Association of country-wide coronavirus mortality with demographics, testing,
lockdowns, and public wearing of masks (Update August 4, 2020).
Christopher T. Leffler, MD, MPH.1,2 *
Edsel Ing MD, MPH, CPH, MIAD.3
Joseph D. Lykins V, MD.4,5
Matthew C. Hogan, MS, MPH.6
Craig A. McKeown, MD.7
Andrzej Grzybowski, MD, PhD, MBA.8,9
1. Department of Ophthalmology. Virginia Commonwealth University. Richmond, VA 23298.
2. Department of Ophthalmology. Hunter Holmes McGuire VA Medical Center, Richmond, VA.
3. Department of Ophthalmology & Vision Sciences, University of Toronto.
4. Department of Internal Medicine, Virginia Commonwealth University. Richmond, VA 23298.
5. Department of Emergency Medicine. Virginia Commonwealth University. Richmond, VA 23298.
6. School of Medicine, Virginia Commonwealth University, Richmond, VA 23298.
7. Bascom Palmer Eye Institute, University of Miami, Miller School of Medicine.
8. Department of Ophthalmology, University of Warmia and Mazury, Olsztyn, Poland.
9. Institute for Research in Ophthalmology, Poznan, Poland.
*Corresponding author: Christopher T. Leffler, MD, MPH.
Department of Ophthalmology. Virginia Commonwealth University. 401 N. 11th St., Box 980209,
Richmond, VA 23298. email@example.com.
August 4, 2020.
None of the authors has any conflicts of interest to disclose.
Purpose. To determine sources of variation between countries in per-capita mortality
from COVID-19 (caused by the SARS-CoV-2 virus).
Methods. Potential predictors of per-capita coronavirus-related mortality in 200
countries by May 9, 2020 were examined, including age, sex, obesity prevalence,
temperature, urbanization, smoking, duration of infection, lockdowns, viral testing,
contact tracing policies, and public mask-wearing norms and policies. Multivariable
linear regression analysis was performed.
Results. In univariate analyses, the prevalence of smoking, per-capita gross domestic
product, urbanization, and colder average country temperature were positively
associated with coronavirus-related mortality. In a multivariable analysis of 196
countries, the duration of infection in the country, and the proportion of the population
60 years of age or older were positively associated with per-capita mortality, while
duration of mask-wearing by the public was negatively associated with mortality (all
p<0.001). International travel restrictions and a lower prevalence of obesity were
independently associated with mortality in a model which controlled for testing policy.
Internal lockdown requirements and viral testing policies and levels were not associated
with mortality. The association of contact tracing policy with mortality approached
statistical significance (p=0.06). In countries with cultural norms or government policies
supporting public mask-wearing, per-capita coronavirus mortality increased on average
by just 15.8% each week, as compared with 62.1% each week in remaining countries.
Conclusions. Societal norms and government policies supporting the wearing of masks
by the public, as well as international travel controls, are independently associated with
lower per-capita mortality from COVID-19.
The COVID-19 global pandemic caused by infection with severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2) has presented a major public health
challenge. For reasons that are not completely understood, the per-capita mortality
from COVID-19 varies by several orders of magnitude between countries.1 Numerous
sources of heterogeneity have been hypothesized. Higher mortality has been observed
in older populations and in men.2,3 Patient-level behaviors, such as smoking, might also
have an impact.3 Other potentially relevant factors include economic activity, and
environmental variation, such as temperature.4 More urban settings and increased
population density would be expected to enhance viral transmission.5
In addition, public health responses to the COVID-19 pandemic may influence
per-capita mortality. Various strategies have been implemented, ranging from robust
testing programs to lockdown or stay-at-home orders, to mandates regarding social
distancing and face mask usage. Practices with theoretical benefit, such as social
distancing, stay-at-home orders, and implementation of mandates regarding use of
masks in public spaces, must be assessed quickly, as implementation has the potential
to reduce morbidity and mortality.
Mask usage by the public is postulated to decrease infection by blocking the
spread of respiratory droplets,1 and was successfully implemented during other
coronavirus outbreaks (i.e. SARS and MERS).6 In the context of the ongoing pandemic,
we assessed the impact of masks on per-capita COVID-19-related mortality, controlling
for the aforementioned factors. We hypothesized that in countries where mask use was
either an accepted cultural norm or favored by government policies on a national level,
the per-capita mortality might be reduced, as compared with countries which did not
In order to be included in the study, countries had to: 1) have coronavirus mortality data
listed in the publicly available Worldometer Database on May 9, 2020;7 2) have dates of
first case and first death reported by the European Centre for Disease Prevention and
Control (which did tabulate worldwide data);8 and 3) have an assessment of viral testing
through May 9, 2020 by either: 3a) report on Worldometer of numbers of coronavirus
PCR tests performed,7 or: 3b) testing and lockdown policies graded by the University of
Oxford Coronavirus Government Response Tracker.9,10
Oxford University defined and scored several composite government response
indices. The stringency index was defined in terms of containment policy and public
information.9 The government response index incorporated containment, economic
measures, public information, and testing and tracing policies.9 The containment and
health index was defined in terms of containment measures, public information, and
testing and tracing policies.9
Archived viral testing data for April 2020 were also downloaded.11 Mean
temperature in each country during the pandemic was estimated using the average
monthly temperature in the country’s largest city from public sources.12,13
Online news reports and government statements, including those cited by a
previous review14 and a public database,15 were searched to identify countries in which
the public wore masks early in the outbreak based on tradition, as well as countries in
which the national government mandated or recommended mask-wearing by the public
before April 16, 2020.
