years old
40 to
49 years old
50 to
59 years old
≥60 years
old
Preregistered sample: Drop individuals without blood draws Intervention prevalence ratio for surgical mask villages 0.889** [0.780,

0.997]

0.967
[0.834,

1.100]

1.009
[0.817,

1.200]

0.772**
[0.595,

0.949]

0.647***
[0.448,

0.845]
Intervention prevalence ratio for cloth mask villages 0.942 [0.781,

1.058
[0.870,

0.713**
[0.459,

0.838
[0.524,

1.084
Expand for mor [0.769, e 
Table 4. Symptomatic seroprevalence by age groups and mask type, expressed in prevalence ratios.

All regressions include an indicator for each control-intervention pair. The regressions include controls for baseline rates of mask-wearing and baseline symptom rates. “Baseline symptom rate” is defined as the rate of surveyed individuals in a village who report symptoms coinciding with the WHO definition of a probable COVID-19 case. We assume that (i) all reported symptoms were acute onset, (ii) all people live or work in an area with a high risk of transmission of virus, and (iii) all people have been a contact of a probable or confirmed case of COVID-19 or are linked to a COVID-19 cluster. The analysis in the top panel uses the preregistered sample, equivalent to that in Table 2; it includes all people surveyed in the baseline household visits, excluding individuals for whom we did not collect midline or endline symptoms, symptomatic individuals from whom we did not collect blood, and individuals from whom we drew blood but did not test their blood. The analysis in the bottom panel replicates the regressions in the top panel but imputes the seropositivity of individuals from whom we did not draw blood. For symptomatic individuals from whom we did not draw blood, we simulate their symptomatic-seroprevalence status by using the average rate of conditional seropositivity among all symptomatic individuals. This analysis includes all people surveyed in the baseline household visits, excluding individuals for whom we did not collect midline or endline symptoms.***Significant at the 1% level.**Significant at the 5% level.*Significant at the 10% level.†We report the mean rate of symptomatic seroprevalence at endline. This is not equivalent to the coefficient on the constant due to the inclusion of the pair indicators as controls. 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 12/28 In appendix N and table S28, we show results for symptoms and symptomatic seropositivity by gender. We see a similar pattern to the cloth and surgical mask results: We see significant effects for both genders for symptoms and symptomatic seroposivity when we impute seropositivity at the average value for nonconsenters. If we instead drop nonconsenters, the symptomatic seropositivity estimates for men become less precise and are no longer significantly different from zero, whereas the estimates for women remain unchanged.

Additional preregistered specifications
In appendix P, we discuss additional preregistered specifications that are not reported in the text, either because they were substantially underpowered given the available data or because data on required variables were unavailable. We also discuss ways in which trial implementation deviated from our preregistered protocol, such as switching from exclusively phone surveys to household visits at weeks 5 and 9 to increase response rates.

Intervention cost and benefit estimates
In appendix Q, we assess the costs of implementing our intervention relative to the health benefits, specifically focusing on our ongoing efforts to implement this same intervention at scale in Bangladesh. We consider a range of possible estimates for excess deaths from COVID-19 from 1 May to 1 September 2021, and we assume that our agespecific impacts on symptomatic seroprevalence will lead to proportional reductions in mortality. We estimate that a scaled version of our intervention being implemented in Bangladesh will cost about $1.50 per person, and between $10,000 and $52,000 per life saved, depending on which estimate we use for excess deaths.

Discussion
We present results from a cluster-randomized controlled trial of a scalable intervention designed to increase maskwearing and reduce COVID-19 symptomatic infections. Our estimates suggest that mask-wearing increased by 28.8 percentage points, corresponding to an estimated 51,357 additional adults wearing masks in intervention villages, and this effect was persistent even after active mask promotion was discontinued. The intervention led to a 9.5% reduction in symptomatic SARS-CoV-2 seroprevalence (which corresponds to 105 fewer symptomatic seropositives) and an 11.6% reduction in the prevalence of COVID-19–like symptoms, corresponding to 1541 fewer people reporting these symptoms. If we assume that nonconsenting symptomatic individuals were seropositive at the same rate as consenting symptomatic individuals, the total estimated symptomatic seropositives prevented would be 354. The effects were substantially larger (and more precisely estimated) in communities where we distributed surgical masks, consistent with their greater filtration efficiency as measured in the laboratory (manuscript forthcoming). In villages randomized to receive surgical masks, the relative reduction in symptomatic seroprevalence was 11% overall, 23% among individuals aged 50 to 59 years, and 35% among those ≥60 years of age in preferred specifications.

We found clear evidence that surgical masks are effective in reducing symptomatic seroprevalence of SARS-CoV-2.

Although cloth masks clearly reduce symptoms, we find less clear evidence of their impact on symptomatic SARSCoV-2 infections, with the statistical significance depending on whether we impute missing values for nonconsenting adults. The number of cloth mask villages (100) was half that for surgical masks (200), meaning that our results tend to be less precise. Additionally, we found evidence that surgical masks were no less likely to be adopted than cloth masks. Surgical masks have higher filtration efficiency, are cheaper, are consistently worn, and are better supported by our evidence as tools to reduce COVID-19 cases.

Our results should not be taken to imply that mask-wearing can prevent only 10% of COVID-19 cases, let alone 10% of COVID-19 mortality. Our intervention induced 29 more people out of every 100 to wear masks, with 42% of people wearing masks in total. The total impact with near-universal masking—perhaps achievable with alternative strategies or stricter enforcement—may be several times larger than our 10% estimate. Additionally, the intervention reduced symptomatic seroprevalence more when surgical masks were used and even more for the highest-risk individuals in our sample (23% for ages 50 to 59 years and 35% for ages ≥60 years). These numbers likely give a better sense of the impact of our intervention on severe morbidity and mortality, because most of the disease burden of the COVID-19 pandemic is borne by the elderly. Where achievable, universal mask adoption is likely to have still larger impacts.
7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 13/28 There are several possible theories for why we might observe a larger reduction in COVID-19 cases for older adults.

We did not directly measure age during surveillance, but mask-wearing could have increased more for older adults.

A second theory is that older adults are more susceptible to infections at viral loads that are preventable by masks.

A third theory is that older adults have fewer social connections, so that reducing transmission through any one connection is more likely to prevent infection by severing all transmissible routes. A fourth theory is that people exercised more care and were more likely to wear masks when proximate to the elderly.

We identified a combination of core intervention elements that were effective in increasing mask-wearing in rural Bangladesh: Mask distribution and role-modeling, combined with mask promotion, lead to large and sustained increases in mask use. Results from our pilot studies suggest that combining mask distribution, role-modeling, and active mask promotion—rather than mask distribution and role-modeling alone—seems critical to achieving the full effect. Our trial results also highlight many factors that appear inessential: We find no evidence that public commitments, village-level incentives, text messages, altruistic messaging, or verbal commitments change maskwearing behavior. The null results on our cross-randomizations do not necessarily imply that these approaches are not worth trying in other contexts, but they teach us that large, persistent increases in mask-wearing are possible without these elements.

Prediction studies that we conducted with policy-makers and public health experts at the WHO and the World Bank before presentations of the study results suggest that our results are informative for policy design. Most of the respondents in the prediction studies anticipated that text messages, verbal commitments, and incentives would increase mask-wearing, when in reality, we estimated fairly precise null effects, and poll respondents believed that in-person mask promotion would have no additional effect, whereas the evidence from our pilot studies suggests that it is essential (for additional details, see appendix R).

Our intervention design is immediately relevant for Bangladesh’s plans for larger-scale distribution of masks across all rural areas. The Bangladesh Directorate General of Health has assigned the study team and the nongovernmental organization Bangladesh Rural Advancement Committee (BRAC) the responsibility to scale up the strategies that were proven most effective in this trial to reach 81 million people (35). At the time of writing, we are implementing this program in the 37 districts prioritized by the government based on SARS-CoV-2 test positivity rates. Our results are also relevant for mask dissemination and promotion campaigns planned in other countries and settings that face similar challenges in ensuring mask usage as a result of limited reach and enforcement capacity. The mask promotion model described in this paper was subsequently adopted by governments and other implementers in Pakistan (36), India (37), and Nepal (38). The intervention package would be feasible to implement in a similar fashion in other world regions as well. Beyond face masks, the conceptual underpinning of our strategies could be applied to encourage the adoption of other health behaviors and technologies, in particular, those easily observable by others outside the household, such as purchase and consumption of food, alcohol, and tobacco products in stores, restaurants, or other public spaces (39); hand washing and infection control in health care facilities (40–42); hygiene interventions in childcare and school settings (43, 44); improved sanitation (45, 46); or vaccination drives (47).

Although critics of mask mandates suggest that individuals who wear masks are more likely to engage in high-risk behaviors (48), we found no evidence of risk compensation as a result of increased mask-wearing. Indeed, we found that our intervention slightly increased the likelihood of physical distancing, presumably because individuals participating in the intervention took the threat of COVID-19 more seriously. These findings are consistent with other behaviors, including seat belt use (49) or immunization (50), where risk compensation, even if present, is not sufficient to outweigh direct effects.

The intervention may have influenced rates of COVID-19 by increasing mask use, physical distancing, and/or other risk prevention behaviors. Three factors suggest that the direct impact of masks is the most likely explanation for our documented health impacts. First, in appendix O, we analyze cross-sectionally the relationship between our biological outcomes and both mask-wearing and physical distancing. We find that symptoms and symptomatic seropositivity are negatively correlated with mask-wearing, but not with physical distancing, after controlling for mask-wearing. This analysis uses variation in observational data, rather than solely experimental data, and should therefore be interpreted with caution, as discussed in the appendix. Second, we see no change in physical distancing in the highest-risk environment in our study, typically crowded indoor mosques. However, women do not typi- 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 14/28 cally go to mosques in rural Bangladesh, and their symptomatic seropositivity decreased by just as much as that of men, so outdoor transmission or transmission in settings that we do not observe directly may be important. Third, our study complements a large body of laboratory and quasi-experimental evidence that masks have a direct effect on SARS-CoV-2 transmission (1).

We estimate that a scaled version of our intervention being implemented in Bangladesh will cost between $10,000 and $52,000 per life saved, depending on what fraction of excess deaths are attributable to COVID-19. This is considerably lower than the value of a statistical life in Bangladesh [$205,000 (51)] and, under severe outbreaks, is comparable to the most cost-efficient humanitarian programs at scale [e.g., distributing insecticide nets to prevent malaria costs $9200 per life saved (52)]. This estimate includes only mortality impacts and not morbidity, and greater cost-efficiency is possible if our intervention can be streamlined to further isolate the essential components. Most of our costs were the personnel costs for mask-promoters: If we consider only the costs of mask production, these numbers would be 20 times lower. Thus, the overall cost to save a life in countries where mask mandates can be enforced at minimal cost with existing infrastructure may be substantially lower than our estimates above.

Study limitations
Our study has several limitations. The distinct appearance of project-associated masks and increased mask-wearing in intervention villages made it impossible to blind surveillance staff to study-arm assignment. However, staff were not informed about the exact purpose of the study. Even though surveillance staff were plain-clothed and were instructed to remain discreet, community members could have recognized that they were being observed and changed their behavior. Additionally, survey respondents could have changed their likelihood of reporting symptoms in places where mask-wearing was more widespread. If respondents were more cognizant of symptoms in mask-wearing areas, this may bias us toward underestimating the impact of masks; if respondents in mask-wearing areas were less concerned with mild symptoms and thus were less likely to recall them, this might bias us toward overestimating the impact of masks. Although we confirm that blood consent rates are not significantly different in the treatment and control groups and are comparable across all demographic groups, we cannot rule out that the composition of consenters differed between the treatment and control groups. The slightly higher point estimate for consent in the treatment group biases us away from finding an effect, because it raises symptomatic seroprevalence in the treatment group. Although control villages were at least 2 km from intervention villages, adults from control villages may have come to intervention villages to receive masks, reducing the apparent impact of the intervention. Although we did not directly assess harms in this study, there could be costs resulting from discomfort with increased mask-wearing, adverse health effects such as dermatitis or headaches, or impaired communication.

Because the study was powered to detect differences in symptomatic seroprevalence, we cannot distinguish whether masks work by making symptoms less severe (through a reduced viral load at transmission) or by reducing new infections. We selected the WHO case definition of COVID-19 for its sensitivity, though its limited specificity may imply that the impact of masks on symptoms comes partly from non–SARS-CoV-2 respiratory infections. If masks reduce COVID-19 by reducing symptoms (for a given number of infections), they could help ease the morbidity and mortality resulting from a given number of SARS-CoV-2 infections. If masks reduce infections, they may reduce the total number of infections over the long-term by buying more time to increase the fraction of the population that is vaccinated. At the time of the study, the predominant circulating SARS-CoV-2 strain was B.1.1.7 (Alpha) (53). The impacts of the Delta variant on the number of infections prevented by a given mask-wearer are uncertain; the population-wide consequences of infections prevented by a given mask-wearer may be larger given a higher reproduction number.

We found that mask distribution, role modeling, and promotion in a low- and middle-income country setting increased mask-wearing and physical distancing, leading to lower illness, particularly in older adults. We find especially robust evidence that surgical masks prevent COVID-19. Whether people with respiratory symptoms should generally wear masks to prevent respiratory virus transmission, including for viruses other than SARS-CoV-2, is an important area for future research. Our findings suggest that such behavior may benefit public health.

Methods and materials
7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 15/28 Sampling frame and timeline
The intervention protocol, prespecified analysis plan, and CONSORT checklist are available at https://osf.io/vzdh6/. We discuss our sample-size calculations in appendix B and discuss the selection and pairwise randomization in appendix C. In brief, we stratified villages based on geographic location and available case data, and then selected one treatment and one control village from each pair.

Village-level cluster randomization was important for three reasons. First, unlike technologies with primarily private benefits, mask adoption is likely to yield especially large benefits at the community level. Second, mask adoption by some may influence mask adoption by others because mask-wearing is immediately visible to other members of the community (45). Third, this design allows us to assess the full impact of masks on symptomatic infections, including through source control. Individual-level randomization would identify only whether masks protect wearers.

Our intervention was designed to last 8 weeks in each village. The intervention started in different villages at different times, rolling out over a 6-week period in seven waves. There were between 16 and 61 village-pairs grouped in each wave based on geographic proximity, and paired control and treatment villages were always included in the same wave. The first wave was rolled out on 17 and 18 November 2020 and the last wave was rolled out on 5 and 6 January 2021.

Innovations for Poverty Action (IPA) staff traveled to many villages that had low mask uptake in the first 5 weeks of the study and found that in these villages, local leaders were not very engaged in supporting mask promotion.

Hence, we retrained mask-promotion staff partway through the intervention to work more closely with local leaders and set specific milestones for that partnership.

Outcomes
Our primary outcome was symptomatic seroprevalence of SARS-CoV-2. Our secondary outcomes were prevalence of proper mask-wearing, physical distancing, and symptoms consistent with COVID-19. For COVID-19 symptoms, we used the symptoms that correspond to the WHO case definition of probable COVID-19 given epidemiological risk factors: (i) fever and cough; (ii) three or more of the following symptoms (fever; cough; general weakness and/or fatigue; headache; myalgia; sore throat; coryza; dyspnea; anorexia, nausea, and/or vomiting; diarrhea; and altered mental status); or (iii) loss of taste or smell. Seropositivity was defined by having detectable IgG antibodies against SARS-CoV-2.

Intervention materials and activities
Our entire intervention was designed to be easily adopted by other nongovernmental organizations or government agencies and required minimal monitoring. We have made the materials public in multiple languages to ease widespread adoption and replication by other implementers (https://osf.io/23mws/).

We provide design specifications for our masks in appendix F. We used high-quality surgical masks that had a filtration efficiency of 95% [standard deviation (SD) = 1%]; this is substantially higher than the filtration efficiency of the cloth masks we designed, which had a filtration efficiency of 37% (SD = 6%). These cloth masks had substantially higher filtration than common commercial three-ply cotton masks but lower filtration than hybrid masks that use materials not commonly available for community members in low-resource settings (54). Although cloth masks have less leakage because they fit the face more closely (55) and can be sewn without specialized equipment, they are an order of magnitude more expensive than surgical masks. The filtration efficiency of the high-quality surgical masks used in this study was 76% after washing them with bar soap and water 10 times (manuscript forthcoming). Although surgical masks can break down into microplastics that can enter the environment if disposed of improperly, an analysis of waste generated in Bangladesh’s first lockdown finds that the mass of surgical mask waste was one-third that of polyethylene bags, which also break down into macro- and microplastics (56–58).

Surgical masks were outfitted with a sticker that had a logo of a mask with an outline of the Bangladeshi flag and a phrase in Bengali that noted that the mask could be washed and reused (59). The relatively large scale of our bulk order allowed us to negotiate mask prices of $0.50 per cloth mask and $0.13 per surgical mask ($0.06 of which was the cost of a sticker reminding people that they could wash and reuse the surgical mask). 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 16/28 Adult household members were asked to wear masks whenever they were outside their house and around other people. To emphasize the importance of mask-wearing, we prepared a brief video of notable public figures discussing why, how, and when to wear a mask. The video was shown to each household during the mask distribution visit and featured the Honorable Prime Minister of Bangladesh Sheikh Hasina, the head of the Imam Training Academy, and the national cricket star Shakib Al Hasan. During the distribution visit, households also received a brochure based on WHO materials that depicted proper mask-wearing.