For each country, the population,16 fraction of the population age 60 years and
over, and age 14 and under, male: female ratio per country,17 surface area,16,17 gross
domestic product per capita,18 percent urbanization,16,19 adult smoking prevalence20-23
and prevalence of adult obesity24-43 were tabulated. Whether a nation was an isolated
political entity on an island was also recorded.
The prevalence of an infectious process undergoing exponential growth (or
decay) appears linear over time when graphed on a logarithmic scale.1 Therefore, we
postulated that the logarithm of the country-wide infection prevalence would be linearly
related with the duration of the infection in each country. In addition, our analysis
postulated that deaths from coronavirus would follow infections with some delay.
On average, the time from infection with the coronavirus to onset of symptoms is
5.1 days,44 and the time from symptom onset to death is on average 17.8 days.45
Therefore, the time from infection to death is expected to be 23 days.1,46 These
incubation and mortality times were prespecified.1,46 Therefore, the date of each
country’s initial infection was estimated as the earlier of: 5 days before the first reported
infection, or 23 days before the first death.8,11,47 Deaths by May 9, 2020 would typically
reflect infections beginning 23 days previously (by April 16). Therefore, we recorded the
time from the first infection in a country until April 16. We also recorded the period of
the outbreak: 1) from when public mask-wearing was recommended until April 16, 2)
from the mandating of international travel restrictions or quarantine until April 16, and 3)
from the start of mandated limits on internal activities (e.g. closures of schools or
workplaces, limits on public gatherings or internal movement, or stay-at-home orders)
until April 16. For countries scored by Oxford University, the Oxford data were used to
determine the start of international travel restrictions and lockdowns on internal activity.
In addition, we calculated the mean time-weighted score for each lockdown and testing
policy as graded by the University of Oxford for the duration of the country’s outbreak,
from beginning through April 16.9 For instance, if the school closure score was 1 for
half the outbreak and 2 for the other half, then the mean score was 1.5.
Per-capita mortality can be analyzed as a binary outcome (low or high), or as a
continuous variable. Each approach has strengths and weaknesses. Analysis of a
binary outcome is not unduly influenced by outliers. Countries with extremely low or
high mortality are included in the appropriate group, but the exact mortality value does
not change the results. Moreover, analysis of a binary outcome facilities clear
communication, because one can describe the characteristics of low and high mortality
On the other hand, per-capita mortality is in fact a continuous variable, and the
separation of countries just below or just above a threshold value is somewhat arbitrary,
or susceptible to chance variation. Analysis of mortality as a continuous variable uses
all the information available, and can appropriately model the exponential growth of an
infection. We view the binary and continuous analyses as complementary. When one
sees that a univariate association is found with both types of analysis, one gains
confidence that the association is not an artifact of the analytic method selected.
In univariate analysis, characteristics of countries with above-median per-capita
mortality were compared with the remaining (lower mortality) countries by the two-
sample t-test using groups.
Significant predictors of per-capita coronavirus mortality in the univariate analysis
were analyzed by stepwise backwards multivariable linear regression analysis. The
dependent variable was the logarithm (base 10) of per-capita coronavirus-related
mortality. Because of the importance relative to public health, the weeks the country
spent in lockdown, with international travel restrictions, and using masks, and per-capita
testing levels, were retained in the model. In addition, because of their biological
plausibility and presumed importance, urbanization, prevalence of obesity, and average
ambient temperature were retained in most of the multivariable models presented
below. Statistical analysis was performed with xlstat 2020.1 (Addinsoft, New York). An
alpha (p value) of 0.05 was deemed to be statistically significant. The study was
approved by the Virginia Commonwealth University Office of Research Subjects
We studied coronavirus mortality in 200 countries, of which 183 had testing
data,7 169 had government policies scored by Oxford University,9 and 152 fell into both
The 100 lower-mortality countries had 0.99 deaths per million population, in
contrast with an average of 93.3 deaths per million population in the 100 higher-
mortality countries (p<0.001, Table 1, Appendix Table A1). The median value was 4.0
deaths per million population.
We assumed that island nations might find it less challenging to isolate and
protect their populations. However, 19 of 100 low-mortality countries were isolated on
islands, compared with 28 of 100 high-mortality countries (p=0.18). Country surface
area and population were not associated with coronavirus mortality (Table 1).
Countries with older populations suffered higher coronavirus mortality. Countries
with low mortality had on average 8.8% of their population over age 60, as compared
with 18.2% in the high-mortality countries (p<0.001, Table 1). The proportion of the
population which was male was not associated with country-wide mortality (p=0.95,
Table 1). Smoking prevalence was on average 13.7% in low mortality countries and
18.4% in high-mortality countries (p<0.001, Table 1). The prevalence of obesity was on
average 14.6% in low-mortality countries and 24.0% in high-mortality countries
(p<0.001, Table 1).
Colder countries were associated with higher coronavirus mortality in univariate
analysis. The mean temperature was 22.2 C (SD 7.6 C) in the low-mortality countries,
and 14.1 C (SD 9.1 C) in the high-mortality countries (p<0.001, Table 1).
Urbanization was associated with coronavirus mortality in univariate analysis. In
low-mortality countries, on average 52% of the population was urban, as compared with
70% of the population in the high-mortality countries (p<0.001, Table 1). Richer
countries suffered a higher coronavirus related mortality. The mean GDP per capita
was $9,060 in the low-mortality countries, and was $27,140 in the high-mortality
countries (Table 1, p<0.001).
Table 1. Characteristics of countries with low and high per-capita coronavirus mortality
by May 9, 2020 in 200 countries.
Deaths (per million)
Deaths (per capita, log)
Duration infection (weeks)
Duration infection without
Time without international
travel restrictions (weeks).
Duration infection without
internal lockdown (weeks)
Temperature, mean (C)
Urban population (%)
GDP per capita ($)
Age 14 & under (% of pop.)