We implemented a basic set of interventions in all treatment villages and cross-randomized additional intervention elements in randomly chosen subsets of treatment villages to investigate whether those have any additional impact on mask-wearing. The basic intervention package consists of five main elements:
1) One-time mask distribution and information provision (about masks) at households. 2) Mask distribution in markets for 3 to 6 days per week during all 8 weeks of the intervention. 3) Mask distribution at mosques on three Fridays during the first 4 weeks of the intervention. 4) Mask promotion in public spaces and markets where non–mask wearers were encouraged to wear masks (weekly or biweekly).
5) Role modeling and advocacy by local leaders, including imams discussing the importance of mask-wearing at Friday prayers using a scripted speech provided by the research team.

Participants and mask surveillance staff were not told which villages were in which intervention arm, but the intervention materials were clearly visible. The prespecified analyses and sample exclusions were made by analysts blinded to the treatment assignment.

Cross-randomization of behavior change communication and incentives Village-level cross-randomizations
Within the intervention arm, we cross-randomized villages to four village-level and four household-level treatments to test the impact of a range of social and behavior change communication strategies on mask-wearing. All intervention villages were assigned to either the treatment or the control group of each of these four randomizations. These village-level randomizations were as follows:
1) Randomization of treated villages to either cloth or surgical masks.

2. Randomization of treated villages to public commitment (providing households signage and asking them to place signage on doors that declares they are a mask-wearing household) or not. The signage was meant to encourage formation of social norms through public signaling.

3. Randomization of treated villages to no incentive, nonmonetary incentive, or monetary incentive of $190 given to the village leader for a project benefitting the public. We announced that the monetary reward or the certificate would be awarded if village-level mask-wearing among adults exceeded 75% at 8 weeks after the intervention started.

4. Randomization of treated villages to 0 or 100% of households receiving twice-weekly text message reminders about the importance of mask-wearing.

Household-level cross-randomizations
We had three household-level cross-randomizations. In any single village, only one of these household randomizations was operative. Because our data collection protocols relied on passive observation at the village level, we could not record the mask-wearing behavior of individual households. To infer the effect of the household-level treatments, we therefore varied the color of the masks distributed to the household based on its cross-randomization status and had surveillance staff record the mask color of observed individuals. In surgical mask villages, a 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 17/28 household received blue or green masks and promoters distributed an equal number of blue and green masks in public settings. In cloth mask villages, households received violet or red masks and promoters distributed blue masks in public settings. To avoid conflating the effect of the household-specific treatment with the effect of the mask color, we randomized which color corresponded to which treatment status across villages (this way a specific color was not fully coincident with a specific treatment). The household-level randomizations, described in further detail in appendix D and visualized in fig. S1, were as follows:
1) Households were randomized to receive messages emphasizing either altruism or self-protection. 2) Households were randomized to making a verbal commitment to be a mask-wearing household (all adults in the household promise to wear a mask when they are outside and around other people) or not. This experiment was conducted in a third set of villages where there was no public signage commitment. 3) Households were randomized to receive twice-weekly text reminders or not. As mentioned above, the text message saturation was randomly varied to 0, 50, or 100% of all households receiving texts, and in the 50% villages, the specific households that received the texts was also random.

Conceptual basis for tested social and behavioral change communication We selected intervention elements that had a reasonable chance of persuading rural Bangladeshis to wear masks by consulting literature in public health, development and behavioral economics, and marketing to identify some of the most promising strategies. An extensive literature identifies price and access as key deterrents to the adoption of welfare-improving products, and especially of technologies that produce positive health externalities, such as face masks (21, 60). Household distribution of free face masks therefore formed the core part of our strategy.

Inspired by large literature in marketing and economics on the role of opinion leaders in new product diffusion, we additionally emphasized a partnership with community leaders in mask distribution (25, 61).

The additional village- and household-level treatments we experimented with were also motivated by insights from marketing, public health, development, and behavioral economics. For example, masks are a visible good where social norms are expected to be important, so we consulted the literature that documented peer effects in product adoption (62–65). We experimented with incentives because it is unclear whether extrinsic rewards crowd out intrinsic motivation (66–68). We tested whether soft commitment devices encourage targets to follow through with actual behavior change (69, 70), whether public displays can promote social norms (27), whether an altruistic framing inspires people more or less than self-interest (71), whether social image concerns and signaling can lead to higher compliance (22, 72), and whether regular reminders are a useful tool to ensure adoption (23).

Piloting interventions
IPA implemented two pilot studies: Pilot 1 from 22 to 31 July 2020 and Pilot 2 from 13 to 26 August 2020. The objective of the pilot studies was to mimic some of the major aspects of the main experiment to identify implementation challenges. Each pilot study was conducted in 10 unions that were not part of the main study area. We used the difference between the pilot studies to better understand which elements of our full intervention were essential. We also conducted focus group discussions and in-depth interviews with village residents, community leaders, religious leaders, and political leaders to elicit opinions on how to maximize the effectiveness of the intervention.

Surveillance strategies
Mask-wearing and physical distancing were measured through direct observation. Surveillance was conducted using a standard protocol that instructed staff to spend 1 hour at each of the following high-traffic locations in the village: market, restaurant entrances, main road, tea stalls, and mosque; the location and timing changed so that the mask-wearing and physical distancing practices of as many individuals as possible could be recorded. Although SARS-CoV-2 transmission is more likely in indoor locations with limited ventilation than outside, rural Bangladeshi villages have few nonresidential spaces where people gather, so observations were conducted outside except at the mosque, where surveillance was conducted inside.

Surveillance staff were distinct from intervention implementation staff and conducted surveillance in paired intervention and control villages. To minimize the likelihood that village residents would perceive that their mask- 7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 18/28 wearing behavior was being observed, surveillance staff were separate from mask promoters and wore no identifying apparel while passively observing mask-wearing and physical distancing practices in the communities. They recorded the mask-wearing behavior of all of the adults that they were able to observe during surveillance periods; observations were not limited to adults from enrolled households. Surveillance staff noted whether adults were wearing any mask or face covering, whether the mask was one distributed by our project (and, if so, the color), and how the mask was worn. We defined proper mask-wearing as wearing either a project mask or an alternative facecovering over the mouth and nose and improper mask-wearing as wearing a mask in any way that did not fully cover the mouth and nose. Surveillance staff observed a single individual and recorded that person as practicing physical distancing if he or she was at least one arm’s length away from all other people. Additional details are available in appendix G.

Symptomatic SARS-CoV-2 testing
Symptom reporting
The owner of the household’s primary phone completed surveys by phone or in-person at weeks 5 and 9 after the start of the intervention. They were asked to report symptoms experienced by any household member that occurred in the previous week and over the previous month. COVID-19–like symptoms were defined by whether they were consistent with the WHO COVID-19 case definition for suspected or probable cases with an epidemiological link (73).

Blood sample collection
We collected endline capillary blood samples from participants who reported COVID-19–like symptoms during the study period and consented to blood collection. We additionally collected samples on a subset of randomly selected participants at baseline, independent of symptoms, to assess overall seropositivity. For the purposes of blood collection, endline was defined as 10 to 12 weeks from the start of the intervention. Blood samples were obtained by puncture with a 20-gauge safety lancet to the third or fourth digit. Five hundred microliters of blood were collected into Microtainer capillary blood collection serum separator tubes (BD, Franklin Lakes, NJ). Blood samples were transported on ice and stored at −20°C until testing.

SARS-CoV-2 testing
Blood samples were tested for the presence of IgG antibodies against SARS-CoV-2 using the SCoV-2 Detect IgG ELISA kit (InBios, Seattle, WA). This assay detects IgG antibodies against the spike protein subunit (S1) of SARSCoV-2. The assays were performed according to the manufacturer’s instructions. Additional details are presented in appendix H.

Symptomatic seropositivity
Our primary outcome is symptomatic seropositivity. As noted above, individuals are symptomatic if they (i) meet the WHO surveillance definition of probable COVID-19 illness and (ii) are seropositive in our blood test at endline.

If either of these conditions fail to hold, , where is an indicator for whether individual i in village j is symptomatic seropositive. To assess seropositivity, we tested all individuals who were symptomatic in either our 5- or 9-week household survey.

Our goal is to estimate the impact of the intervention on symptomatic seropositivity, defined as where is an indicator for whether a village was treated and are village-level covariates, including baseline mask use in each village (constructed as described below) and baseline influenza-like illness and COVID-19 illness based on reported symptoms, as well as indicators for each pair of villages from our pairwise stratification method.

In our preregistered specification, we estimate this parameter by ordinary least squares, clustering at the village level using the approach in (74–76). The dependent variable is , the independent variable of interest is , and controls are included for the covariates, including baseline mask use and baseline respiratory symptom rates in each village. We also report results from a generalized linear model with a Poisson family and log-link function to compute relative risk (77). More details of our statistical analyses are reported in appendix K.

Yij = 0 Yij
ψ0 = Ex[E(Y | = 1, ) − E( | = 0, )] ij Tj xj Yij Tj xj Tj xj
Yij Tj
xj
7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 19/28 Acknowledgments
Thanks to S. Flora, the additional director general of the Directorate General of Health Services in Bangladesh; J.

Snowden; and K. Levy for ongoing support and encouragement. Thanks to WHO chief scientist S. Swaminathan for her encouragement to conduct this trial. Thanks to A. Chowdhury, policy advisor to the Bangladesh government, and S. El Arifeen of the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) for establishing connections with the Bangladesh Directorate General of Health Services in the Ministry of Health and Family Welfare. Thanks to M. Friedman and the CDC Bangladesh country office for assistance with antibody tests. Thanks to A. Saleh, the executive director of BRAC; M. Chowdhury; T. M. Drishti; I. A. Chowdhury; and hundreds of BRAC staff for help with implementation, especially in the scale-up phase of this project in Bangladesh. Similarly, R.

Nanavaty, S. Hebbar, and other staff of SEWA India; Captain Usman and his team at the Lahore Commissioners of- fice; the Nepal Rapid Action Taskforce (C19 RAT); Senator C. Sanguinetti; M. Sanchez; and F. L. Boo played crucial roles in replication and scale-ups in India, Pakistan, Nepal, and Uruguay. Thanks also to J. Chevalier, B. P. Kasina, and S. Daves-Ohlin for their advice and assistance; T. Schmidt for help in shipping; P. Hull for econometrics consulting; A. Bhattacharya of the Tata Institute of Fundamental Research and S. Kumar of Stanford University for conducting filtration efficiency testing of the study masks and evaluation of the impact of washing on surgical mask performance; Y. Choudhury from Katex for assistance with the surgical masks; A. Rahman from Standard Group for assistance with the cloth masks; GreenVoice; A. Gsellman for help with visualizations; and many employees at IPA Bangladesh for assistance throughout this project. Most importantly, our continued engagement in and scaling-up of mask promotion would not be possible without the tireless efforts of the Mask-NORM team, including N. Saldanha, H. McAnnally-Linz, M. Rehman, G. Patel, J. Pinilla, J. Rajashekar, P. Adhikary, S. Barnhardt, M. Ali, U. Wattal, I. Haque, A. Tamayo, L. Burke, J. Mosenkis, and many other staff of Yale University and IPA.

Funding: This research was financially supported by a grant from GiveWell.org to IPA (grant GR-000000272). J.B.- C. was supported by the National Institute of Allergy and Infectious Diseases, National Institutes of Health (grant K01AI141616).

Research ethics approvals: Our study protocols were reviewed and approved by the Yale University Institutional Review Board (protocol ID 2000028482) and by the Bangladesh Medical Research Council National Research Ethics Committee (IRB registration number 330 26 08 2020). We also received separate administrative approval from the Bangladesh Ministry of Health and Family Welfare. The Bangladesh Directorate General of Health Services under the Ministry of Health; Aspire to Innovate (a2i), an information and data-focused organization within the Bangladesh government; North-South University in Dhaka; and icddr,b partnered in the study design and discussions and reviewed protocols. We provide ethical justification for our decisions in our online ethics appendix (https://osf.io/m2bwq/).

Author contributions: Conceptualization: J.A., L.H.K., A.S., S.P.L., A.M.M.; Methodology: J.A., L.H.K., A.S., J.B.- C., P.J.W., S.P.L., A.M.M.; Software: E.C.; Validation: E.C.; Formal analysis: J.A., E.C.; Investigation: L.H.K., A.S., M.H., H.M.R., A.A.J., S.G.M., A.R., F.L.B., T.S.H.; Resources: E.B.-J., S.B.; Data curation: S.Rah., E.C., N.Z.B.; Writing: J.A., L.H.K., A.S., E.C., S.P.L., A.M.M.; Visualization: E.C., N.Z.B.; Supervision: J.A., S.P.L., A.M.M.; Project administration: J.A., L.H.K., A.H., M.A.K., S.Rai., S.Rah.; Funding acquisition: J.A., A.M.M., L.H.K., A.S., S.P.L.

Competing interests: The funder had no role in the study design, interpretation of results, or decision to publish.

The authors declare no competing interests.

Data and materials availability: This clinical trial has been registered at clinicaltrials.gov (identifier NCT04630054). All data and code are provided in our online repository (https://gitlab.com/emily-crawford/bdmask-rct) (78). This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/. This license does not apply to figures/photos/artwork or other content included in the article that is credited to a third party; obtain authorization from the rights holder before using such material.

Supplementary Materials
7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 20/28 This PDF file includes:

Figs. S1 to S6
Tables S1 to S37
Appendices
References (79–81)
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Other Supplementary Material for this manuscript includes the following:

MDAR Reproducibility Checklist
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References and Notes
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APR. 25, 2022
Reply to Mitchell Lee
JASON ABALUCK Professor of Economics, Yale University, School of Management We thank Mitchell for identifying two inadvertent deviations from our pre-analysis plan – we of course regret the errors, although we certainly disagree that these deviations are serious ones, let alone the "Major Problems" his title indicates.

In one case, we can show the deviation has no impact on the results. In the second case, we inadvertently collected no data view more
MAR. 27, 2022
Major problems with the definition of "WHO-defined COVID symptoms"

MITCHELL LEE
7/22/22, 1:23 PM Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh https://www.science.org/doi/10.1126/science.abi9069 26/28 SHOW ALL eLETTERS
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I believe the study has a serious undeclared deviation from its preregistered analysis plan. In short, the definition of "WHOdefined COVID symptoms" that the authors preregistered is significantly different from the definition they actually used in their analysis.
view more
FEB. 21, 2022
Important study but results sensitive to modelling approaches CHAO WANG Senior Lecturer in Health & Social Care Statistic, Kingston University and St George's, University of London I would firstly like to thank the authors for conducting such an important study As rightly stated by Glasziou et al (2021) Recommended articles from TrendMD
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3 7/21/22, 10:25 AM Effectiveness of Adding a MaskRecommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish MaskWea… https://www.acpjournals.org/doi/10.7326/M20-6817 1/58
ACP Journals
Original Research | March 2021
Effectiveness of Adding a Mask Recommendation to Other
Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers FREE
A Randomized Controlled Trial
Henning Bundgaard, DMSc, Johan Skov Bundgaard, BSc, … View all authors  Author, Article, and Disclosure Information
https://doi.org/10.7326/M20-6817
Eligible for CME Point-of-Care
Visual Abstract. Effectiveness of Mask Recommendation for Preventing SARS-CoV-2 Infection Observational evidence suggests that mask wearing mitigates SARS-CoV-2 transmission. It is uncertain if this observed association arises through protection of uninfected wearers (protective effect), via reduced transmission from infected mask wearers (source control), or both. This randomized controlled trial investigates whether recommending surgical mask use when outside the home reduces wearers' risk for SARS-CoV-2 infection in a setting where masks were uncommon and not among recommended public health measures.

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Abstract
Background:

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Observational evidence suggests that mask wearing mitigates transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is uncertain if this observed association arises through protection of uninfected wearers (protective effect), via reduced transmission from infected mask wearers (source control), or both.

Objective:

To assess whether recommending surgical mask use outside the home reduces wearers' risk for SARS-CoV-2 infection in a setting where masks were uncommon and not among recommended public health measures.

Design:

Randomized controlled trial (DANMASK-19 [Danish Study to Assess Face Masks for the Protection Against COVID-19 Infection]). (ClinicalTrials.gov:

NCT04337541)
Setting:

Denmark, April and May 2020.

Participants:

Adults spending more than 3 hours per day outside the home without occupational mask use.

Intervention:

Encouragement to follow social distancing measures for coronavirus disease 2019, plus either no mask recommendation or a recommendation to wear a PDF
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mask when outside the home among other persons together with a supply of 50 surgical masks and instructions for proper use.

Measurements:

The primary outcome was SARS-CoV-2 infection in the mask wearer at 1 month by antibody testing, polymerase chain reaction (PCR), or hospital diagnosis. The secondary outcome was PCR positivity for other respiratory viruses.

Results:

A total of 3030 participants were randomly assigned to the recommendation to wear masks, and 2994 were assigned to control; 4862 completed the study.

Infection with SARS-CoV-2 occurred in 42 participants recommended masks (1.8%) and 53 control participants (2.1%). The between-group difference was −0.3 percentage point (95% CI, −1.2 to 0.4 percentage point; P = 0.38) (odds ratio, 0.82 [CI, 0.54 to 1.23]; P = 0.33). Multiple imputation accounting for loss to follow-up yielded similar results. Although the difference observed was not statistically significant, the 95% CIs are compatible with a 46% reduction to a 23% increase in infection.

Limitation:

Inconclusive results, missing data, variable adherence, patient-reported findings on home tests, no blinding, and no assessment of whether masks could decrease disease transmission from mask wearers to others.