Age 60 & over (% of pop.)
Surface area (million km2)
Prevalence males (%)
Smoking prevalence, adult
Obesity prevalence, adult
Tests per cap. (log) by Apr
Tests per cap. (log) by Apr
Tests per cap. (log) by May
Durations run from the estimated date of first infection in the country until 23 days before May
9, 2020 (i.e. April 16), or the stated event (mask recommendation or lockdown). Obesity data
available for 196 countries. Testing data available for 135 countries by April 4, 162 countries by
April 16, and 183 countries by May 9.
Masks: Early Adoption.
The World Health Organization initially advised against widespread mask
wearing by the public, as did the United States CDC.1,48 The WHO reversed course and
recommended masks in public on June 5, 2020.49
Despite these initial recommendations, a number of countries did favor mask
wear by the public early in their outbreak, and such countries experienced low
coronavirus-related mortality (Table 2, Table A1, Figure 1).50-68,S1-S301 It is likely that in
Mongolia and Laos, both of which reported no coronavirus-related mortality by May 9,
the public began wearing masks before any cases were confirmed in their countries
(Table 2). We identified 22 additional countries with recommendations or cultural norms
favoring mask-wearing by the public within 20 days of the estimated onset of the
country’s outbreak:1 including (beginning with those favoring masks earliest in the
course of their outbreak): Japan, the Philippines, Macau, Hong Kong, Sierra Leone,
Cambodia, Timor-Leste, Vietnam, Malaysia, Bhutan, Venezuela, Taiwan, Slovakia, St.
Kitts and Nevis, South Korea, Indonesia, Brunei, Grenada, Mozambique, Uzbekistan,
Thailand, and Malawi (Table 2). The average mortality by May 9 for these 24 early
mask-wearing countries was 1.5 per million (SD 2.0). Twenty of the 24 were lower-
mortality countries (p=0.001).
An additional 17 countries recommended that the public wear masks within 30
days of the estimated onset of their outbreak: São Tomé and Príncipe, Czechia,
Dominica, Bangladesh, Zambia, Chad, Benin, Sudan, El Salvador, Antigua and
Barbuda, Myanmar, Bosnia and Herzegovina, Côte d'Ivoire, South Sudan, Kenya, Saint
Lucia, and Barbados (Table 2). The average mortality by May 9 for this group was 8.5
per million (SD 12.4).
Table 2. Countries in which masks were widely used by the public or recommended by
the government within 31 days of the estimated local onset of the outbreak, by
timeliness of mask-wearing.
The public began wearing masks in
January.S183 The mayor of Ulaanbaatar
ordered organizations to implement mask-
wearing on January 27, 2020.S184 Public mask
wearing was quite common by mid-February
when the government encouraged mask
usage by denying service on transport for
those not wearing masks.50
Health officials in Laos advised mask-wearing
by March 6,S156 and the public began wearing
masks even before any cases were reported
in the country.S157
Public use of masks is traditional.48 Surveys
indicate that 64% of adults habitually wore a
mask in Winter.51 Public masking was
manifest by Jan. 16 when the first domestic
case was announced.S144-S146 The
government initially recommended masks
when in “confined, badly ventilated spaces”.48
One survey documented mask wear
prevalence over 60% by March 14, increasing
to over 75% by April 12.52 In another poll,
62% indicated wearing a mask in public by
March 17, 76% by April 13, 81% by April 20,
and 86% by May 4, 2020.53
Masks were used extensively as early as Jan.
30.S215 In a poll, 60% indicated wearing a
mask in public on Feb. 24, 76% on March 23,
and 81% to 84% from March 30 through June
22.53 Masks were mandated on April 2.
Mask use is traditional. By Jan. 23, the
government had implemented a mask
distribution program for the public.S169
Surgical masks were traditionally used, and
also were recommended on public transport
and in crowded places, on January 24,
2020.48,S120 Surveys indicated that masks
were worn by about 73% in the week of Jan.
21, and by 98% of the public by mid-February,
which persisted into May.S122 In February
2020, 94.8% of pedestrians were observed to
wear masks, and 94.1% believed mass
masking reduces the chance of community
outbreak.54 A poll consistently found that 85%
or more wore masks in public between Feb.