Conclusion:

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The recommendation to wear surgical masks to supplement other public health measures did not reduce the SARS-CoV-2 infection rate among wearers by more than 50% in a community with modest infection rates, some degree of social distancing, and uncommon general mask use. The data were compatible with lesser degrees of self-protection.

Primary Funding Source:

The Salling Foundations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has infected more than 54 million persons (1, 2). Measures to impede transmission in health care and community settings are essential (3). The virus is transmitted person-toperson, primarily through the mouth, nose, or eyes via respiratory droplets, aerosols, or fomites (4, 5). It can survive on surfaces for up to 72 hours (6), and touching a contaminated surface followed by face touching is another possible route of transmission (7). Face masks are a plausible means to reduce transmission of respiratory viruses by minimizing the risk that respiratory droplets will reach wearers' nasal or oral mucosa. Face masks are also hypothesized to reduce face touching (8, 9), but frequent face and mask touching has been reported among health care personnel (10). Observational evidence supports the efficacy of face masks in health care settings (11, 12) and as source control in patients infected with SARS-CoV-2 or other coronaviruses (13).

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7/21/22, 10:25 AM Effectiveness of Adding a MaskRecommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish MaskWea… https://www.acpjournals.org/doi/10.7326/M20-6817 5/58
An increasing number of localities recommend masks in community settings on the basis of this observational evidence, but recommendations vary and controversy exists (14). The World Health Organization (WHO) and the U.S.

Centers for Disease Control and Prevention (15) strongly recommend that persons with symptoms or known infection wear masks to prevent transmission of SARS-CoV-2 to others (source control) (16). However, WHO acknowledges that we lack evidence that wearing a mask protects healthy persons from SARS-CoV-2 (prevention) (17). A systematic review of observational studies reported that mask use reduced risk for SARS, Middle East respiratory syndrome, and COVID-19 by 66% overall, 70% in health care workers, and 44% in the community (12). However, surgical and cloth masks were grouped in preventive studies, and none of the 3 included non–health care studies related directly to COVID-19. Another systematic review (18) and American College of Physicians recommendations (19) concluded that evidence on mask effectiveness for respiratory infection prevention is stronger in health care than community settings.

Observational evidence suggests that mask wearing mitigates SARS-CoV-2 transmission, but whether this observed association arises because masks protect uninfected wearers (protective effect) or because transmission is reduced from infected mask wearers (source control) is uncertain. Here, we report a randomized controlled trial (20) that assessed whether a recommendation to wear a surgical mask when outside the home among others reduced wearers' risk for SARS-CoV-2 infection in a setting where public health measures were in effect but community mask wearing was uncommon and not recommended.

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Methods
Trial Design and Oversight
DANMASK-19 (Danish Study to Assess Face Masks for the Protection Against COVID-19 Infection) was an investigator-initiated, nationwide, unblinded, randomized controlled trial (ClinicalTrials.gov: NCT04337541). The trial protocol was registered with the Danish Data Protection Agency (P-2020-311) (Part 10 of the Supplement) and published (21). The researchers presented the protocol to the independent regional scientific ethics committee of the Capital Region of Denmark, which did not require ethics approval (H20023709) in accordance with Danish legislation (Parts 11 and 12 of the Supplement). The trial was done in accordance with the principles of the Declaration of Helsinki.

Participants and Study Period
During the study period (3 April to 2 June 2020), Danish authorities did not recommend use of masks in the community and mask use was uncommon (<5%) outside hospitals (22). Recommended public health measures included quarantining persons with SARS-CoV-2 infection, social distancing (including in shops and public transportation, which remained open), limiting the number of persons seen, frequent hand hygiene and cleaning, and limiting visitors to hospitals and nursing homes (23, 24). Cafés and restaurants were closed during the study until 18 May 2020.

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Eligible persons were community-dwelling adults aged 18 years or older without current or prior symptoms or diagnosis of COVID-19 who reported being outside the home among others for at least 3 hours per day and who did not wear masks during their daily work. Recruitment involved media advertisements and contacting private companies and public organizations.

Interested citizens had internet access to detailed study information and to research staff for questions (Part 3 of the Supplement). At baseline, participants completed a demographic survey and provided consent for researchers to access their national registry data (Parts 4 and 5 of the Supplement). Recruitment occurred from 3 through 24 April 2020. Half of participants were randomly assigned to a group on 12 April and half on 24 April.

Intervention
Participants were enrolled and data registered using Research Electronic Data Capture (REDCap) software (25). Eligible participants were randomly assigned 1:1 to the mask or control group using a computer algorithm and were stratified by the 5 regions of Denmark (Supplement Table 1).

Participants were notified of allocation by e-mail, and study packages were sent by courier (Part 7 of the Supplement). Participants in the mask group were instructed to wear a mask when outside the home during the next month. They received 50 three-layer, disposable, surgical face masks with ear loops (TYPE II EN 14683 [Abena]; filtration rate, 98%; made in China).

Participants in both groups received materials and instructions for antibody testing on receipt and at 1 month. They also received materials and PDF
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instructions for collecting an oropharyngeal/nasal swab sample for polymerase chain reaction (PCR) testing at 1 month and whenever symptoms compatible with COVID-19 occurred during follow-up. If symptomatic, participants were strongly encouraged to seek medical care. They registered symptoms and results of the antibody test in the online REDCap system.

Participants returned the test material by prepaid express courier.

Written instructions and instructional videos guided antibody testing, oropharyngeal/nasal swabbing, and proper use of masks (Part 8 of the Supplement), and a help line was available to participants. In accordance with WHO recommendations for health care settings at that time, participants were instructed to change the mask if outside the home for more than 8 hours. At baseline and in weekly follow-up e-mails, participants in both groups were encouraged to follow current COVID-19 recommendations from the Danish authorities.

Antibody and Viral PCR Testing
Participants tested for SARS-CoV-2 IgM and IgG antibodies in whole blood using a point-of-care test (Lateral Flow test [Zhuhai Livzon Diagnostics]) according to the manufacturer's recommendations and as previously described (26). After puncturing a fingertip with a lancet, they withdrew blood into a capillary tube and placed 1 drop of blood followed by 2 drops of saline in the test chamber in each of the 2 test plates (IgM and IgG).

Participants reported IgM and IgG results separately as “1 line present” (negative), “2 lines present” (positive), or “I am not sure, or I could not PDF
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perform the test” (treated as a negative result). Participants were categorized as seropositive if they had developed IgM, IgG, or both. The manufacturer reported that sensitivity was 90.2% and specificity 99.2%. A previously reported internal validation using 651 samples from blood donors before November 2019 and 155 patients with PCR-confirmed SARS-CoV-2 infection estimated a sensitivity of 82.5% (95% CI, 75.3% to 88.4%) and specificity of

99.5% (CI, 98.7% to 99.9%) (26). We (27) and others (28) have reported that oropharyngeal/nasal swab sampling for SARS-CoV-2 by participants, as opposed to health care workers, is clinically useful. Descriptions of RNA extraction, primer and probe used, reverse transcription, preamplification, and microfluidic quantitative PCR are detailed in Part 6 of the Supplement.

Data Collection
Participants received 4 follow-up surveys (Parts 4 and 5 of the Supplement) by e-mail to collect information on antibody test results, adherence to recommendations on time spent outside the home among others, development of symptoms, COVID-19 diagnosis based on PCR testing done in public hospitals, and known COVID-19 exposures.

Outcomes
The primary outcome was SARS-CoV-2 infection, defined as a positive result on an oropharyngeal/nasal swab test for SARS-CoV-2, development of a positive SARS-CoV-2 antibody test result (IgM or IgG) during the study period, or a hospital-based diagnosis of SARS-CoV-2 infection or COVID-19.

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Secondary end points included PCR evidence of infection with other respiratory viruses (Supplement Table 2).

Sample Size Calculations
The sample size was determined to provide adequate power for assessment of the combined composite primary outcome in the intention-to-treat analysis. Authorities estimated an incidence of SARS-CoV-2 infection of at least 2% during the study period. Assuming that wearing a face mask halves risk for infection, we estimated that a sample of 4636 participants would provide the trial with 80% power at a significance level of 5% (2-sided α level). Anticipating 20% loss to follow-up in this community-based study, we aimed to assign at least 6000 participants.

Statistical Analysis
Participants with a positive result on an antibody test at baseline were excluded from the analyses. We calculated CIs of proportions assuming binomial distribution (Clopper–Pearson).

The primary composite outcome (intention-to-treat) was compared between groups using the χ test. Odds ratios and confidence limits were calculated using logistic regression. We did a per protocol analysis that included only participants reporting complete or predominant use of face masks as instructed. A conservative sensitivity analysis assumed that participants with a positive result on an antibody test at the end of the study who had not provided antibody test results at study entrance had had a positive result at 2 PDF
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entrance. To further examine the uncertainty of loss to follow-up, we did (post hoc) 200 imputations using the R package smcfcs, version 1.4.1 (29), to impute missing values of outcome. We included sex, age, type of work, time out of home, and outcome in this calculation.

Prespecified subgroups were compared by logistic regression analysis. In a post hoc analysis, we explored whether there was a subgroup defined by a constellation of participant characteristics for which a recommendation to wear masks seemed to be effective. We included sex, age, type of work, time out of home, and outcome in this calculation.

Two-sided P values less than 0.05 were considered statistically significant.

Analyses were done using R, version 3.6.1 (R Foundation).

Role of the Funding Source
An unrestricted grant from the Salling Foundations supported the study, and the BESTSELLER Foundation donated the Livzon tests. The funders did not influence study design, conduct, or reporting.

Results
Participants
A total of 17 258 Danish citizens responded to recruitment, and 6024 completed the baseline survey and fulfilled eligibility criteria. The first participants (group 1; n = 2995) were randomly assigned on 12 April 2020 and PDF
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were followed from 14 to 16 April through 15 May 2020. Remaining participants (group 2; n = 3029) were randomly assigned on 24 April 2020 and were followed from 2 to 4 May through 2 June 2020. A total of 3030 participants were randomly assigned to the recommendation to wear face masks, and 2994 were assigned not to wear face masks (Figure); 4862 participants (80.7%) completed the study. Table 1 shows baseline characteristics, which were well balanced between groups. Participants reported having spent a median of 4.5 hours per day outside the home.

Figure. Study flow diagram.

Inclusion and exclusion criteria are described in the Methods section, and criteria for completion of the study are given in the Supplement. SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2.

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Adherence
Based on the lowest adherence reported in the mask group during follow-up, 46% of participants wore the mask as recommended, 47% predominantly as recommended, and 7% not as recommended.

Primary Outcome
Table 1. Characteristics of Participants Completing the Study PDF
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The primary outcome occurred in 42 participants (1.8%) in the mask group and 53 (2.1%) in the control group. In an intention-to-treat analysis, the between-group difference was −0.3 percentage point (CI, −1.2 to 0.4 percentage point; P = 0.38) (odds ratio [OR], 0.82 [CI, 0.54 to 1.23]; P = 0.33) in favor of the mask group (Supplement Figure 1). When this analysis was repeated with multiple imputation for missing data due to loss to follow-up, it yielded similar results (OR, 0.81 [CI, 0.53 to 1.23]; P = 0.32). Table 2 provides data on the components of the primary end point, which were similar between groups.

In a per protocol analysis that excluded participants in the mask group who reported nonadherence (7%), SARS-CoV-2 infection occurred in 40 participants (1.8%) in the mask group and 53 (2.1%) in the control group (between-group difference, −0.4 percentage point [CI, −1.2 to 0.5 percentage point]; P = 0.40) (OR, 0.84 [CI, 0.55 to 1.26]; P = 0.40). Supplement Figure 2 provides results of the prespecified subgroup analyses of the primary composite end point. No statistically significant interactions were identified.

In the preplanned sensitivity analysis, those who had a positive result on an antibody test at 1 month but had not provided antibody results at baseline were considered to have had positive results at baseline (n = 18)—that is, they were excluded from the analysis. In this analysis, the primary outcome Table 2. Distribution of the Components of the Composite Primary Outcome PDF
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occurred in 33 participants (1.4%) in the face mask group and 44 (1.8%) in the control group (between-group difference, −0.4 percentage point [CI, −1.1 to 0.4 percentage point]; P = 0.22) (OR, 0.77 [CI, 0.49 to 1.22]; P = 0.26).

Three post hoc (not preplanned) analyses were done. In the first, which included only participants reporting wearing face masks “exactly as instructed,” infection (the primary outcome) occurred in 22 participants (2.0%) in the face mask group and 53 (2.1%) in the control group (betweengroup difference, −0.2 percentage point [CI, −1.3 to 0.9 percentage point]; P =

0.82) (OR, 0.93 [CI, 0.56 to 1.54]; P = 0.78). The second post hoc analysis excluded participants who did not provide antibody test results at baseline; infection occurred in 33 participants (1.7%) in the face mask group and 44 (2.1%) in the control group (between-group difference, −0.4 percentage point [CI, −1.4 to 0.4 percentage point]; P = 0.33) (OR, 0.80 [CI, 0.51 to 1.27]; P =

0.35). In the third post hoc analysis, which investigated constellations of patient characteristics, we did not find a subgroup where face masks were effective at conventional levels of statistical significance (data not shown).

A total of 52 participants in the mask group and 39 control participants reported COVID-19 in their household. Of these, 2 participants in the face mask group and 1 in the control group developed SARS-CoV-2 infection, suggesting that the source of most observed infections was outside the home.

Reported symptoms did not differ between groups during the study period (Supplement Table 3).

Secondary Outcomes
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In the mask group, 9 participants (0.5%) were positive for 1 or more of the 11 respiratory viruses other than SARS-CoV-2, compared with 11 participants (0.6%) in the control group (between-group difference, −0.1 percentage point [CI, −0.6 to 0.4 percentage point]; P = 0.87) (OR, 0.84 [CI, 0.35 to 2.04]; P =

0.71). Positivity for any virus, including SARS-CoV-2, occurred in 9 mask participants (0.5%) versus 16 control participants (0.8%) (between-group difference, −0.3 percentage point [CI, −0.9 to 0.2 percentage point]; P = 0.26) (OR, 0.58 [CI, 0.25 to 1.31]; P = 0.19).

Discussion
In this community-based, randomized controlled trial conducted in a setting where mask wearing was uncommon and was not among other recommended public health measures related to COVID-19, a recommendation to wear a surgical mask when outside the home among others did not reduce, at conventional levels of statistical significance, incident SARS-CoV-2 infection compared with no mask recommendation. We designed the study to detect a reduction in infection rate from 2% to 1%.

Although no statistically significant difference in SARS-CoV-2 incidence was observed, the 95% CIs are compatible with a possible 46% reduction to 23% increase in infection among mask wearers. These findings do offer evidence about the degree of protection mask wearers can anticipate in a setting where others are not wearing masks and where other public health measures, including social distancing, are in effect. The findings, however, should not be used to conclude that a recommendation for everyone to wear masks in the community would not be effective in reducing SARS-CoV-2 PDF
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infections, because the trial did not test the role of masks in source control of SARS-CoV-2 infection. During the study period, authorities did not recommend face mask use outside hospital settings and mask use was rare in community settings (22). This means that study participants' exposure was overwhelmingly to persons not wearing masks.

The observed infection rate was similar to that reported in other large Danish studies during the study period (26, 30). Of note, the observed incidence of SARS-CoV-2 infection was higher than we had estimated when planning a sample size that would ensure more than 80% power to detect a 50% decrease in infection. The intervention lasted only 1 month and was carried out during a period when Danish authorities recommended quarantine of diagnosed patients, physical distancing, and hand hygiene as general protective means against SARS-CoV-2 transmission (23). Cafés and restaurants were closed through 18 May, but follow-up of the second randomized group continued through 2 June.

The first randomized group was followed while the Danish society was under lockdown. Reopening occurred (18 May 2020) during follow-up of the second group of participants, but it was not reflected in the outcome because infection rates were similar between groups (Supplement Figure 2).

The relative infection rate between mask wearers and those not wearing masks would most likely be affected by changes in applied protective means or in the virulence of SARS-CoV-2, whereas the rate difference between the 2 groups would probably not be affected solely by a higher—or lower— number of infected citizens.

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Although we saw no statistically significant difference in presence of other respiratory viruses, the study was not sufficiently powered to draw definite conclusions about the protective effect of masks for other viral infections.

Likewise, the study had limited power for any of the subgroup analyses.

The primary outcome was mainly defined by antibodies against SARS-CoV-2.

This definition was chosen because the viral load of infected patients may be only transiently detectable (31, 32) and because approximately half of persons infected with SARS-CoV-2 are asymptomatic (26, 33). Masks have been hypothesized to reduce inoculum size (34) and could increase the likelihood that infected mask users are asymptomatic, but this hypothesis has been challenged (35). For these reasons, we did not rely solely on identification of SARS-CoV-2 in oropharyngeal/nasal swab samples. As mentioned in the Methods section, an internal validation study estimated that the point-of-care test has 82.5% sensitivity and 99.5% specificity (26).

The observed rate of incident SARS-CoV-2 infection was similar to what was estimated during trial design. These rates were based on thorough screening of all participants using antibody measurements combined with PCR, whereas the observed official infection rates relied solely on PCR test–based estimates during the period. In addition, authorities tested only a small subset of primarily symptomatic citizens of the entire population, yielding low incidence rates. On this basis, the infection rates we report here are not comparable with the official SARS-CoV-2 infection rates in the Danish population. The eligibility requirement of at least 3 hours of exposure to other persons outside the home would add to this difference. Between 6 April PDF
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and 9 May 2020, we found a similar seroprevalence of SARS-CoV-2 of 1.9% (CI, 0.8% to 2.3%) in Danish blood donors using the Livzon point-of-care test and assessed by laboratory technicians (36). Testing at the end of follow-up, however, may not have captured any infections contracted during the last part of the study period, but this would have been true in both the mask and control groups and was not expected to influence the overall findings.