25 and June 22, 2020.53
Masks were recommended in public on April
1.S237 Compliance has been incomplete.S238
Masks were widely used by the public by
Masks were required in stores and other
venues as part of a state of emergency
beginning March 28.S271
Masks were widely used by the public by
January 27,S295,S296 and were mandated by the
government on March 16. One survey found
the prevalence of mask wear consistently from
85-90% from March 12 to April 14.52 A poll
reported 59% wore a mask on March 23, and
between 79% and 87% from March 30 to June
8.53 From March 31 to April 6, 2020, 99.5% of
respondents reported using a mask when
Masks were used by the public by January
30.S173 A poll reported 55% wore a mask in
public on Feb. 24, 69% on Mar. 23, 82% on
Apr 6, and 85-88% from May 4 to June 8.53
On Mar. 11, the Ministry of Health advised
wearing of masks in “a crowded place”.S32
The first death was announced on March
26.S293 President Maduro demonstrated
wearing of masks on live television on March
13 (the day the first case was confirmed), and
required masks on public transport.S290,S291
Masks were required in any public space by
Use of masks is traditional. By January 24,
Taiwan banned the export of surgical
masks.56,57 By January 27, the government
had to limit mask exports and limit sales from
pharmacies to those needed for personal
use.S265 On January 28, the government
began releasing 6 million masks daily, with
each resident able to purchase 3 masks
weekly at a set price.56 A poll consistently
found over 80% wore a mask from Feb. 25 to
June 22, 2020.53
Masks were mandated in shops and transit on
March 15,S243 and more broadly in public on
St. Kitts and
On April 2, Chief Medical Officer Dr. Hazel
Laws recommended wearing a mask in public
on the grounds that masks could block
droplets, and viral particles could remain
suspended for 3 hours.S224 The requirement
to wear masks in public became mandatory on
Use of masks is traditional.48 The alert level
was raised from yellow to orange on Jan. 27.58
Children were advised to wear masks at
school by January 30.S249 By Feb. 2, mask
sales increased 373 times year-over-year.58
Stores were selling out of masks by February
3.S250 A superspreader event in mid-February
was associated with a religious group which
did not use masks at their gatherings.59 South
Korea initially had trouble obtaining enough
masks, but at the end of February the
government began to control the distribution of
masks to the public.S251 On Feb. 22, the
government instructed the wearing of masks in
the epidemic area.58
The first death occurred on March 3.S128 The
public scrambled to buy face masks in early
February.S126 The proportion of Indonesian
adults wearing a mask in public was 54% on
Feb. 24, 2020, 47% on March 9, 59% on
March 23, 71% on March 30, 79% on April 13,
81% on April 20, and from 82%-84% from May
4 to June 9.53 During March and April, 76% of
students indicated that they wore a mask
outside the home.60 Masks were mandated in
public on April 5.S129
On March 22, Sultan Hassanal Bolkiah
advised the people to wear masks in public.S40
On April 3, the Ministry of Health
recommended all wear a mask, which could
be purchased at a pharmacy, to “prevent
asymptomatic people from transmitting the
disease unknowingly”.S111 Masks were
mandated outside the home on April 6.S112
Masks were recommended by health
authorities on April 4,S189 and were required on
public transport or in gatherings on April 8.S190
The first coronavirus death was on March 29.
Masks were mandated on March 25.S289
Masks, including N95 masks, were already
worn outdoors in early January to combat
smog. The Thai government was handing out
masks and advising wearing of masks in
public to prevent coronavirus by January 28,
2020.S266-S269 The recommendation of cloth
masks for the public was reaffirmed by the
Ministry of Public Health on March 3, 2020.61
Enforcement of a mask mandate on public
transport began on March 26.61 One survey
reported high mask-wearing: 73% by Feb. 24,
80% by March 23, and between 84 and 89%
between March 30 and June 22.53 During
March 2020, another survey found masks
were worn “all the time” by 14% of COVID-19
cases and 24% of controls, and “some of the
time” by 38% of cases and 15% of controls.61
The first death was on April 7.S171 The public
was required to wear masks on April 4.S172 A
survey in Karonga from April 25 to May 23
found that 22% of urban residents and 5% of
rural residents wore a mask.62
On April 22, it was announced that masks
would be mandatory in public beginning April
Masks were required in public on March 19.S71
Prime Minister Skerrit and Health Minister
McIntyre wore masks during an interview on
March 30.S75 When Dr. Adis King
demonstrated mask-wearing to the legislative
assembly on April 7, all in attendance wore
masks.S76 President Savarin recommended
the wearing of masks in public on April 9.S74
Others,S79 including the state
epidemiologist,S80 repeated this
recommendation in coming days. On April 21,
physician Sam King estimated that 95% of the
population was wearing masks in public.S78
Masks were mandated on public transport on
The first death occurred on March 18.S19
From March 11-19, 2020, when students age
17 to 28 were asked if they were wearing a
surgical face mask in public, 53.8% responded
“yes” and an additional 6.6% responded
“occasionally”.64 A survey from March 29 to
April 29 found that 98.7% reported wearing a
face mask in crowded places.65
The first death was recorded on April 2. On
April 4, masks were recommended for the
public “at all times” by the Zambian Minister of
Health.S298 This spurred the manufacture of
cloth masks.S299 On April 16, masks were
mandated for the public.S300
On April 13, the office of the president
announced that a mask or suitable alternative
(e.g. turban, veil) would be mandatory in
public on April 14.66,S53 On April 14, the
government had to backtrack on enforcement
due to lack of supplies.S56 Specific penalties
for failing to wear a mask in public were
announced on May 7.S54
Masks were recommended in public on April
6,S28 mandated on April 7,S29 and enforced by
police beginning April 8.S30
The first death occurred on March 12. Masks
were dispensed by pharmacists for free in
Sudan by March 16.S261,S262 A survey from
March 25 to April 4 of 2336 adults found that
703 (30.1%) had been to a crowded area, and
1153 (49.4%) had worn a mask outside the
home in the previous few days.67
The first death was reported March 31.
President Bukele recommended universal
mask wear in public on April 4.S90 Masks were
mandated in San Salvador on April 7.S91 On
April 11, the president announced a
nationwide mask mandate, effective April
Masks were required in all public spaces on
In Myanmar, the first death occurred on March
31.S192 A study from March 3-20, 2020 found
that 72% of adults were confident they would
wear a surgical mask whenever visiting a
crowded area.68 On April 5, the Ministry of
Health recommended masks in crowded
places, and cited the US CDC
recommendation for the use of cloth masks by
the public.S194 On April 7, State Counsellor
Daw Aung San Suu Kyi announced that she
would make a mask for herself.S195 By April
16, some regions mandated masks in
public.S196 A survey from May 7-23, 2020
conducted by the Ministry of Health found that
80% of the public wore a mask each time they
Masks were required in public by March
On April 4, senior health officials
recommended masks when in public.66,S141
On April 29, the High Level Task Force
approved the use of locally-manufactured
cloth masks to be worn in public.S253
The March 12 case had arrived from the U.S.
on March 5.S150 The first death was on March
26, of a man who arrived in Kenya on March
13.S151 Masks were mandated in Kenya on
public transport on April 2, and more broadly
in public on April 4.S152,S153 A survey in Nairobi
published on May 5, 2020 found that 89% had
worn a face mask in the previous week, and
73% said they always did so outside the
Face masks were recommended to be worn
when shopping by the chief medical officer on
By April 11, cloth face masks were required
when shopping.S21-S23 Masks were mandatory
on buses by May 11.S24
The delay was the number of days from the start of the outbreak until masks were
recommended by the government or became widespread due to cultural norms. The estimated
start of the outbreak was 5 days before the first infection was reported, or 23 days before the
first death (whichever was first).