The face masks provided to participants were high-quality surgical masks with a filtration rate of 98% (37). A published meta-analysis found no statistically significant difference in preventing influenza in health care workers between respirators (N95 [American standard] or FFP2 [European standard]) and surgical face masks (38). Adherence to mask use may be higher than observed in this study in settings where mask use is common.

Some mask group participants (14%) reported adverse reactions from other citizens (Supplement Table 4). Although adherence may influence the protective effect of masks, sensitivity analyses had similar results across reported adherence.

How SARS-CoV-2 is transmitted—via respiratory droplets, aerosols, or (to a lesser extent) fomites—is not firmly established. Droplets are larger and rapidly fall to the ground, whereas aerosols are smaller (≤5 μm) and may evaporate and remain in the air for hours (39). Transmission of SARS-CoV-2 may take place through multiple routes. It has been argued that for the primary route of SARS-CoV-2 spread—that is, via droplets—face masks would be considered effective, whereas masks would not be effective against spread via aerosols, which might penetrate or circumnavigate a face mask (37, 39).

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Thus, spread of SARS-CoV-2 via aerosols would at least partially explain the present findings. Lack of eye protection may also have been of importance, and use of face shields also covering the eyes (rather than face masks only) has been advocated to halt the conjunctival route of transmission (40, 41). We observed no statistically significant interaction between wearers and nonwearers of eyeglasses (Supplement Figure 2). Recent reports indicate that transmission of SARS-CoV-2 via fomites is unusual (42), but masks may alter behavior and potentially affect fomite transmission.

The present findings are compatible with the findings of a review of randomized controlled trials of the efficacy of face masks for prevention (as personal protective equipment) against influenza virus (18). A recent metaanalysis that suggested a protective effect of face masks in the non–health care setting was based on 3 observational studies that included a total of 725 participants and focused on transmission of SARS-CoV-1 rather than SARSCoV-2 (12). Of 725 participants, 138 (19%) were infected, so the transmission rate seems to be higher than for SARS-CoV-2. Further, these studies focused on prevention of infection in healthy mask wearers from patients with a known, diagnosed infection rather than prevention of transmission from persons in their surroundings in general. In addition, identified comparators (control participants) not wearing masks may also have missed other protective means. Recent observational studies that indicate a protective association between mandated mask use in the community and SARS-CoV-2 transmission are limited by study design and simultaneous introduction of other public health interventions (14, 43).

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Several challenges regarding wearing disposable face masks in the community exist. These include practical aspects, such as potential incorrect wearing, reduced adherence, reduced durability of the mask depending on type of mask and occupation, and weather. Such circumstances may necessitate the use of multiple face masks during the day. In our study, participants used a mean of 1.7 masks per weekday and 1.3 per weekend day (Supplement Table 4). Wearing a face mask may be physically unpleasant, and psychological barriers and other side effects have been described (44). “Face mask policing” between citizens might reinforce use of masks but may be challenging. In addition, the wearer of a face mask may change to a less cautious behavior because of a false sense of security, as pointed out by WHO (17); accordingly, our face mask group seemed less worried (Supplement Table 4), which may explain their increased willingness to wear face masks in the future (Supplement Table 5). These challenges, including costs and availability, may reduce the efficacy of face masks to prevent SARSCoV-2 infection.

The potential benefits of a community-wide recommendation to wear masks include combined prevention and source control for symptomatic and asymptomatic persons, improved attention, and reduced potential stigmatization of persons wearing masks to prevent infection of others (17).

Although masks may also have served as source control in SARS-CoV-2– infected participants, the study was not designed to determine the effectiveness of source control.

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The most important limitation is that the findings are inconclusive, with CIs compatible with a 46% decrease to a 23% increase in infection. Other limitations include the following. Participants may have been more cautious and focused on hygiene than the general population; however, the observed infection rate was similar to findings of other studies in Denmark (26, 30).

Loss to follow-up was 19%, but results of multiple imputation accounting for missing data were similar to the main results. In addition, we relied on patient-reported findings on home antibody tests, and blinding to the intervention was not possible. Finally, a randomized controlled trial provides high-level evidence for treatment effects but can be prone to reduced external validity.

Our results suggest that the recommendation to wear a surgical mask when outside the home among others did not reduce, at conventional levels of statistical significance, the incidence of SARS-CoV-2 infection in mask wearers in a setting where social distancing and other public health measures were in effect, mask recommendations were not among those measures, and community use of masks was uncommon. Yet, the findings were inconclusive and cannot definitively exclude a 46% reduction to a 23% increase in infection of mask wearers in such a setting. It is important to emphasize that this trial did not address the effects of masks as source control or as protection in settings where social distancing and other public health measures are not in effect.

Reduction in release of virus from infected persons into the environment may be the mechanism for mitigation of transmission in communities where PDF
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mask use is common or mandated, as noted in observational studies. Thus, these findings do not provide data on the effectiveness of widespread mask wearing in the community in reducing SARS-CoV-2 infections. They do, however, offer evidence about the degree of protection mask wearers can anticipate in a setting where others are not wearing masks and where other public health measures, including social distancing, are in effect. The findings also suggest that persons should not abandon other COVID-19 safety measures regardless of the use of masks. While we await additional data to inform mask recommendations, communities must balance the seriousness of COVID-19, uncertainty about the degree of source control and protective effect, and the absence of data suggesting serious adverse effects of masks (45).

Comments
39 Comments SIGN IN TO SUBMIT A COMMENT
Brian P Hanley • Butterfly Sciences, Scientist • 4 February 2022 Other confounding factors

1. PPE problems occur among MS-PhD-DVM’s that may handle select agents which occasionally kill, getting investigators into MMWR. Hence, we have regular safety training and officers (RO’s) tasked to ensure PPE is properly fitted and worn. (In practice, cookies are involved to ease the pain of staff attendance.) Observing public mask use notes partial compliance styles invisible in one 46% number. A. Wide gaps mask. B. Under-nose mask. C. Chin mask. D. Not a mask.

2. Tyranny of R encourages incorrect infectious disease thinking. Reality is not that someone sick transmits to 1, 2, maybe 3 people. Super-spreaders drive pandemics, infecting tens or hundreds of people (Lloyd-Smith 2005). From whom should we expect masking conformance? Not superspreaders, who, in or out of the treatment arm, will drive outsize effects from low noncompliance levels. 0 PDF
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3. My physician reports indicate ~50% of 2020 ER SARS-CoV-2 cases arrived for other reasons with CXR Dx pneumonia. O2<90% (lowest conscious patient <50%) is a basic triage diagnostic for SARSCoV-2. What does this mean for masking? The O2 compromised tachypneic do not tolerate masks well. Thus, we should expect those shedding virus are least likely to tolerate a mask – ergo, they will be in that 54% non-compliance. This catch-22 of the SARS-CoV-2 pandemic should be addressed directly in our discussions of control.

4. Degree of morbidity, and ultimately death rate, matters for populations. Masks lower the infecting dose, which should affect death rate. Obviously, 10 infected cells^20th generation is less than 1000^20thor 10,000^20th. Capturing the effect of masking on morbidity and mortality would take a very large study. However, we should be clear that “Who dies?” is the bottom line. Thus, is rapid test diagnostic a proper surrogate endpoint? Further, is an infecting dose study possible?

5. I attempted to address the economic/pandemic intertwined issues with a joint editorial in 2020 calling for immediate rollout of killed, component, and nucleotide vaccines, monitored as occurs in stage 4 (Hanley 2020). My observation is that the USA working class’ incomes were often devastated while the white-collar (computer-work) class was not. The working class took masking as a symbol and vaccines ended up in that same tent. More discussion of inequality exacerbation is warranted.

6. Given a 46% compliance rate not based on direct monitoring, clinical trials tell us compliance is lower. Thus, pharma prefers subjects stay in their facility for complete monitoring. People forget, confabulate, etc.

REFERENCES:

Lloyd-Smith JO, Schreiber SJ, Kopp PE, Getz WM. Superspreading and the effect of individual variation on disease emergence. Nature. 2005 Nov 17;438(7066):355-9. doi: 10.1038/nature04153. PMID: 16292310; PMCID: PMC7094981.

Hanley BP, Keen S, Church G. A Call for a Three-Tiered Pandemic Public Health Strategy in Context of SARS-CoV-2. Rejuvenation Res. 2020 Aug;23(4):281-283. doi: 10.1089/rej.2020.2363. Epub 2020 Jun 24.

PMID: 32539623; PMCID: PMC7462018.
ong valcot • Retired • 12 September 2021
Infection rate mored than order of magnitude too high
When the study was conducted in 30 day period in Denmark about 4,300 people got infected which is about 0.07% of population but the study registerd about 2% infection rate in the 30 day period. The discrepancy by factor of 28 is way too high. Denmark could not have 28 higher infection prevalence than the offcial rate. The multiplier of 28x would imply that by the end of 2020 all adults in Denmark would be infected.

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Since the majority of infections in the study were determined by the self-administered antibody tests one must conclude that there was much higher rate of false positives than what the manufacturer of tests claimed.

For this reason the study has a fatal flaw and its conclusiosn should be dismissed. The study does not have anything interesting or valid to tell us about the efficacy of masks.

Henning Bundgaard, Anna K Ringgaard, Daniel Emil Tadeusz Raaschou-Pedersen, Johan Skov Bundgaard and Kasper K Iversen • University of Copenhagen • 9 June 2021
Authors' Response to Moran, Spinelli, Gains, Llor, Rand.

We thank readers for the many interesting comments and address some of them here. We agree with Brendan Moran, that the “lag” relating to infection late during the trial and time to seroconversion was to some extent captured by PCR tests. In our sample size calculation, we applied a power of 80% with an assumed infection rate of 2% in the control group. The power was ensured as the infection rate was 2.1% in the control group, and the number of participants who finalized the study was as little higher as compared to the number needed to include according to the sample size calculation. We agree with the interesting point made by Matthew A. Spinelli, David V. Glidden, Efstathios D. Gennatas, George W.

Rutherford and Monica Gandhi that cluster randomization might be a good alternative to our randomization approach. However, in practical terms it might be difficult to perform such cluster randomization; will all – or just most – citizens in the towns randomized to wear masks accept to do so? – will all – or just most – citizens in the town randomized not the wear a mask accept to do so? – there are several ethical concerns. Furthermore, as SARS-CoV-2 spreads in clusters, and the number of randomized clusters should therefore be very large to ensure a nonbiased result – making such a study logistically difficult to implement. We instructed the participants in correct use of the masks, we provided high quality masks, delivered at home, free of charge and we assessed compliance through the email surveys 4 times during the study, and the worst reported compliance was accounted for in analyses. Our take is that compliance was very high – and most likely higher than what is seen during every-day use of face masks.

Hans Gaines may be right that participants might have been infected at home from asymptomatic, i.e. undiagnosed members of their household. The participants were only asked to wear masks when outside the home consistent with public health recommendations on use of masks -- as it is hard to imagine a recommendation to wear masks at home. We also agree with Carl Llor that the circumstances have changed since April-May when we conducted our study. We do not believe that the cultural and social behavior in Denmark is so different from other countries, but we agree that habits like kissing and hugging relatives, neighbors and friends are different in different cultures – and such habits might represent a risk for SARS-CoV-2 transmission. We agree that the question of the effectiveness of masks in crowded places and when in proximity to others is important – and was not addressed in our study. We tested the effect of adding the masks to the general recommendations including the recommendation to keep a social distance PDF
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of 1-2 meters - even in crowded places. However, we agree – we need more studies to assess the efficacy of masking in different settings. We would like to highlight in response the comment by Janet Rand that our study demonstrated that “the recommendation to wear surgical masks to supplement other public health measures did not reduce the SARS-CoV-2 infection rate among wearers by more than 50% in a community with modest infection rates, some degree of social distancing, and uncommon general mask use” and that “the findings, however, should not be used to conclude that a recommendation for everyone to wear masks in the community would not be effective in reducing SARS-CoV-2 infections, because the trial did not test the role of masks in source control of SARS-CoV-2 infection.” Despite these statements in our paper, some have misinterpreted our results and unfortunately, made conclusions to questions that were not addressed by our study.

Magnus Glindvad Ahlström, Frederik Boëtius Hertz, and Kristian Schønning • Department of Clinical Microbiology 9301, Rigshospitalet, Henrik Harpestrengs Vej 4A, Copenhagen, Denmark • 15 December 2020 To mask or not – diagnostics matter.

Bundgaard et al. present data from a randomized controlled trial (DANMASK-19) to assess whether face mask use outside home reduces risk for SARS-CoV-2 infection (1). Infection was assessed by antibody testing, PCR testing, and healthcare diagnosis. Infection occurred in 42 participants recommended mask wearing (1.8%), and 53 control participants (2.1%). 75/95 (79%) infections were diagnosed by seroconversion. Participants tested themselves for antibodies at baseline and end of intervention using a lateral flow assay.

Antibodies to SARS-CoV-2 develop in symptomatic individuals in the second week after symptom onset and occur later in less severe infections (2, 3). The incubation period is 4-6 days (4). The purpose of mask intervention is to limit exposure to SARS-CoV-2. Yet, seroconversions in the two first weeks of the intervention period may be attributed to SARS-CoV-2 exposures before intervention. The study was conducted in a period of lockdown in Denmark. In the week preceding the first intervention period, 1504 SARS-CoV-2+ cases were identified in 13,940 PCR tests (positive rate: 10.8%); in the last week of the second intervention period 306 cases were identified in 67,773 PCR tests (positive rate: 0.5%). Therefore, a burn-in intervention period before baseline serological testing would have been appropriate.

Seroconversion occurred in 1.5% (75/4862) of participants. Seroconversions were rare and warranted confirmation by secondary testing. The authors validated the test used and found a specificity of 99.5% (CI:

98.7-99.9). This validation was done by skilled laboratory personnel using plasma samples laboratory personnel (5). In DANMASK-19, testing was done by the participants themselves using whole blood specimens. If test specificity is the same under these conditions is doubtful.

Twenty incident SARS-CoV-2 infections were diagnosed by PCR testing in a healthcare setting (n=15) or at the end of the intervention (n=5). PCR tests are specific and often use multiple SARS-CoV-2 targets (1; Part 6 of the Supplement) simulating confirmatory testing. Lag time between infectious exposure and positive PCR is only 4-5 days, which reduces need for a burn-in period. There were 5 cases in the intervention PDF
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group and 15 cases in the control group diagnosed by PCR (OR: 0.34; 95%CI: 0.10-0.99). If analysis is restricted to securely ascertained infections, the effect of face masks was both clinically and statistically significant. In the prespecified analysis reported in the study, this effect may be obscured by virus exposures occurring before intervention and inappropriateness of the serological diagnostic strategy applied.

Diagnostics matter also in randomized clinical trials.

References

1. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of adding a mask recommendation to other public health measures to prevent SARS-CoV-2 infection in Danish mask wearers. Ann Intern Med. 2020; 18:M20-6817. [PMID: 33205991] doi: 10.7326/M20-6817

2. Wang Y, Zhang L, Sang L, et al. Kinetics of viral load and antibody response in relation to COVID-19 severity. J Clin Invest. 2020; 130:5235-5244. [PMID: 32634129] doi: 10.1172/JCI138759

3. Prévost J, Gasser R, Beaudoin-Bussières G, et al. Cross-sectional evaluation of humoral responses against SARS-CoV-2 spike. Cell Rep Med. 2020; 1:100126. [PMID: 33015650] doi:

10.1016/j.xcrm.2020.100126

4. Wassie GT, Azene AG, Bantie GM, et al. Incubation period of Severe Acute Respiratory Syndrome Novel Coronavirus 2 that causes Coronavirus disease 2019: A systematic review and meta-analysis.

Curr Ther Clin Exp. 2020; 93:100607. [PMID: 33071295] doi: 10.1016/curtheres.2020.100607

5. Iversen K, Bundgaard H, Hasselbach RB, et al. Risk of COVID-19 in health-care in Denmark: an observational cohort study. Lancet Infect Dis. 2020; 20:1401-1408. [PMID: 32758438] doi:

10.1016/S1473-3099(20)30589-2
Jiahe Chen, MS, PhDc, Hanke Zhang, MS, PhDc, Nadine K. Zawadzki, MPH, PhDc, Joel W. Hay, PhD, Cynthia L. Gong, PharmD, PhD • Schaeffer Center for Health Economics and Policy; Fetal & Neonatal Institute, Division of Neonatology, Children's Hospital Los Angeles, University of Southern California, Los Angeles, CA • 17 December 2020 Universal mask mandates are not supported by the evidence The COVID-19 pandemic has led to near-universal adoption of non-pharmaceutical intervention policies in the United States, including masking in public places. Recently, Bundgaard et al [1] reported they did not find a significant protective effect of wearing surgical face masks in their randomized control trial (RCT).

This result is consistent with our review of Chu et al’s meta-analysis [2] reviewing the ability of masking to reduce coronavirus transmission, in which the included studies were mostly limited by their quasiexperimental study designs and narrow healthcare-based settings.

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E-values can be used to quantify the extent to which unmeasured confounding can nullify the observed results.[3] We calculated E-values for the outcomes in Bundgaard et al’s study, finding an E-value (confidence limit) of 1.74 (1) for the primary composite end point of antibodies against SARS-CoV-2 (OR=0.82, 95% CI 0.54-1.23). For presence of IgM (OR=0.87, 95% CI = 0.54-1.41) and IgG (OR=1.07, 95% CI = 0.66-1.75), the E-value (confidence limit) was 1.56 (1) and 1.34 (1) respectively. Finally, the outcome of healthcare-diagnosed SARS-CoV-2 (OR=0.52, 95% CI = 0.18-1.53) had an E-value (confidence limit) of 3.25 (1). These low E-values indicate that unobserved activities like vigilant handwashing could easily explain the findings in this study.

Although Bundgaard et al acknowledge their study’s limitations including missing data, variable adherence and absence of blinding, it is more applicable to real-world settings during the pandemic than the observational studies in Chu et al’s meta-analysis, considering Bundgaard et al used an RCT study design and focused specifically on reducing COVID-19 transmission under non-healthcare community settings. In fact, that only 7% of mask-wearers reported non-adherence appears low, considering that 100% adherence was defined as properly covering the nose and mouth and changing the mask if worn for >8 hours. In addition, participants received three-layer disposable surgical face masks, which is inconsistent with policies mandating that any cloth covering should be used. At best, the Bundgaard et al’s findings provide negative or insignificant support for public mask-wearing policies. Nonetheless, the authors should be commended for their efforts to conduct a real-world RCT on a politically charged topic.

References

1. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of adding a mask recommendation to other public health measures to prevent SARS-CoV-2 infection in Danish mask wearers: a randomized controlled trial. Ann Intern Med. 2020 Nov 18. doi: 10.7326/M20-6817.

2. Chu DK, Akl EA, Duda S, et al. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and metaanalysis. Lancet. 2020;395(10242):1973-1987.

3. VanderWeele TJ, Ding P. Sensitivity analysis in observational research: Introducing the E-Value. Ann Intern Med. 2017;167(4):268-274. doi:10.7326/M16-2607
Jun Xu • none • 25 December 2020
Masks Work
Dear Editor,
I agree with the DANMASK-19 findings that common masks provide small protection for the wearers. But how much protection for the people around the wearers?
To get a full picture of the masks’ protective effect, an ideal trial should separate the mask group from the non-mask group. If a trial mixes two groups together, their infection rates will be distorted. In other words, the non-mask group’s infection rate will be underestimated because the non-maskers are PDF
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benefitting from the mask group’s source control, while the mask group’s will be overestimated because the maskers are suffering from the non-mask group’s spreads.

A German study [1] estimates that the effects of mandating face mask use in public would reduce the growth rates of infections by 40% to 60%. This is a clear picture of the impact of a face mask mandate on infections because the mask and non-mask groups in the study didn’t affect each other.

References

1. Mitze T., Kosfeld R., Rode J., Wälde K. Face Masks Considerably Reduce COVID-19 Cases in Germany:

A Synthetic Control Method Approach. IZA – Institute of Labor Economics (Germany);2020.ISSN:
2365-9793, DP No. 13319.

Magnus Glindvad Ahlström, Frederik Boëtius Hertz, and Kristian Schønning • Department of Clinical Microbiology 9301, Rigshospitalet, Henrik Harpestrengs Vej 4A, Copenhagen, Denmark • 15 December 2020 To mask or not – diagnostics matter.

Bundgaard et al. present data from a randomized controlled trial (DANMASK-19) to assess whether face mask use outside home reduces risk for SARS-CoV-2 infection (1). Infection was assessed by antibody testing, PCR testing, and healthcare diagnosis. Infection occurred in 42 participants recommended mask wearing (1.8%), and 53 control participants (2.1%). 75/95 (79%) infections were diagnosed by seroconversion. Participants tested themselves for antibodies at baseline and end of intervention using a lateral flow assay.

Antibodies to SARS-CoV-2 develop in symptomatic individuals in the second week after symptom onset and occur later in less severe infections (2, 3). The incubation period is 4-6 days (4). The purpose of mask intervention is to limit exposure to SARS-CoV-2. Yet, seroconversions in the two first weeks of the intervention period may be attributed to SARS-CoV-2 exposures before intervention. The study was conducted in a period of lockdown in Denmark. In the week preceding the first intervention period, 1504 SARS-CoV-2+ cases were identified in 13,940 PCR tests (positive rate: 10.8%); in the last week of the second intervention period 306 cases were identified in 67,773 PCR tests (positive rate: 0.5%). Therefore, a burn-in intervention period before baseline serological testing would have been appropriate.

Seroconversion occurred in 1.5% (75/4862) of participants. Seroconversions were rare and warranted confirmation by secondary testing. The authors validated the test used and found a specificity of 99.5% (CI:

98.7-99.9). This validation was done by skilled laboratory personnel using plasma samples laboratory personnel (5). In DANMASK-19, testing was done by the participants themselves using whole blood specimens. If test specificity is the same under these conditions is doubtful.

Twenty incident SARS-CoV-2 infections were diagnosed by PCR testing in a healthcare setting (n=15) or at the end of the intervention (n=5). PCR tests are specific and often use multiple SARS-CoV-2 targets (1; Part 6 of the Supplement) simulating confirmatory testing. Lag time between infectious exposure and positive PDF
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PCR is only 4-5 days, which reduces need for a burn-in period. There were 5 cases in the intervention group and 15 cases in the control group diagnosed by PCR (OR: 0.34; 95%CI: 0.10-0.99). If analysis is restricted to securely ascertained infections, the effect of face masks was both clinically and statistically significant. In the prespecified analysis reported in the study, this effect may be obscured by virus exposures occurring before intervention and inappropriateness of the serological diagnostic strategy applied.

Diagnostics matter also in randomized clinical trials.

References

1. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of adding a mask recommendation to other public health measures to prevent SARS-CoV-2 infection in Danish mask wearers. Ann Intern Med. 2020; 18:M20-6817. [PMID: 33205991] doi: 10.7326/M20-6817

2. Wang Y, Zhang L, Sang L, et al. Kinetics of viral load and antibody response in relation to COVID-19 severity. J Clin Invest. 2020; 130:5235-5244. [PMID: 32634129] doi: 10.1172/JCI138759

3. Prévost J, Gasser R, Beaudoin-Bussières G, et al. Cross-sectional evaluation of humoral responses against SARS-CoV-2 spike. Cell Rep Med. 2020; 1:100126. [PMID: 33015650] doi:

10.1016/j.xcrm.2020.100126

4. Wassie GT, Azene AG, Bantie GM, et al. Incubation period of Severe Acute Respiratory Syndrome Novel Coronavirus 2 that causes Coronavirus disease 2019: A systematic review and meta-analysis.

Curr Ther Clin Exp. 2020; 93:100607. [PMID: 33071295] doi: 10.1016/curtheres.2020.100607

5. Iversen K, Bundgaard H, Hasselbach RB, et al. Risk of COVID-19 in health-care in Denmark: an observational cohort study. Lancet Infect Dis. 2020; 20:1401-1408. [PMID: 32758438] doi:

10.1016/S1473-3099(20)30589-2
Max Longin • Mathematician in Denmark • 15 December 2020 This study design would not even proof that a 100% protection has a protective effect Imagine a 100% perfect protection against COVID-19 (a hermetic room), what outcome should be expected for this by-definition safe group using this study design? Here is the math only for estimating
- the false-positive antibody-tests
- positive test due to before-baseline infections
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But as the study design grants protection at average only 4.5 hours/day infections outside the room should be added to the calculated expectations (in the study false-classified as noneffective protection).

The study reports antibody testing has an estimated 99,2% specificity. For about 2400 tests this leads to an expectation of 2400*0.008=19 false-positive tests in each antibody test group.

IgG-antibodies form very delayed. So in non-increasing rate of new infections (as the case in 05/2020 in Denmark) about 80% of all true-positive IgG tests at study-end show infections before study-baseline. So the expectation of positive tests due to before-baseline infections in the control group is 10.4 (80% of 13 (=32-19) „true-positive“ IgG tests)
The mentioned false-detection arises solely to from a test-property (specificity) and before-baseline events, so the expectations for the control group for false-positive test (19) and for true-positive tests due to beforebaseline infections (10.4) equals the expectations for the safe group, adding up to: expectation(IgGSafeGroup)=29.4 IgM responds from >2-6 weeks after infection. So about 50% of the IgM true positive tests are likely due to before-baseline infections. Analogue to above 19 false positive and 9 positive IgM tests (50% of 18 (=37-19) „true-positive“ IgM tests) due to before-baseline infections sum up to: expectation(IgM-SafeGroup)=29 PCR-tests hardly suffer from specifity and time lags in the study, so no positive PCR-tests should be expected in the safe group: expectation(PCR-SafeGroup)=0 A temporally evenly distributed health care diagnosis during study will again suffer from the delay from infection to diagnosis (first 9 days (=30% of 30 days) diagnosis will likely show before-baseline infections).

So 0,3*10=3 cases are likely due to before-baseline infections and have to be expected for the safe group as well: expectation(HealthCare-SafeGroup)=3
Even without additional expected infections at home, friends etc. - falsely assigned as inside the hermetic room the expected outcome in the by-definition safe group is already about 75% of the control outcome (or 90% of the face-mask-group).

Altogether this study design expects for a by-definition 100%-protection:
- measure an Odd Ratio of ≥0.75 (≤25% protection),
- include OR=1 (i.e. no-protection-at-all) in the 95%-Confidence Interval and - exclude OR≤0.4 (≥60% protection) from 95%-CI
Alberto Donzelli • Scientific Committee of Foundation “Allineare Sanità e Salute” – Milan - Italy. • 14 December 2020 PDF
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The effectiveness of mask recommendation (mainly outdoors) is questionable, for overlooked reasons
The DANMASK-19 (1) conclude: “The recommendation to wear surgical masks to supplement other public health measures did not reduce the SARS-CoV-2 infection rate among wearers… The difference was not statistically significant, the 95% CIs are compatible with a 46% reduction to a 23% increase in infection.” Two editorialists (2) state: “Across all analyses odds ratios were approximately 0.8, consistent with a 20% reduction in incident SARS-CoV-2 infection if masks are recommended. The sample size was insufficient to determine the statistical significance of a 20% reduction”. However, 52 participants in the mask group and 39 control participants reported COVID-19 in their household, that might be considered as randomized clusters. Assuming the same (or proportional) numbers of Covid-19 and similar households’ denominators, summing the Sars-CoV-2 infections of each group with the COVID-19 of its households, the mask group plus households experienced more infections/diseases than the control group plus households. Moreover, 40% of face mask group reduced physical activity (1).

The criticism that “the antibody-positive results in both intervention and control groups could have been false positives” (2), biasing the findings towards the null, does not apply to the reported households’ COVID-19.

The criticism that “only 46% of those in the intervention group reported adherence” (2) exactly as instructed, weakens the editorialists’ thesis indeed, because infection, the primary outcome, occurred in

2.0% of “adherents”, further approaching the control group’s 2.1%.

The editorialists point that the intervention group females had less infections (odds ratio, 0.65; 0.38-1.12 [please note: males 1.12; 0.59-2.12]), because women “may be more likely to adhere” (2). Inconsistently, their citation (3) shows that women indeed are more compliant than men with each of ten restraining measures, and significantly so in three, including handwashing and distancing, but not with wearing face masks.

The mechanistic evidence that masks reduce wearer exposure and block his/her respiratory droplets implies specularly that microorganisms eventually multiplying in the infected persons’ airways are in turn blocked at each exhalation and partially re-inhaled, increasing the cumulative viral load and the infection, and contagiousness (4). This overlooked mechanism works in the opposite direction to the protective one:
only well-designed trials can establish which net effect prevails at the community level. In the Hajj pilgrims trial (5) the net effect outdoors shifted towards an excess of respiratory infections in mask wearers (and perhaps in pilgrims sharing tents with others in the mask group). Wearing masks long and everywhere is not evidence-based.

References
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1. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of Adding a Mask Recommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers. A Randomized Controlled Trial.Ann Intern Med. 18 November 2020. doi:10.7326/M20- 6817

2. Frieden TR, Cash-Goldwasser S. Of Masks and Methods. Ann Intern Med. 18 November 2020. doi:10.7326/M20-7499

3. Galasso V, Pons V, Profeta P, et al. Gender Differences in COVID-19 Attitudes and Behavior: Panel Evidence from 8 Countries. PNAS. 2020; 117(44):27285–27291.

4. Donzelli A. Mascherine “chirurgiche” in comunità/all’aperto: prove di efficacia e sicurezza inadeguate. Epidemiol Prev.2020, https://repo.epiprev.it/index.php/download/mascherinechirurgiche-in-comunita-allaperto-prove-di-efficacia-e-sicurezza-inadeguate/

5. Alfelali M, Haworth EA, Barasheed O, et al. Facemask against viral respiratory infections among Hajj pilgrims: A challenging cluster randomized trial. PLoS ONE 15(10):e0240287. https://doi.org/10.1371/journal.pone.0240287
Disclosures:

There are no conflicts of interest to disclose.

Dr. SJM • ACP • 9 December 2020
No future trials are needed!
I respectfully disagree with Dr. Bundgaard that additional trials are needed to help answer the question of protective benefit masks in COVID-19. We had 12 RCTs (1) from influenza and other respiratory viruses that showed us there was no added benefit from mask use. Despite this compelling evidence, we believed that the situation was different with SARS-2 in the presymptomatic phase. With the DANMASK 19, powered with 6000 individuals, it is consistent with all previous trials of mask benefit that the effects are negligible. We need to show integrity in mandating masks when the evidence CLEARLY does not support such a measure. Neither has there been any additional benefit in countries that have been more adherent to masks. The only evidence based conclusions we can recommend to the public are to avoid crowds and to enhance hand hygiene. Nothing more!

1. Chou R, Dana T, Jungbauer R, et al. Masks for Prevention of Respiratory Virus Infections, Including SARS-CoV-2, in Health Care and Community Settings : A Living Rapid Review. Ann Intern Med. 2020 Oct 6;173(7):542-555. doi: 10.7326/M20-3213. Epub 2020 Jun 24. PMID: 32579379; PMCID: PMC7322812.

Carl Llor • Primary care physician and senior researcher. University Institute in Primary Care Research Jordi Gol, Via Roma Health Centre, Barcelona. • 6 December 2020
External validity of these results to hard-hit areas.

Dear Editor,
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Bundgaard et al. showed in their randomized controlled trial [1] that face mask use supplementing other public health strategies did not significantly reduce SARS-CoV2 infection in people wearing the mask.

Apart from the limitations of the study mentioned by the authors themselves, mainly the low face mask wear adherence and the lack of assessment of whether masks could decrease disease transmission from mask wearers to others, there are other variables that can make generalization of these results difficult.

The randomized controlled trial design is irrefutably the best method in clinical research addressing interventions and we have to applaud the authors for conducting such a great trial in a short period of time, but this trial was conducted in a country with a low-moderate incidence of COVID-19 and during lockdown (April and May 2020).

People in many areas of the world are less likely to avoid public places and stay home than residents of Denmark. Social distancing could qualify as an oxymoron in Southern Europe, South America, the United States and citizens of many other crowded parts of the world, where walking arm-in-arm with friends, eating out in crowded restaurants and terraces, or kissing relatives, neighbors and friends are part of their cultures. There is now solid evidence that individuals in poor health are more susceptible to serious illnesses [2]. In Southern Europe, for example, low-paid employees are less likely to do their jobs from home and taking public transport to crowded workplaces might lead to more contagions, as are families pushed into housing with insufficient space.

The “real life conditions” in many areas in the world are quite different from Denmark. We should ask if this modest protection of face mask wearers from infection with SARS-Cov-2 in this country would have been the same if this trial had been conducted in crowded areas with no curfew. We agree with the authors that more well-conducted studies are needed before drawing a conclusion like this.

References

1. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of adding a mask recommendation to other public health measures to prevent SARS-CoV-2 infection in Danish mask wearers: a randomized controlled trial. Ann Intern Med. 2020 Nov 18. doi: 10.7326/M20-6817.

2. Marmot M. Social determinants of health inequalities. Lancet. 2005;365(9464):1099-104. doi:

10.1016/S0140-6736(05)71146-6.

Suliman Ahmad, Zoe Gan • Faculty of Life Sciences & Medicine, King's College London, London, UK • 6 December 2020 Comment on: Effectiveness of Adding a Mask Recommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers To The Editor,
The authors are to be commended for their contributions regarding the efficacy of face masks in mitigating the risk of transmission of SARS-CoV-2 infection (1). However, these findings should be interpreted with caution due to a number of confounding variables that were not accounted for in the study design.

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Firstly, the instruction guide provided on how to wear a mask were extremely brief. It was advised that participants “place the mask over the nose and under the chin” and to “remember hand hygiene when using the mask” but no guidance was offered regarding appropriate use of the mask while it was worn, nor safe disposal of the mask when it was no longer needed. Self-contamination by touching the mask with contaminated hands after it has been donned, sharing face masks with others and reusing masks is recognised as a potential risk of SARS-CoV-2 transmission (2). Detailed and explicit instructions should have therefore been given on safe and appropriate usage of medical masks.

Furthermore, it was recommended that masks should be changed every eight hours. This eight-hourly time frame was based on World Health Organisation (WHO) guidance at the time of the trial (April-May 2020) according to the authors. However, to our knowledge, WHO recommendations at this time were that a medical mask should be replaced every six hours, or when damp or soiled (2,3). Therefore it would have been prudent to issue guidance to participants on replacing a mask within this time frame or when wet, soiled or damaged, as extended use of a mask may risk contamination with the SARS-CoV-2 virus.