Masks in Asia.
Throughout much of East, South, and Southeast Asia, masks were worn by the
public as a preventive measure, rather than a policy implemented after evidence
emerged of health system overload (Table 2). The public sometimes implemented
masks before government recommendations were issued.
As the country where the pandemic started, China is a noteworthy case of a
nation which traditionally has favored mask-wearing by the public for respiratory
illnesses, but which did not deploy masks immediately. The first cases in China had
begun by December 1, 2019.69 By the time human-to-human transmission was
confirmed on Jan. 20, 2020, many in Beijing were already wearing masks.S58 The
government required masks in public in Wuhan on Jan. 22.S59 From Jan. 23-25, thirty
regions in China mandated masks in public.58,70 Masks were ordered throughout China
when around others in public on Jan. 31.S60 China suffered a very significant outbreak
in Wuhan, but appears not to have experienced the same level of infection in other
regions. Surveys indicate that the prevalence of public mask wear in China remained
between 82% and 90% between February 24 and June 22.53 Another survey confirmed
mask wear from 80-90% from March 12 to April 14.52 The reported country-wide per-
capita mortality by May 9, 2020 was 3.2 per million population.
For several countries in South or Southeast Asia with mortality lower than in the
West, we did not score the country as mask-wearing in the primary analysis until their
governments issued recommendations to do so. Nonetheless, there is evidence of
significant mask wear by the public before the recommendations in Nepal, India, and Sri
In Nepal, facemasks are commonly seen in urban centers due to air pollution.71
The first case of COVID-19 in the country was reported on January 13, in a traveler
returning from Wuhan.72 However, no subsequent cases were reported in Nepal until
the second week of March.72 By January 29, all students at some schools were wearing
masks.S198 By February 3, pharmacies were selling out of masks due to increased
demand.S199 With the outbreak, tailors began sewing cloth masks.71 By February 8,
2020, “a majority” of the public was wearing masks.S200 The recommendation to wear
masks in public became more formalized on March 25.S201 The Ministry of Health
distributed masks to children and elderly in shelters by March 25.S202 Surveys in Nepal
found that 83% of respondents agreed that asymptomatic people should wear masks to
prevent COVID-19 infection at the end of March,72 and 96% agreed with this statement
from May 15 to June 20.73 As of May 9, Nepal reported no coronavirus-related
mortality. We used the March 25 recommendation as the date in the mask analysis, but
earlier mask use might have forestalled the epidemic in Nepal.
In India, the first case of coronavirus was diagnosed on January 30.S124 The
Health Ministry recommended homemade face masks on April 4, 2020.S125 However,
mask wear was high both before and after the recommendation. According to one poll,
masks were worn by 60% of the public from March 12-14, 67% from March 19-21, and
then from 73% to 76% between March 26 through April 12.52 According to another poll,
masks were worn by 43% of the public on March 16, 46% on March 20, 65% on March
27, 71% on April 3, 79% on April 10, and 81-84% between April 17 and May 1.53 A
survey conducted in March 2020 found that 75% of the public believed that masks
should be worn even by asymptomatic people, and 77% of respondents indicated that
the N95 mask was most protective.74 By May 9, the per-capita mortality was 1.5 per
In Sri Lanka, the public immediately bought masks at the end of January when
the first cases were identified.S257 Masks were mandated in public on April 11.S258 The
per-capita mortality by May 9 was 0.4 per million.
Singapore was slower than its Asian neighbors to embrace masks, but when the
government shifted course, the public was ready to respond. On March 27, only 27% of
respondents indicated that they wore a mask.53 On April 3, when the government
announced that it would no longer discourage mask-wearing by the public, and would
instead distribute masks,S239-S241 37% indicated that they wore a mask.53 Mask wearing
by the public reached 73% on April 10, 85% on April 17, and 90% on April 24, where it
remained through June 19. 53
Early in the pandemic, masks were noted to be “somewhat common” in
Afghanistan.75 By March 29, 2020, the Taliban had begun distributing masks to the
public in areas under their control.S1
In March 2020, 78% of Pakistanis in Sargodha were in favor of wearing a mask
to prevent coronavirus.76 Another survey conducted from April 1-12 indicated that 80%
of Pakistanis believed the government should mandate mask wearing for adults outside
the home.77 Masks were mandated when in crowded spaces in Pakistan on May 31.S209
Masks in the Middle East.
In parts of the Middle East, masks were embraced by the public even before
government requirements. In the United Arab Emirates, the first cases were reported
on January 29.S280 By February 29, mask usage had become “more prominent”, but the
Ministry of Health and Community Protection advised that N95 masks should be
reserved for medical personnel treating coronavirus patients, and could cause
“respiratory illness” if worn by the public.S281 Despite this warning, a poll of UAE
residents found that masks were worn by 39% of the public on March 18, and 44% on
March 25.53 On March 27, the government followed the people’s lead, and mandated
masks when indoors.S282 Subsequently, masks were worn by 63% on April 1 and
between 78% and 81% between April 14 and June 17.53 By May 9, the per-capita
mortality was 18.7 per million.