In addition, adherence to mask-wearing was not only poor but poorly assessed. Only 46% of participants wore the mask as recommended, as measured through a single question (“are you using the mask according to our recommendation?”) on a weekly survey. The subjective nature of such an approach lends itself to self-reporting bias due to differences between individuals in perceiving how well they followed recommendations (4). This could have been mitigated through further questioning on the survey to more objectively estimate compliance, such as enquiring about the duration and frequency of use (5).

In summary, we believe that the conclusions drawn by this study are weak due to omissions in the study design and the potential benefits of mask-wearing as protection against SARS-CoV-2 may therefore have been missed.

References

1. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, von Buchwald C, Todsen T, Norsk JB, et al. Effectiveness of Adding a Mask Recommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers. Annals of Internal Medicine [Internet]. 2020 Nov 18 [cited 2020 Nov 23];M20-6817. Available from: https://www.acpjournals.org/doi/10.7326/M20-6817

2. Advice on the use of masks in the community, during home care and in healthcare settings in the context of the novel coronavirus (COVID-19) outbreak [Internet]. [cited 2020 Nov 23]. Available from: https://www.who.int/publications/i/item/advice-on-the-use-of-masks-in-the-communityduring-home-care-and-in-healthcare-settings-in-the-context-of-the-novel-coronavirus-(2019-ncov)- outbreak
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3. Rational use of personal protective equipment for coronavirus disease (COVID-19) and considerations during severe shortages [Internet]. [cited 2020 Dec 6]. Available from:
https://www.who.int/publications/i/item/rational-use-of-personal-protective-equipment-forcoronavirus-disease-(covid-19)-and-considerations-during-severe-shortages

4. Althubaiti A. Information bias in health research: Definition, pitfalls, and adjustment methods [Internet]. Vol. 9, Journal of Multidisciplinary Healthcare. Dove Medical Press Ltd.; 2016 [cited 2020 Dec 6]. p. 211–7. Available from: /pmc/articles/PMC4862344/?report=abstract

5. Barasheed O, Alfelali M, Mushta S, Bokhary H, Alshehri J, Attar AA, et al. Uptake and effectiveness of facemask against respiratory infections at mass gatherings: A systematic review.

International Journal of Infectious Diseases [Internet]. 2016 Jun 1 [cited 2020 Dec 6];47:105–11.

Available from: /pmc/articles/PMC7110449/?report=abstract Corresponding authors:

Suliman Ahmad, Zoe Gan
Faculty of Life Sciences & Medicine, King’s College London Conflict of interest: None to declare
Greg Taylor • Avrea Radiologist • 6 December 2020
Mask effect with low prevalence
Perhaps your article can be interpreted as saying that at a time with low prevalence, especially compared with the current daily rates, mask wearing confers at best minimal benefit. Here in South Dakota, other than factory transmission by a symptomatic worker, we had virtually no spread of Covid this spring and summer, I saw a few abnormal Covid chest xrays per month. Now we are at the breaking point, I see several abnormal Covid chest xrays per day.

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Pedro M Teixeira • School of Medicine, University of Minho • 3 December 2020 Yet another case of trial external validity demolished by incongruous intervention features.

Dear Editor,
This trial resembles in many aspects the ‘Parachute use to prevent death and major trauma when jumping from aircraft: randomized controlled trial’ published in 2018 by Robert W Yeh. (1) Both present nonstatistically significant results on major outcomes. They both fail to reject the null hypothesis that state that there is no effect in using a parachute when jumping from aircraft to prevent death or major trauma (1) and there is no effect in reducing respiratory infections when using facial masks in the community (2).

In Yeh’s study, the aircraft was on the ground and in Bundgaard’s trial, people in the community do not vastly wear facial masks, only participants in the experimental group do. SARS-CoV-2 transmission may occur by mouth, nose or eye exposure. (3) Participants in the experimental group when in close contact with other people, that do not contain air droplets by using facial masks, were exposed to similar risk of eye SARS-CoV-2 infection as the control group. If the plane was on the ground, participants from the experimental group faced the same risk as the control group. Without widespread facial mask use in the community, the protective nature of facial masks (i.e. droplets containment) remains severely compromised in close encounters. Such performance bias pose serious constrains and challenges in effectiveness trial studies design and may induce error in result interpretation and decision making in health interventions. (4) The critical appraisal of the intervention features in real life settings is warranted. 1 YEH, Robert W., et al. Parachute use to prevent death and major trauma when jumping from aircraft:
randomized controlled trial. bmj, 2018, 363.

2. BUNDGAARD, Henning, et al. Effectiveness of adding a mask recommendation to other public health measures to prevent SARS-CoV-2 infection in Danish mask wearers: a randomized controlled trial. Annals of Internal Medicine, 2020.
3 WU, Ping, et al. Characteristics of ocular findings of patients with coronavirus disease 2019 (COVID-19) in Hubei Province, China. JAMA ophthalmology, 2020, 138.5: 575-578.

4. BARRETO, Mauricio L. Efficacy, effectiveness, and the evaluation of public health interventions. Journal of epidemiology and community health, 2005, 59.5: 345-346.

Henning Bundgaard, DMSc, MD, Kasper Iverson, MD • Copenhagen University • 4 December 2020 Authors' Response to comments
Authors Henning Bundgaard and Kasper Iversen’s response to Tuan Nguyen PDF
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Thanks for this interesting analysis. It should be noted that the meta-analysis was not related to SARS-CoV2, which might be a limitation. Also, our pre-defined statistical analysis plan did not include the Bayesian approach.

Authors Henning Bundgaard and Kasper Iversen’s response to Constantine Manthous Thank you for your comment. The study participants were not instructed to wear masks at home as this is not part of the authorities Public Health Recommendations. In the paper we accounted for reported diagnosed COVID-19 in the household, but of course – asymptomatic household members might have been missed. We consider that masking at home would not be realistic, so this potential limitation is after all just another reflection of the real-world setting of the trial.

Authors Henning Bundgaard and Kasper Iversen’s response to Hadi Ali, Gunce Kaya and Khameinei Ali Thank you very much for these comments. We have been as open and clear in our reporting. We agree that randomized clinical trials (RCTs) may suffer from many limitations or biases, but still RCTs are the most widely used design to obtain clinical documentation. For the same reason, more than one trial is often requested before firm recommendations are made. This relates to circumventing some of the potential biases in one study and to ensure external validation. On this basis we most certainly hope that others are perming new trials to expand our knowledge and build a stronger foundation for future recommendations.

In the paper we really tried our very best to be as judicious as possible in the conclusion.

Authors Henning Bundgaard and Kasper Iversen’s response to Edward Siguel Thank you for your interesting comments. Testing a hypothesis is the backbone of science, and although a hypothesis might be considered common sense, we still need to conduct the proper studies under the right circumstances to accept or reject a hypothesis. Here the focus is source control, i.e. whether the wearer of the face mask is protected from getting infected.

Authors Henning Bundgaard and Kasper Iversen’s response Matthew A. Spinelli, David V. Glidden, Efstathios D. Gennatas, George W. Rutherford and Monica Gandhi Thanks for these interesting comments. We agree that cluster randomization might be a good alternative to RCT’s. However, in practical terms it might be difficult to perform a face mask trial clustering; will all – or just most – citizens in the towns randomized to wear masks accept to do so? – will all – or just most – citizens in the town randomized not the wear a mask accept to do so? – there are several ethical concerns.

Furthermore, as SARS-CoV-2 spreads in clusters and the number of clusters should therefore be very large PDF
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to ensure a nonbiased result – making a cluster study even more difficult. We instructed the participants in correct use of the masks, we provided high quality masks, delivered at home, free of charge and we assessed compliance through the email surveys 4 times during the study, and the worst reported compliance was in the analyses. Our take is that compliance was very high – and most likely higher than what is seen during every-day use of face masks.

Authors Henning Bundgaard and Kasper Iversen’s response to Michael Cook In our study we assessed if masks offer a protective effect to uninfected wearers - and not if masks reduced the transmission of SARS-CoV-2 from infected mask wearers out into the community.

Authors Henning Bundgaard and Kasper Iversen’s response to Simon Thompson Thank you for these comments. Our contribution was to provide research data on efficiency of face masks.

Authorities have to include all other data and other aspects as referred to into consideration when developing the guidelines for the citizens.

Authors Henning Bundgaard and Kasper Iversen’s response to Max Longin Thank you for these comments. The participants in the mask group were recommended to wear masks when outside the home. At entry – and at end of study IgG and IgM were determined, and only participants reporting not to have or have had COVID-19 were eligible. IgG and/or IgM positive participants at baseline were excluded from the analyses. The primary outcome was a composite outcome of antibody test results, PCR and diagnosed COVID-19 in the healthcare system. COVID-19 diagnosed household members were accounted for. However, asymptomatic household members were not accounted for. The issue of before entry infection and just before end-of-study infection is true for both groups.

Authors Henning Bundgaard and Kasper Iversen’s response to Janet Rand Thank you for your comments. Our study demonstrate that “the recommendation to wear surgical masks to supplement other public health measures did not reduce the SARS-CoV-2 infection rate among wearers by more than 50% in a community with modest infection rates, some degree of social distancing, and uncommon general mask use.” As you also mention, our study also highlight that “the findings, however, should not be used to conclude that a recommendation for everyone to wear masks in the community would not be effective in reducing SARS-CoV-2 infections, because the trial did not test the role of masks in source control of SARS-CoV-2 infection.”
Despite these statements, we cannot control how our study is being interpreted.

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Authors Henning Bundgaard and Kasper Iversen’s response to Dr Rosamond A K Jones Thank you for your comments. Our aim was to provide scientific documentation for the efficiency of face masks for the wearer. We agree that masking may have a number of side effects – including psychological side effects – also in children. However, we have not assessed the psychological aspects of wearing face masks and further studies are needed to address this.

Authors Henning Bundgaard and Kasper Iversen’s response to Brenda Marfin Thank you for your comments. We are sorry to hear about your and your husbands’ situation. Our study finding is one part of the puzzle for understanding the effects of mask. We have been very clear that we studied the efficiency of masks protection for the wearer – not the effects of face masks when used by an infected individual (source control). We have made an effort to communicate the results in an objective manner and to emphasize the limitations of the study in order to accommodate the considerations you also raise. We cannot control how our study is being interpreted by individuals.

Authors Henning Bundgaard and Kasper Iversen’s response to Ambuj Kumar Thank you for the comments. Our aim was to provide scientific documentation for the protective efficiency of face masks for the wearer in addition to other protective means. The efficiency was not assessed as a dichotomous outcome – except an expected lowest outcome had to be applied in the power calculation.

Authors Henning Bundgaard and Kasper Iversen’s response to Eric Thompson Our study finding is one part of the puzzle for understanding the effects of mask. Formulation of policy recommendations should take into account all the research and knowledge available, and we leave this to the policy makers.

Authors Henning Bundgaard and Kasper Iversen’s response to El Rowan Testing adherence to recommendations in a community-based, randomized controlled trial such as this is difficult, as the real-life setting does not allow individual control. The question of true adherence will always be a question unanswered in a community-based randomized trial where the participant is the active part in carrying out the intervention – whether it be wearing a mask, taken their medicine as recommended, doing their exercise etc. - and it will in the end always depend on the honesty and selfPDF Help
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reflection of the participant. Like in most drug trials we rely on the fact that the volunteer participation motivates honest answers. But yes, we – and others - cannot be sure.

Authors Henning Bundgaard and Kasper Iversen’s response to Hans Gaines Thank you for your comments. Our study investigated the “effectiveness of adding a mask recommendation to other public health measures to prevent SARS-CoV-2 infection”. We agree that participants might have been infected at home from asymptomatic members of their household. The participants were only asked to wear masks when outside the home. We consider that this reflects the generally used recommendations as it is hard to imaging a recommendation to wear masks at home.

Authors Henning Bundgaard and Kasper Iversen’s response to Eemil Zhang Thank you for your input. The Lammers, Crusuis, Gast 2020 paper you refer to discuss that the perception of the spread – whether linear or exponentially biased – will affect the way people act on the recommendations. However, the SARS-CoV-2 infection rate was not growing exponentially in Denmark during the study period. Moreover, if the question is whether people perceive it as exponentially growth - and thus would change their behavior thereafter - this perception would be expected to be similar between the groups.

Authors Henning Bundgaard and Kasper Iversen’s response to Brendan Moran Thanks for your comments. We agree, the “lag” relating to infection late during the trial and time to seroconversion was to some extent captured by the PCR. In our sample size calculation, we applied a power of 80% with an assumed infection rate of 2% in the control group. The power was ensured as the infection rate was 2.1% in the control group, and the number of participants who finalized the study was as little higher as compared to the number needed to include according to the sample size calculation.

David Bardenstein • Ret • 2 December 2020
Paper may suggest that masks may indeed be effective.

Did not the article report that a much larger number of mask wearing subjects had Covid 19 in their households? If so, a significantly higher rate of Covid 19 infection would have been expected given the PDF
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known household transmission. Yet Covid infection despite all the other uncertainties in the protocols, was less in the masked group.

The failure of the study to have mask wearers not be “taxed” with wearing masks at home , even if there was known Covid 19 present raises scientific, public health and ethical questions. On that basis it may be due for retraction. The imprecision due to multiple uncontrolled factors similarly makes it a study, however well intentioned, that should have been rejected as it is inconclusive and does not clearly guide the path for how a useful one might be done.

Zhicheng Lin, PhD • McLean Hospital, Harvard Medical School • 2 December 2020 Maskless driving as high risk for catching coronavirus
To Editor
In the United States, the number of daily new cases with COVID-19 keeps breaking global records. After seven months of preventive measures mandated and practiced, this wrong direction should be introspecting.

COVID-19 is caused by infection with the coronavirus SARS-CoV-2 and spreading mainly via airborne transmission so that wearing face masks is the most effective prevention measure for the public(1).

However, Bundgaard et al reported a marginal and inclusive mask-based prevention from outdoor infection based on their randomized controlled trial(2). That study didn’t consider stratified outdoor time because the outdoor activity could be situational in terms of coronavirus transmission, such as gathering and driving.

Currently in the States, there is no curfew or strict lockdown. By contrast, many working places remain active at reduced density and automobiles are running all over the streets and highways day and night. Of people with face masks, approximately a half don’t wear their masks correctly in the public and most people inside their cars don’t wear masks at all.

It is safe to stay inside the car, however, can be a misperception regarding SARS-CoV-2. People usually feel safe when getting into their cars so that they take off the masks immediately once inside the cars.

Automobiles are equipped with cabin air filters which are designed to keep air pollutants such as dust and pollen out of the passenger compartment. However, these filters can trap particles only as small as 0.3~0.5 microns, with a filtration efficiency of 50–90% where the filtration effectiveness decreases with decreasing particle size.(3) Therefore, these cabin filters are not designed to filter out the coronavirus whose average size is 0.1 microns (with a range of 0.06~0.14 micron) so that inside the car is not coronavirus-proof.

Inadequate and insufficient mearing of face masks(4) may partly explain the current surges in daily new cases. In the peaking times of this pandemic, when one drives a car with air ventilated from outside, the risk of airborne transmission can be increased with the speed of the vehicle. SARS-CoV-2 in aerosols (with PDF
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sizes similar to the coronavirus) remains infectious for hours(5) so that 10-20 fold-accelerated exposure to the public air is a high risk but was neglected by the randomized trial. “The goal of reliably filtering coronavirus from a vehicle cabin has myriad challenges,” as clarified and warned by the Society of Automotive Engineers International (https://www.sae.org/news/2020/03/coronavirus-cabin-air-filtration). Maskless driving can be searching for SARS-CoV-2.

Conflict of interest: None to declare.

Funding: None.

References:

1. Zhang R, Li Y, Zhang AL, Wang Y, Molina MJ. Identifying airborne transmission as the dominant route for the spread of COVID-19. Proc Natl Acad Sci U S A. 2020;117(26):14857-63.

2. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, von Buchwald C, Todsen T, Norsk JB, et al.

Effectiveness of Adding a Mask Recommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers : A Randomized Controlled Trial. Ann Intern Med. 2020.

3. Heo K, Noh J, Lee B, Kim Y, Jung J. Comparison of filtration performance of commercially available automotive cabin air filters against various airborne pollutants. Building and Environment. 2019;161:106272.

4. Konda A, Prakash A, Moss GA, Schmoldt M, Grant GD, Guha S. Aerosol Filtration Efficiency of Common Fabrics Used in Respiratory Cloth Masks. ACS Nano. 2020;14(5):6339-47.

5. van Doremalen N, Bushmaker T, Morris DH, Holbrook MG, Gamble A, Williamson BN, et al. Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1. N Engl J Med. 2020;382(16):1564-

7. Disclosures:

None to declare.

Elena Pezzolo,1* Simone Cazzaniga,1* Silvano Gallus,2 Luigi Naldi,1 • 1.study Center of Italian Group for Epidemiological Research in Dermatology (GISED), Bergamo, Italy 2.Environmental Health Sciences Department, Istituto Ricerche Farmacologiche M.Negri, Milano, Italia • 26 November 2020 Evidence from randomized controlled trials on the surgical masks’ effect on the spread of respiratory infections in the community
Dear Editor:

In the Bundgaard et al. randomized controlled trial (RCT) , face mask use supplementing other public health measures did not significantly reduce SARS-CoV2 infection in people wearing the mask, albeit the results cannot exclude a 46% reduction or a 23% increase in infection among mask wearers. These findings 1 PDF
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seem to confirm the notion that recommendations on the public use of respiratory devices to prevent SARSCoV-2 infection have low certainty evidence.