In Saudi Arabia, the first case was announced on March 2.S231 A poll of Saudi
residents found that 35% wore a mask on March 18, 54% on April 1, and 59% on April
14,53 despite the lack of any official guidance to do so. A different survey conducted
from April 2-5, during a period of lockdown, found that 16.9% had worn a mask even
without symptoms.78 Public mask-wearing was recommended by the Saudi government
on April 28,S232 and mandated on May 30.S233 Mask-wearing reached 63% on May 4,
and 72% on June 3.53 A survey of Saudi nursing students which concluded on June 30
found that 87% had worn a mask when going out in recent days.79 By May 9, the per-
capita mortality was 6.9 per million.
In Lebanon, the first case was reported on February 21.S159 Masks were popular
among the public from mid-March to early April.S160,S161 Masks were recommended by
the health minister on April 25.S161 By May 9, the per-capita mortality was 3.8 per
In March 2020 in Egypt, 76.4% of adults expressed an understanding of the
value of wearing a mask in public, but only 36.4% agreed that they actually did so.80 At
this time, the government was not mandating masks, but by March 20, prices of masks
had soared, and volunteer organizations were advocating public masking in Egypt.S87
Masks were mandated in public in Egypt on May 31.S88
In Iran, no infections were announced until February 19, when two deaths were
reported.S130 By March 12, satellite imagery demonstrated the digging of mass graves
in Qom.S131 In accord with WHO guidelines, the guidance of the Iranian Health Ministry
available on March 24, 2020 advised that the public wear a mask only if symptomatic or
caring for the sick (personal communication, Linnea I. Laestadius, June 7, 2020).14
However, a new guidance which recommended universal masking in gyms, parks, and
public transit was issued by the Ministry by March 29,14 an estimated 62 days after the
start of the outbreak (assuming the reported deaths were really the first). A survey
conducted from February 25 to April 25 found that 64% of the public reported wearing a
mask and gloves in crowded places.81 By May 9, the reported per-capita mortality in
Iran was 78.4 per million, though many, even those within the Iranian government, have
questioned the official figures.82,83,S132
In Jordan, a study conducted from March 19-21, 2020 found that 39.8% of
university students wore a face mask when leaving home.84 King Abdullah
recommended that the public wear masks when shopping on April 27.S147
In Yemen, 90% of women wear the niqab, which local doctors believe might
reduce transmission of the virus by functioning as a mask.85 By May 9, the per-capita
mortality in Yemen was 0.2 per million.
In Syria, a survey of university students conducted from March 19-21, 2020
found that 52% of respondents indicated that everyone should wear a mask when
outside, but that 25% indicated that they did so at least sometimes, and 75% never
wore a mask on the street.86
Government mandates or recommendations for mask wearing by the public were
issued in Kuwait for gatherings by March 23,14 in Israel on April 1,S135 and in Bahrain on
Masks in Africa.
As noted above, 11 African countries recommended or mandated masks within
31 days of the onset of their outbreak: Sierra Leone, Mozambique, Malawi, São Tomé
and Príncipe, Zambia, Chad, Benin, Sudan, Côte d'Ivoire, South Sudan, and Kenya
(Table 2). In addition, the public widely sought masks to wear early in the outbreak in
In Ethiopia, 75.7% of chronic disease patients surveyed from March 2-April 10,
2020 agreed that it was important to wear a mask outside the home to prevent infection
with coronavirus.87 A survey from March 20-24 found that 87% of the public believed
wearing a mask could prevent spread of the virus, but only 14% had done so in the few
days before the survey.88 Another survey from April 1-15 in southern Ethiopia found
that 84% believed that wearing a mask was protective, 160 respondents (36%) had
been to a crowded place in recent days, and 129 respondents (29%) had worn a mask
when leaving home in recent days.89 Masks were mandated in public on April 11.S95 In
a survey in that country from April 15-22, 84% believed a mask could provide protection
from coronavirus, 137 people (40%) had gone to a crowded place after the onset of the
pandemic, and 82 people (24%) had worn a mask outside the home.90 By May 9,
Ethiopia had reported no deaths from coronavirus.
In Cameroon, the first cases of coronavirus were identified on March 6.91 From
March 10-18, a study found that 93.5% of the public viewed the wearing of face masks
as protective, and 21.7% had already purchased them.91 A study in Northern
Cameroon conducted from March 1-28 found that only 13% wore a mask outside the
home.92 A survey in Cameroon conducted from April 1 to 25 found that 83.6% reported
wearing a mask at gatherings.93 On April 9, it was announced that masks would be
mandatory in public beginning April 13.66,S47,S48 By May 9, the per-capita mortality was
4.1 per million.
In a city in the Democratic Republic of the Congo not yet affected by the
pandemic at the time of a survey conducted from April 17 to May 11, 61% of
respondents were aware of the value of wearing a face mask, 27% reported wearing a
face mask since the pandemic began, and 65% felt that wearing a face mask was
In Ghana, a study from March 27-29 of 43 public transport stations found that
masks were worn by many people at one station, worn by a few people at 27 stations,
and not worn at the remainder.95 On April 19, 2020, the president of Ghana announced
that masks would be required in public.S107,S108
Masks were required in public in Nigeria on April 14.96,S206 A study in Nigeria
from May 7 to 18 found that 65% of respondents had worn a mask outside the home in
In South Africa from April 8-24, 2020, 85.6% of the public agreed that wearing a
mask could help to prevent coronavirus infection.S246 South African health officials
recommended mask wear in public on April 10.S247
In addition, government mandates or recommendations for mask wearing by the
public were issued by April 16 in: Mauritius on March 31;S178 TunisiaS274 and
MoroccoS187 on April 6; Guinea on April 13;S114 Gabon on April 15;63,66 Equatorial
Guinea on April 14;S93 and Libya on April 16.S164
Masks in Europe.
Most countries in Europe and North America failed to embrace masks early in
their outbreaks, and only adopted mask policies after signs of health system overload
became apparent. Only 3 countries in Europe appear to have had government
recommendations for the public to wear masks within 31 days of the onset of their
outbreak: Slovakia, Czechia, and Bosnia and Herzegovina (Table 2).
The first country in Europe to be strongly affected by the outbreak was Italy,
which reported its first cases on January 31, among a family who arrived from China on
January 23.S136 By March 10, doctors in Lombardy indicated that all intensive care beds
were taken, and the system did not have enough respirators for the affected.208X A poll
found that only 26% of Italians wore a mask in public on March 11, but, with the rising
health system overload, 59% did so on March 1953—at least 53 days from the local
onset of the outbreak. Another poll confirms that the prevalence of mask wear
exceeded 50% for the first time from March 19-21.52 Lombardy (April 5) and Tuscany
(April 6) required the public to wear masks in early April.S138 A nationwide mandate to
wear masks in shops and public transport was announced on April 28, to take effect on
May 4.S139 Mask wear in public remained between 85% and 89% between April 16 and
June 10.53 By May 9, the per-capita mortality in Italy was 502.7 per million.
The next country to suffer was Spain, which reported its first case on January
31,S254 and experienced its first death from the virus on February 13.S255 The
prevalence of mask wear among the Spanish public was 5% on March 12, 25% on
March 19, 42% on March 25, and 56% on April 853—potentially 72 days after the entry
of the virus into the country. Masks were mandated when in transit beginning April
11.S256 Mask wearing in public had climbed to 65% by April 16, 72% by April 30, and
remained between 84% and 87% between May 20 and June 12.53 According to another
survey, the prevalence of mask wear was 50% by March 21, 53% by April 4, and 61%
by April 12.52 The per-capita mortality by May 9 was 566.3 per million.
In France, the first case of coronavirus was reported on January 24,S97 and the
first death on February 14, of a man who arrived from China on January 16.S98 A poll
found on March 10 that only 5% of those in France wore a mask in public.53 This
number increased to 22% on March 27 and 25% on April 3,53 the day that the Académie
Nationale de Médecine announced that masks should be compulsory in publicS99—at
least 72 days into their outbreak. Polls indicated that mask wear among the public
climbed to 38% on April 10, 43% on April 17, 56% on May 1, 76% on May 20, and 75%
on June 12.53 Mask wear below 50% in early April was confirmed in another survey.52
On May 7, it was announced that throughout France, including its overseas
departments, masks would be mandatory on transport, starting May 11.98 By May 9, the
per-capita mortality in France was 403.1 per million.
In Germany, the first case of COVID-19 was reported on January 27. The patient
had contact with a colleague visiting from China beginning January 19.S103 By March
30, only 7% of the public reported wearing a mask in public.53 On March 31, the city of
Jena mandated use of masks by the public.S104 The Robert Koch Institute
recommended that the public wear masks on April 1S105—at least 70 days from the
onset of the outbreak. Masks were worn by 14% of the public on April 6, 17% on April
13, 24% on April 20, 62%-64% from May 4 through June 18.53 Another survey confirms
mask wear at or below 20% in March and early April.52 All German states had
mandates relating to mask wear in public by April 22.S106 By May 9, the per-capita
mortality was 90.1 per million.
In the United Kingdom, the first cases of coronavirus were reported on January
31.S283 Here, 2% of the population wore a mask by March 20, 11% by April 17, 20% on
May 1, and 27% on June 17.53 Another survey confirms mask wear below 20% from
March 12 to April 12.52 Masks were recommended in England on public transport and
in shops on May 11S284—over 100 days after the local outbreak onset. On June 4,
English authorities announced that masks would be mandatory on public transit,
beginning June 15.S285 By May 9, the per-capita mortality was 465.3 per million.
In the Netherlands, from April 1 to 19, the prevalence of mask wear was
approximately 7%.99 The prime minister announced on May 6, 2020 that beginning
June 1, masks would be required on public transport due to their value in situations
where social distancing was not possible.S203
In Belgium, from April 4 to 19, the prevalence of mask wear increased from about
30 to 37%.99 The Prime Minister of Belgium announced on April 24 that masks would
be mandatory on public transport effective May 4.S25
In the Scandinavian countries of Sweden, Norway, Denmark, and Finland, polls
repeatedly showed masks to be worn by 10% or less of the population from March 16
through June 9.53 This low usage occurred despite the fact that the government in
Finland began recommending that the public wear masks on April 14.S96
In Switzerland, the chief of the Communicable Diseases Department
recommended masks on public transport on June 15.S264 However, a survey released
June 18 found that only 6% of Swiss public transport riders did so.S264
In Poland, the health minister announced on April 9 that a public mask mandate
would go into effect on April 16, and mask vending machines began to be installed.S216
In Poland, from April 12-14, 2020, 60.4% of Polish students age 18 to 27 wore a face
mask in the previous 7 days.100 By May 9, the per-capita mortality was 20.7 per million.
The first cases of coronavirus in Russia were reported on January 31, 2020.S220
In Russia, the prevalence of mask wear among the public was 11% by March 14, 19%
by March 21, 36% by March 28, and 57% by April 452—69 days after the estimated start
of the outbreak. Mask wearing prevalence had increased to 59% by April 12.52 On May
11, it was announced that masks would be mandatory in shops and public transport
(Time/Russia). By May 9, the per-capita mortality was 12.5 per million.