Indirect supportive data can come from studies dealing with the protection offered by surgical masks in influenza-like illness (ILI). We conducted a systematic review and meta-analysis of RCTs (PROSPERO ID:

CRD42020178913) on the use of surgical masks in the community as a mean to prevent the spreading of ILI. The population included students and households’ members of any age and sex. The main outcome was the risk of ILI among mask users vs non-users. Eligible studies included RCTs published between January 1, 2005 and April 7, 2020 in English language. Two blinded reviewers independently screened the papers identified through a search strategy including umbrella and traditional reviews, based on PubMed/Medline and Embase libraries.

Out of 422 papers, 11 RCTs assessed the role of wearing versus not wearing surgical masks on ILI prevention. Overall, the studies enrolled a total of 7469 subjects. The pooled random effect relative risk (RR) for face mask protection was 0·92 (95% CI:0·81-1·04), suggesting that wearing surgical masks in the community confer no significant protection against ILI in mask wearers. It should be noted that most studies in our meta-analysis were underpowered, and that 73% of them reported a poor adherence of participants to mask use. A sub-analysis of few high compliance studies showed a RR of 0·67, 95% CI:0·46- 0·99.

Notably, the type of mask and the securing system may largely influence the filtering effectiveness of face masks, with surgical or procedural masks secured with elastic ear lobes showing the least filtration efficiency.

At variance with observational studies, randomised trials have failed, up to now, to clearly document the utility of wearing masks to prevent SARS-CoV2 infection. A public health intervention promoting face mask use, is usually implemented at units larger than that of individuals. Hence, we suggest that a convenient study design would be a cluster randomised trial assessing, in a factorial way, the impact of promoting the combination of different components of individual protection on the prevention of SARS-CoV2 spreading.

References

1. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of adding a mask recommendation to other public health measures to prevent SARS-CoV-2 infection in Danish mask wearers: a randomized controlled trial. Ann Intern Med. 2020 Nov 18. doi: 10.7326/M20-6817.

2. Chu DK, Akl EA, Duda S, et al. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and metaanalysis. Lancet. 2020;395(10242):1973-1987.

3. Lugo A, Bosetti C, Peveri G, et al. Dose-response relationship between cigarette smoking and sitespecific cancer risk: protocol for a systematic review with an original design combining umbrella and traditional reviews. BMJ Open. 2017; 7(10): e018930. 2 3
4 PDF
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4. Sickbert-Bennett EE, Samet JM, Clapp PW, et al. Filtration Efficiency of Hospital Face Mask Alternatives Available for Use During the COVID-19 Pandemic. JAMA Intern Med. 2020 Aug 11:
e204221. Doi: 10.1001/jamainternmed.2020.4221.

Corresponding author:

Prof. Luigi Naldi
Study Center of the Italian Group for Epidemiological Research in Dermatology (GISED) Via Clara Maffei 4, 24121 Bergamo (Italy)
Tel. +39035223753
e-mail [email protected]
Wolfgang Uter, M.D. • Dept. of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander University Erlangen/Nürnberg, Germany • 29 November 2020
Another possible source of bias
Dear Editor:

Performing a large intervention study on the population level is surely a huge effort, and the authors must be applauded for setting out to assess the effectiveness of “medical” type face masks in addition to measures of social distancing in preventing SARS-CoV-2 infection. Thereby, they followed a conclusion from a recent meta-analysis on the topic, which had found a clear indication of a protection from virus transmission by - particularly N95 or surgical quality - face masks, but noted considerable uncertainty of evidence [1].

The randomised controlled trial design chosen is undisputedly the gold standard method in clinical research addressing interventions. However, its application in a population setting instead of a relatively well-controlled, quasi experimental clinical setting is not without pitfalls, some of which have already been outlined by other scientific comments. Another particular confounding effect related to the intervention not being amenable to blinding, and also biasing the results towards “no effect”, is the possibility that participants in the intervention group may have changed their relevant behaviour once wearing masks, notwithstanding similar behaviour at baseline. Such a change would most plausibly happen in terms of respecting less the fundamental rules of social distancing, feeling protected well enough by the face mask, thereby increasing infection risk.

From a general perspective, the DANMASK-19 study results, independent from other issues likely biasing the results towards “no effect” as discussed in other comments, cannot quantify efficacy, i.e. the maximum possible effect of an intervention, but effectiveness, i.e., the intervention effect observed under “real life conditions”. Effectiveness is often (much) smaller than efficacy, owing to manifold interferences, perhaps including the confounding effect suggested above. As “real life conditions” largely mean the societal and PDF
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historical context, the following conclusions can be drawn: (i) effectiveness as observed in the study cannot be easily generalised; (ii) efficacy of wearing adequate masks adequately is underestimated by the current results, to an unknown extent; (iii) contrary to clinical interventions, the (individually) randomised controlled trial cannot necessarily be regarded as gold standard to assess efficacy on the population level. [1] Derek K Chu, Elie A Akl, Stephanie Duda, Karla Solo, Sally Yaacoub, Holger J Schünemann, COVID-19 Systematic Urgent Review Group Effort (SURGE) study authors. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. Lancet 2020 Jun 27;395(10242):1973-1987
Dr Joseph Hutchinson • St. George's Hospital, London • 29 November 2020 Data raise concerns about mask-wearing causing potentially harmful reductions in physical activity
Dear Editor,
This randomised control study by Bundgaard et al. did not find face-mask wearing to have a significant effect on SARS-COV2 infection. However, the data indicate a concerning decrease in levels of physical activity among the mask-wearing cohort, which the article does not explore.

The results of the tertiary end points published in the supplementary material suggest that levels of physical activity decreased in 40% of the mask-wearing cohort. This potential effect of mask wearing is worthy of further study. Unfortunately, the decrease in physical activity reported in this trial cannot be compared to a control as the non-mask-wearing cohort were not asked about their level of exercise in the study period. Also, trial participants were not asked to quantify the change in their physical activity, which would indicate how much of a concern this decrease should raise.

The WHO Global Action Plan on Physical Activity 2018-2030 highlights physical inactivity as a major cost to health systems and society due to resultant ill health. If mask wearing results in reduced levels of physical exercise, and therefore worse physical health, this risk should be taken into account both by individuals and those responsible for health policy.

Additionally, results regarding levels of sick leave and bacterial infection in the two groups have yet to be published. May I ask when the authors expect this information to become available? Elena Pezzolo 1, Simone Cazzaniga 1, Silvano Gallus 2, Luigi Naldi 1 • 1.Study Center of Italian Group for Epidemiological Research in Dermatology (GISED), Bergamo, Italy 2.Environmental Health Sciences Department, Istituto Ricerche Farmacologiche M.Negri, Milano, Italia • 26 November 2020 Evidence from randomised controlled trials on the surgical masks’ effect on the spread of respiratory infections in the community
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Dear Editor:

In the Bundgaard et al. randomized controlled trial (RCT) , face mask use supplementing other public health measures did not significantly reduce SARS-CoV2 infection in people wearing the mask, albeit the results cannot exclude a 46% reduction or a 23% increase in infection among mask wearers. These findings seem to confirm the notion that recommendations on the public use of respiratory devices to prevent SARSCoV-2 infection have low certainty evidence.

Indirect supportive data can come from studies dealing with the protection offered by surgical masks in influenza-like illness (ILI). We conducted a systematic review and meta-analysis of RCTs (PROSPERO ID:

CRD42020178913) on the use of surgical masks in the community as a mean to prevent the spreading of ILI. The population included students and households’ members of any age and sex. The main outcome was the risk of ILI among mask users vs non-users. Eligible studies included RCTs published between January 1, 2005 and April 7, 2020 in English language. Two blinded reviewers independently screened the papers identified through a search strategy including umbrella and traditional reviews, based on PubMed/Medline and Embase libraries.

Out of 422 papers, 11 RCTs assessed the role of wearing versus not wearing surgical masks on ILI prevention. Overall, the studies enrolled a total of 7469 subjects. The pooled random effect relative risk (RR) for face mask protection was 0·92 (95% CI:0·81-1·04), suggesting that wearing surgical masks in the community confer no significant protection against ILI in mask wearers. It should be noted that most studies in our meta-analysis were underpowered, and that 73% of them reported a poor adherence of participants to mask use. A sub-analysis of few high compliance studies showed a RR of 0·67, 95% CI:0·46- 0·99.

Notably, the type of mask and the securing system may largely influence the filtering effectiveness of face masks, with surgical or procedural masks secured with elastic ear lobes showing the least filtration efficiency.

At variance with observational studies, randomised trials have failed, up to now, to clearly document the utility of wearing masks to prevent SARS-CoV2 infection. A public health intervention promoting face mask use, is usually implemented at units larger than that of individuals. Hence, we suggest that a convenient study design would be a cluster randomised trial assessing, in a factorial way, the impact of promoting the combination of different components of individual protection on the prevention of SARS-CoV2 spreading.

References

1. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of adding a mask recommendation to other public health measures to prevent SARS-CoV-2 infection in Danish mask wearers: a randomized controlled trial. Ann Intern Med. 2020 Nov 18. doi: 10.7326/M20-6817.

2. Chu DK, Akl EA, Duda S, et al. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and metaanalysis. Lancet. 2020;395(10242):1973-1987. 1 2
3 4
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7/21/22, 10:25 AM Effectiveness of Adding a MaskRecommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish MaskWea… https://www.acpjournals.org/doi/10.7326/M20-6817 47/58

3. Lugo A, Bosetti C, Peveri G, et al. Dose-response relationship between cigarette smoking and sitespecific cancer risk: protocol for a systematic review with an original design combining umbrella and traditional reviews. BMJ Open. 2017; 7(10): e018930.

4. Sickbert-Bennett EE, Samet JM, Clapp PW, et al. Filtration Efficiency of Hospital Face Mask Alternatives Available for Use During the COVID-19 Pandemic. JAMA Intern Med. 2020 Aug 11:
e204221. Doi: 10.1001/jamainternmed.2020.4221.

ANTONIO C BANDEIRA • Director, Brazilian Society of Infectious Diseases • 25 November 2020 Multiple bias towards the Null
Any study to evaluate the effectiveness of wearing masks should be done with a very careful methodological approach in order to avoid multiple sources of error. We have learned so far that the risk of SARS-CoV-2 infection through the respiratory route is very high specially at home, at lunch and coffeebreak times, where nobody uses any mask protection. In this randomized open trial, there was no control over these sources of infection. Besides, only 46% of participants wore the mask as recommended, a very low adherence level. With that in mind, I would expect the results to be biased towards no association between the use of masks and the risk of SARS-CoV-2 infection as the authors stated Tuan Nguyen • Garvan Institute of Medical Research • 23 November 2020 A Bayesian interpretation of the effect of face mask on SARS-Cov-2 infection Dear Editor:

I would like to offer an alternative interpretation of the DANMASK-19's data [1]. My interpretation centers on the question: what is the probability that face mask wearing reduces the risk of SARS-Cov-2 infection.

This question can only be answered by a Bayesian approach that updates our pre-existing knowledge with new evidence [2].

Our pre-existing knowledge is informed by a recent meta-analysis which shows that surgical face mask is associated with a 13% reduction in the risk of acute respiratory infection (risk ratio [RR], 0.87; 95% confidence interval [CI], 0.74 to 1.04) [3]. Note that the average risk reduction reported in this metaanalysis is statistically comparable with that observed in the DANMASK-19 study (i.e., 18% risk reduction; RR, 0.82; 95% CI, 0.54 to 1.23).

When the distribution of relative risks obtained from the meta-analysis [3] is updated by the DANMASK- 19's relative risk [1] by the Bayesian theorem [4], the new relative risk is 0.85, with 95% credible interval ranging from 0.72 to 0.99. Moreover, the probability that face mask wearing reduces the risk of SARS-Cov-2 infection by at least 50% is zero. Nevertheless, there is a 93% chance that face mask wearing reduces the risk SARS-Cov-2 infection by at least 5%.

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Thus, in settings with moderate Covid-19 infection (such as Denmark) the updated evidence suggests that wearing face mask may modestly protect the wearers from infection with SARS-Cov-2.

References:
[1] Bundgaard H, et al. Effectiveness of Adding a Mask Recommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers: A Randomized Controlled Trial. Ann Int Med 18/11/2020.
[2] Ferreira D, et al. Theory and practical use of Bayesian methods in interpreting clinical trial data: a narrative review. Br J Anaesth. 2020;125(2):201-7.
[3] Wang MX, et al. Effectiveness of Surgical Face Masks in Reducing Acute Respiratory Infections in NonHealthcare Settings: A Systematic Review and Meta-Analysis. Front Med 2020;7:564280. [4] R codes available here: https://github.com/tuanvnguyen/Bayesian-analysis/blob/main/NormalNormal%20model Constantine Manthous • Yale New Haven Health • 21 November 2020 Masks didn't work? Not so fast
In the November 18 issue of Annals, Bundgaard et al conclude: “The recommendation to wear surgical masks to supplement other public health measures did not reduce the SARS-CoV-2 infection rate among wearers . . . (1)“ Not so quick. Study subjects were not required to wear masks at home. Their family members/visitors were neither taxed to wear masks in public nor were they tested for asymptomatic Covid, which is often spread in homes (2). Accordingly, it is plausible, if not likely, that some study subjects caught Covid in their own homes. This critical design flaw prevents any conclusion about the efficacy of masks for preventing Covid; a nuance that will be lost on non-scientists. Nonetheless, the erroneous conclusion was immediately trumpeted, using the imprimatur of Annals, to challenge maskwearing. The effect – albeit inadvertent – is almost certain to be greater morbidity and mortality.

1. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, von Buchwald C, Todsen T, Norsk JB, et al.

Effectiveness of adding a mask recommendation to other public health measures to prevent SARSCoV-2 infection in Danish mask wearer. A randomized controlled trial. Ann Intern Med 2020 Nov 18. doi: 10.7326/M20-6817.

2. Qin-Long J, Ming-Jin L, Zhou-Bin Z, Li-Qun F, Jun Y, An-Ran Z, et al Household secondary attack rate of COVID-19 and associated determinants in Guangzhou, China: a retrospective cohort study. The Lancet Inf Dis 2020: 20; 1141-1150.

3. Davidson J. Major study finds masks don’t reduce cOVID-19 infection rates. The Federalist 2020https://thefederalist.com/2020/11/18/major-study-finds-masks-dont-reduce-covid-19-infectionrates/ last accessed November 21, 2020.

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Hadi Ali, MS , Gunce Kaya, MPhil [1], Khameinei Ali, MD, MBA [2][3] • [1] Ferkauf Graduate School of Psychology: Yeshiva University [2] Northwell Health [3] Zucker School of Medicine at Hofstra/ Northwell • 22 November 2020 Regarding "Effectiveness of Adding a Mask Recommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers" We commend the authors of the study on broaching a much-debated subject in the current environment.

The trial was designed to obtain the most power to detect a difference. Unfortunately, there were confounding variables that were unaccounted for and unmeasured.

There is a flaw in primary outcome ascertainment. False-negative rate and false positive rate of antibody testing, PCR, and diagnosis all vary widely. For example, sensitivity (IgM and IgG) of the antibody kit in this study (86.7% and 66.7%, respectively) is equivalent to a 64.6% PPV with a 5.0% prevalence [1]. This is even more pertinent in the low prevalence (1.2%) Danish population [2], [3].

Individuals who could not correctly perform the test were assumed negative, which would further skew the data. Additionally, the intention group attrition was higher than the control group (638 vs. 524). The characteristics of the study participants’ households would heavily affect the data set as well. If family or house members were COVID-19 positive, mask-wearing outside of their homes would not protect them from their highest risk source (their homes).

We contest that an intent-to-treat analysis is inappropriate, given the authors’ own published intervention adherence rate (46%). Multiple imputation analysis is simply an amplification of the data set and agreement between the original data set is a moot point. The homogeneous Danish population would make it difficult to externally validate this to other much more heterogeneous populations (i.e. New York).

It is questionable if the study is a true RCT as it lacked blinding and utilized a self-reported and selfmeasured primary outcome which opens it up to a majority of biases. Although the researchers cited their study for the equivalence of self-testing with healthcare professional testing, this may be inappropriate for research purposes and better suited for pandemic infection control [5].

Although the goal of the study was to publish the researchers’ heard-earned data, contextualization in these volatile times is paramount. This study received 90,000 tweets by 60,000 users within 4 days of publication [4]. The majority of these tweets championed the study as evidence of the impotence of masks in the control of the COVID-19 pandemic. The authors of the study would agree that this is a gross misinterpretation of the research, which further points to the fact that the wording of the conclusion should have been chosen slightly more judiciously.

References:
[1] Serology Test Evaluation Report for “Livzon IgM/IgG Diagnostic Kit for IgM/IgG Antibody to Coronovirus (SARS-Cov-2) Lateral Flow” from Zhuhai Livzon Diagnostics Inc. Food and Drug Administration website.

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Updated June 10, 2020. Accessed November 22, 2020
https://www.accessdata.fda.gov/cdrh_docs/presentations/maf/maf3285-a001.pdf [2] COVID-19 surveillance. Current data on the development of coronavirus/COVID-19. Danish Health Authority website. Updated November 20, 2020. Accessed November 22, 2020.https://www.sst.dk/en/english/corona-eng/status-of-the-epidemic/covid-19-updates- statistics-andcharts [3] Denmark Population (Live). Worldometer website. Updated, November, 22, 2020. Accessed November 22, 2020. https://www.worldometers.info/world-population/denmark-population/ [4] Article metrics. Annals of Internal Medicine website. Updated November 22, 2020. Accessed November 22, 2020. https://annals.altmetric.com/details/94531651/twitter [5] McCulloch DJ, Kim AE, Wilcox NC, et al. Comparison of Unsupervised Home Self-collected Midnasal Swabs With Clinician-Collected Nasopharyngeal Swabs for Detection of SARS-CoV-2 Infection. JAMA Netw Open. 2020;3(7):e2016382. doi:10.1001/jamanetworkopen.2020.16382 Disclosures:

No disclosure to claim.

Edward Siguel, MD, PhD • Self employed in biomedical research, MD, USA. • 23 November 2020 Thought experiments and science predict that facemasks reduce viral loads and reduce severity of infection
The study is misleading; it did not consider adequately too many critical variables (factors) that have major impact on measured outcomes. Thought experiments from science predict that facemasks reduce viral loads and severity of infection.

Statistics describe outcomes, but does not explain causes. It is impossible to conduct experiments on all possible observations and outcomes, and it is not necessary. We can use “thought experiments”, which Einstein used to create Relativity. We had data on the movement of planets for over 100 years, but it took “thought” experiments for Newton to predict planetary movement via equations.

We understand enough about viruses to know the body produces and expels them, mostly via mouth and nose. We know an infected person can expel many viruses. A well-designed mask, and substantial obstruction, will reduce the number of virus expelled far into the air. A mask will absorb viruses. This is not “genius” physics. I knew about it since I was about 6 yo. My parents taught me to use a handkerchief, hold it to my nose, to prevent spreading “stuff” when I cough. It worked. There is no doubt that holding a paper towel or similar paper or cloth to the mouth reduces the amount of “stuff” going out when I cough.

To those who doubt it and need more “studies”, I propose they put themselves in front of people coughing without covering their mouth. Although it may not infect them, the fluids they get in the face and mouth PDF
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will provide evidence of how facemasks work.

Thus, a thought experiment and science provide probative evidence that facemasks can reduce the amount of “stuff” an infected person sends to the air. How much of a reduction depends on the nature of the facemask, how tight it is, how much it absorbs and retains fluid, etc. If everybody used facemasks in public places, viral loads in public places are reduced.

We do not need more studies of the obvious; we do not need a sample size of 1,000 people thrown out of 10 story windows to predict broken bones when they hit the concrete sidewalk. If a study of 10,000 people who took Vitamin EZY434 proved they fly like birds, I would not believe it because my thought experiment says it cannot be true.

Similarly, facemasks reduce particles absorbed from air. Known for years in construction, surgery, labs, etc.

Matthew A. Spinelli, David V. Glidden, Efstathios D. Gennatas, George W. Rutherford, Monica Gandhi • Departments of Medicine and Epidemiology, University of California, San Francisco • 20 November 2020 Cluster randomization and adherence assessment are needed to test masks’ true potential
We read with interest the study evaluating mask mandates in Denmark by Bundgaard and colleagues. We commend the authors for performing a randomized trial of a non-pharmaceutical intervention in the midst of the pandemic. However, the study makes it difficult to draw conclusions about the impact of masks in preventing incident infection or severe COVID-19. Although masks were provided and recommended to participants, masking was not commonplace in Denmark at the time, and 14% of participants reported experiencing social harms due to masking. Only 46% of participants reported wearing a mask as recommended, and overreporting of adherence, as has been seen in previous prevention studies for stigmatizing interventions, likely occurred. Notably, due to the complexity of interpreting self-reported adherence, HIV and sexually-transmitted infection prevention trials are now designed to incorporate objective assessment of adherence.

The study would have benefitted from inclusion of implementation science principles: understanding the desired behavior in its social context, cluster randomization, and assessment of intervention fidelity.

Recommending a potentially stigmatizing intervention in a minority of individuals within a community is, we believe, a major flaw in a study designed to evaluate a policy intervention. Cluster randomization would have allowed an entire community to be randomized to the recommendation, minimizing social harms to the individual and likely increasing intervention adherence. Assessment of intervention fidelity and acceptability, such as through direct observation within the community, would allow a more accurate interpretation of self-reported adherence data.

Use of cluster-randomization has other benefits. Masks are likely to be more effective in preventing forward transmission, in the context of high community uptake and adherence. By randomizing isolated th
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members in the community to the mask recommendation, this study design cannot answer if “masks protect you.” Second, given the high proportion of asymptomatic COVID-19 infections, we do not know how many individuals were infected within their household bubbles. An optimal design would pursue a cluster-randomized approach, with sufficient power to detect incident (with PCR) rather than prevalent (with serology) infections, and assess disease severity via cataloging clinical outcomes (do masks lead to less severe infections via reduced inoculum? ). A mask recommendation for isolated members of a community is unlikely to be effective. We suggest that future studies assess the impact of recommendations to wear masks at the community-level, which will be more informative for public health officials trying to stem transmission and disease while awaiting an effective and widely available vaccine.

1. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of Adding a Mask Recommendation to Other Public Health Measures to Prevent SARS-CoV-2 Infection in Danish Mask Wearers : A Randomized Controlled Trial. Ann Intern Med 2020.

2. Marrazzo JM, Ramjee G, Richardson BA, et al. Tenofovir-based preexposure prophylaxis for HIV infection among African women. N Engl J Med 2015;372:509-18.

3. Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implement Sci 2013;8:139.

4. Wenger DS, Triplette M, Crothers K, et al. Incidence, Risk Factors, and Outcomes of Idiopathic Pneumonia Syndrome after Allogeneic Hematopoietic Cell Transplantation. Biol Blood Marrow Transplant 2020;26:413-20.

5. Gandhi M, Beyrer C, Goosby E. Masks Do More Than Protect Others During COVID-19: Reducing the Inoculum of SARS-CoV-2 to Protect the Wearer. J Gen Intern Med 2020;35:3063-6.

Michael Cook • Vis a vis symposiums • 22 November 2020
Authors state major limitations of study
The authors state the limitations of the study: Inconclusive results, missing data, variable adherence, patient-reported findings on home tests, no blinding, and no assessment of whether masks could decrease disease transmission from mask wearers to others. Asian countries have very low levels of COVID and for decades people wear mask if they think they have flu or a cold. The authors clearly state they could not assess this.

Simon Thompson • Independent researcher • 22 November 2020 This is extremely inadequate research to support forcing the entire world to wear masks
Before making any recomendations to wear masks adequate research would be needed but this hasn't occured. Whilst such measures are often described as a recommendation in the real world people are being forced to wear masks and in some countries quite agressively. This study finds no significant effects in relation to the alleged Sars-cov2 but does not look at the many other possible effects of wearing these. 4 5
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For example there has been a doubling in shootings in NY this year. Could the masks be contributing to this? What are the effects on overall health? What are the dangers of conditioning people to accept forced medication in violation of informed consent laws? Without having done any proper research to establish the long term effects it is incredibly reckless to be forcing masks on the entire world and this study shows how little is known about it. It is time to immediately end these impositions and any further experimentation on the public.

Max Longin • Dipl.Math., Denmark, private • 23 November 2020 This study design would not even proof that a 100% protection has a protective effect Imagine a 100% perfect protection against COVID-19 (a hermetic room), what outcome should be expected for this by-definition safe group using this study design? Here is the math only for estimating
- the false-positive antibody-tests
- positive test due to before-baseline infections
But as the study design grants protection at average only 4.5 hours/day further infections outside the room (in the study false-classified as noneffective protection) should be added to the calculated expectations.

The study reports antibody testing has an estimated 99,2% specificity. For about 2400 tests this leads to an expectation of 2400*0.008=19 false-positive tests in each antibody test group.

IgG-antibodies form very delayed and persist very long. So in non-increasing rate of new infections (as the case in 05/2020 in Denmark) about 80% of all true-positive IgG tests at study-end show infections before study-baseline. So the expectation of positive tests due to before-baseline infections in the control group is

10.4 (80% of 13 (=32-19) „true-positive“ IgG tests)
The mentioned false-detection arises solely by a test-property (specificity) and before-baseline events, so the expectations for the control group for false-positive test (19) and for true-positive tests due to beforebaseline infections (10.4) equals the expectations for the safe group, adding up to: expectation(IgGSafeGroup)=29.4 IgM-tests respond from >2-6 weeks after infection. So about 50% of the IgM true positive tests are likely due to before-baseline infections. Analogue to above 19 false positive and 9 positive IgM tests (50% of 18 (=37-19) „true-positive“ IgM tests) due to before-baseline infections sum up to: expectation(IgMSafeGroup)=29 PCR-tests hardly suffer from specifity and time lags in the study, so no positive PCR-tests should be expected in the safe group: expectation(PCR-SafeGroup)=0 PDF
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A temporally evenly distributed health care diagnosis during study will again suffer from the delay from infection to diagnosis (first 9 days (=30% of 30 days) diagnosis will likely show before-baseline infections).

So 0,3*10=3 cases are likely due to before-baseline infections and have to be expected for the safe group as well: expectation(HealthCare-SafeGroup)=3
Even without additional expected infections at home, friends etc. - falsely assigned as inside the hermetic room the expected outcome in the by-definition safe group is already about 75% of the control outcome (or 90% of the face-mask-group).

Altogether this study design expects for a by-definition 100%-protection:
- measure an Odd Ratio of ≥0.75 (≤25% protection),
- include OR=1 (i.e. no-protection-at-all) in the 95%-Confidence Interval and - exclude OR≤0.4 (≥60% protection) from 95%-CI
Janet Rand, OD • Concerned US citizen • 20 November 2020 Mis-leading study . Results need to be made more clear.*” Exposure was to persons NOT wearing masks”*
This study does NOT show that mask wearing in ineffective in mitigating the spread of Corona Virus / COVID-19 / SARS-CoV-2. It shows (what we already knew) that wearing a mask does not protect the person wearing the mask as much as we would like. The reason you wear a mask is to keep your viral particles to yourself - don't spread them to others. Unfortunately, anti-maskers are using this study as "prof" that they don't need to wear masks. This is irresponsible and should be made clear in the title of the study. From the discussion: "The findings, however, should not be used to conclude that a recommendation for everyone to wear masks in the community would not be effective in reducing SARS-CoV-2 infections, because the trial did not test the role of masks in source control of SARS-CoV-2 infection. During the study period, authorities did not recommend face mask use outside hospital settings and mask use was rare in community settings (22). This means that study participants' exposure was overwhelmingly to persons not wearing masks."
Dr Rosamond A K Jones • #UsforThemUK • 18 November 2020 Will mandatory mask usage be scaled back in light of these results? Dr Bundgaard and colleagues are to be congratulated on this well-constructed randomised trial, at a time when much policy has been based on weak observational or laboratory-based studies. Their results highlight the dilemma that lack of evidence for benefit is unlikely to alter public policy. The suggestion that mask wearing is for the protection of others, rather than of the wearer, has created a climate of discrimination against those with genuine medical exemptions. This is especially worrying when applied PDF
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to school children, known to play a very small role in transmission of Sars-Cov-2. In particular, the creeping use of masks in classrrooms in the UK, has resulted in many reports of children feeling alienated and unable to understand their teachers. Parents of primary school children are being instructed to wear masks when collecting their children from the school playground, giving children a potent message that they and their parents are all a danger to one another. The long-term mental health impacts of this are yet to be fully realised.

Brenda Marfin • Not affiliate. I have a Ph.D. In educational leadership • 18 November 2020 Mis-representation of research purpose
Members of the general public are referencing this research as a battle cry that communities do not need to wear masks in public. After reading the entire article, I ascertained that telling the general public to stop wearing masks was not the purpose or outcome of this research.

During these tumultuous times it might be a moral imperative to include some type of explanation with this research. Very few individuals outside of the medical profession will take the time to thoroughly read the article and analyze the outcomes.

Sincerely,
Brenda Marfin, Ph.D.

Unassociated at this time while caring for my husband with end stage renal disease and Alzheimer's. I depend on the kindness (and myself) of others to wear a mask.

Ambuj Kumar, MD, MPH • Professor, Department of Internal Medicine Director, Morsani College of Medicine, University of South Florida, Tampa • 19 November 2020
In absence of an objective mechanism to track the intervention what are we counting? The effort by Dr. Bundgaard and colleagues is commendable. However, the trial design and the associated results remind me of the randomized controlled trials assessing the efficacy of a "prayer" intervention. The fundamental issue with mask intervention and social distancing, like prayer, is the lack of objective mechanisms to ensure and track compliance or non-compliance (lack of an accurate method to track who is praying or not praying). As an example, the authors state that only "46% of participants wore the mask as recommended" in the mask group but failed to ask participants in the no mask group about their usage of the mask. Furthermore, a mask is considered an added layer of protection with social distancing and therefore the mask's added effects would be challenging to deduce. Accordingly, given this basic challenge of delivering an intervention without tracking/confirmation mechanism, the results, at best, can be considered anecdotal. The desire for evidence from a randomized controlled trial for an intervention question is understandable. However, logistical challenges associated with the reliable implementation of the intervention (i.e., mask) and tracking of adherence makes the conduct of a randomized trial to assess PDF
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the efficacy of mask a non-starter. The efficacy of a mask needs to be framed in the context of reducing the risk and not binary choices of works or does not work.

Eric Thompson • Independent Researcher • 18 November 2020 Please *clarify* your policy recommendations
In light of your recent research, will you please clarify your policy recommendations? Thank-you El Rowan • Private • 19 November 2020
Tested recommendation, not adherence to recommendation
While I commend the researchers and it does demonstrate whether recommending masks provides benefit, the experiment does not demonstrate whether mask-wearing actually took place. Research in other arenas has shown people are not honest when providing answers to surveys, and these people would have likely had reason to be less than honest about the frequency with which they wore a mask and the coverage of their mouth and nose while wearing one. It may be better to find people with serious concern about NOT wearing a mask to act as the experimental group, and those who are entirely opposed to maskwearing as the control group. This would be answer the question of whether wearing a mask provides benefit. I think people are misunderstanding the intent of this study, which was to test the power of recommendation with the hope that those in the experimental group would be honest in their responses.

We will never know if they were honest or used the masks properly.

Hans Gaines • Karolinska Institute, Stockholm, Sweden • 18 November 2020 Risk for bias?
An important large-scale study investigating the benefit of bearing a mask to reduce the risk of aquiring COVID-19 during an daily average of 4,5 hours stay outside the home during one month.

To be able to do that, one must eliminate the possible bias that the participants are instead infected during the daily 19,5 hours they stay at home.

A total of 52 participants in the mask group and 39 control participants reported COVID-19 in their household. Of these, 2 participants in the face mask group and 1 in the control group developed SARS-CoV2 infection…' However, more participants may have been exposed and infected by household members, without participants reporting COVID-19 in their household, if the members experienced asymptomatic infection or only mild disease, not suspected to be due to COVID-19.

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The possible inclusion of misdiagnosed subjects - infected trough household contact but estimated as infected during outside the home should influence both groups - with or without masks - equally. And the true difference between the groups, and thus the benefit of wearing a mask, should increase if this bias had been controlled, although with wide confidence intervals, due to the relatively low number of infection.

The reported finding of only 3% (3/95) infected through household contacts during the study appear to be surprisingly low, supporting the proposed risk for bias, due to misdiagnosis.

Eemil Zhang • Independent Researcher • 18 November 2020 Perceptual error in viewing COVID-19 spread as linear, not exponential.

In the discussion section the authors state that "Testing at the end of follow-up, however, may not have captured any infections contracted during the last part of the study period, but this would have been true in both the mask and control groups and was not expected to influence the overall findings.". This statement assumes a linear spread of infection among both groups. COVID-19 however has been spread exponentially (Lammers, Crusuis, Gast 2020). As such infections contracted during the last part of the study period would be largely significant to the overall findings.

Brendan Moran • NHS COVID Clinical Assessment Service • 19 November 2020 Timing is everything
This study pooled participants from two cohorts split two weeks apart in the months following the peak of first wave of infections in Denmark.

Self-reported pre-study baseline seropositive prevalence was 1.7% and these participants were excluded from the study.

Of those with unknown baseline seropositivity, 2% were positive at the end of the study.

Of those with known baseline seropositivity, around 1.7% appear to have seroconverted during the month of the study.

Do these very similar percentages spread across time raise concerns about the false positive rate of the self-reported antibody test used in a low prevalence population? Even without false positive rate, to achieve 80% sensitivity, this lateral flow antibody test has to be performed at least 15 days after symptom onset. It takes an average of 5-6 days to develop symptoms following exposure, so this creates at least a 3 week lag. Given the study only lasted 1 month in each PDF
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cohort, any protective effect of mask-wearing will be diluted by late sero-conversions infected prior to the study. This effect will be balanced in the control group, but still increases the OR towards 1 even if masks were having an effect when both groups are pre-loaded equally. Taking this into account and any poststudy seroconversions missed in the control group could possibly have led to a significant result. The PCR and clinically diagnosed outcomes will not suffer from this lag so much, and it is noteworthy that mask wearers scored 0 and 5 cases respectively versus 5 and 10 for controls, whilst IgG seropositivity was higher than IgM in mask wearers and vice versa in controls.

The study was also underpowered for detecting a protective-to-wearer effect of somewhere less than 50% which could be a more reasonable estimate of efficacy.
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