In Serbia, in April 2020, 60% of the public agreed they were willing to wear a
mask during a pandemic, and respondents on average answered 3.25 (SD 1.6) on a 1
to 5 scale when asked if they wore masks, where 4 represented “agree” and 5
represented “strongly agree”.101
Some additional Western governments mandated or recommended mask-
wearing in public by April 16, 2020. By March 29, masks were mandated in indoor
public spaces in Slovenia.S245 In Austria, a mandate to wear masks in shops was
announced on March 30, with the expectation that masks would be available by April
1.S13 In addition, the requirement to wear masks on public transit was announced there
on April 6.S14 Masks were recommended for the public in BulgariaS41 and
UkraineS278,S279 on March 30. In Lithuania, masks were recommended for the public on
March 26,S166 and mandated on April 8.S167 Government mandates or
recommendations for mask wearing by the public were also issued in: Turkey,S275 and
CyprusS69 on April 3; Estonia on April 5;S94 and Luxembourg on April 15.S168
Masks in the United States and Canada.
The earliest case of COVID-19 in the United States was a man who returned
from China on January 15, 2020, and presented at an urgent care clinic on January
19.102 In the United States, the prevalence of mask wear in public was 7% on March 2,
5% on March 17, and 17% on March 30.53 The U.S. C.D.C. began recommending that
asymptomatic people wear a mask in public on the evening of April 3103—at least 79
days after the virus had entered the country. Subsequently, the prevalence of mask
wear was 29% on April 6, 49% on April 13, 58% on April 20, 63% on April 27, 68% on
May 26, and 66% on June 8.53 Another survey found that the prevalence of mask wear
was 32% from April 2-4, and 50% from April 9-12.52 According to another survey, from
April 14-20, 36% of U.S. adults always wore a mask outside the home, 32% did so
sometimes, and 31% never did.S286 Mask wearing varied by region. In Vermont, from
May 16 to 30, 76% of people entering businesses were observed to wear a mask.104
On the other hand, in Wisconsin from June 3-9, only 42% of shoppers were observed to
wear a mask.105 By May 9, the per-capita coronavirus-related mortality was 241.8 per
In Canada, the prevalence of mask wear was 6% on March 17, and 18% on April
6,53 when the government announced that masks were now recommended in public.S49
Uptake was gradual, with mask wearing at 16% on April 13, 31% on April 20, 41% on
April 27, 49% on May 26, and 58% on June 11.53 Another survey confirms mask wear
below 30% in March and early April.52 By May 9, the per-capita coronavirus-related
mortality was 124.3 per million.
Masks in Australia.
In Australia, surveys of the public indicated that 10% wore a mask by March 15,
which gradually increased to a high point of 27% by April 19, after which use gradually
declined to 17% on June 5.53 Another survey confirms mask wear below 25% in March
and early April.52
Masks in Latin America and the Caribbean.On April 3, a reporter in Bogotá
noted that 90% of the people on the street were wearing face masks.S63 On April 4, the
government of Colombia mandated masks on public transport and shops.S62-S65
On April 6, the Minister of Health in Chile announced that masks would be
mandatory on public transport starting April 8.S57 Due to the shortage of medical masks,
the public was invited to make their own out of cloth.S57
Surveys indicate that in Mexico, the prevalence of public mask wear increased
steadily from 17% on March 17 to 37% on April 6, 46% on April 13, 60% on April 20,
and 67% on April 27.53 According to another survey, the prevalence was 31% by March
14, 36% by March 21, 46% by April 4, and 58% by April 9.52 Although some states had
mandated masks, the federal minister leading the coronavirus response refrained from
encouraging the public wearing of masks until May 5.S180,S181 By May 9, the per-capita
mortality was 26.0 per million.
Ecuador did not require masks early in their outbreak. The first case of COVID-
19 in Ecuador was reported on February 29 in a traveler who had arrived from Spain on
February 14.S83 The first death was reported on March 13.S84 By April 3, it was noted in
Guayaquil that mortuary facilities were overwhelmed, and bodies were being left on the
streets.S85 On April 7, the Interior Minister of Ecuador announced that face masks were
mandatory in publicS86—at least 48 days (and possibly 53 days) after the local onset of
the outbreak. By May 9, the reported mortality was 97.3 per million.
The first case of COVID-19 in Brazil was reported on February 26.S37 In Brazil,
the prevalence of mask wear in public was 25% by March 14, 28% by March 21, 39%
by April 4, and 56% by April 1252—50 days after the virus is estimated to have arrived in
the country. By May 9, the per-capita mortality was 50.1 per million.
Graphical Analysis of Mask Effect.
Before the formal statistical analysis, we graphically illustrate the effect of mask
wear (Figures 1, 2). The first figure demonstrates the effect of early mask usage
(Figure 1). In the countries not using masks by April 16, or not using them until 60 days
after the start of the outbreak, the per-capita mortality by May 9 rises dramatically if the
infection has persisted in the country over 60 days (Figure 1, red line). On the other
hand, countries in which a mask was used from 16 to 30 days after infection onset had
per-capita mortality several orders of magnitude less by May 9 (Figure 1, orange line).
When countries recommended masks within 15 days of the onset of the outbreak, the
mortality was so low that the curve is difficult to distinguish from the x-axis (Figure 1,
Figure 1. Per-capita mortality by May 9 versus duration of infection according to whether early
masking was adopted. Data grouped by whether country did not recommend masks by April
16, 2020 or recommended them more than 60 days after outbreak onset (red line);
recommended masks 16 to 30 days after onset of the country’s outbreak (orange line); or
recommended masks (or traditionally used masks) within 15 days of the outbreak onset (blue
line close to the x-axis). Country mortality was averaged for the following country groups of
infection duration: 0-15 days, 16-30 days, 31-45 days, 46-60 days, 61-75 days, 76-90 days, 91-
105 days. For instance, per-capita mortality for all non-mask or late-masking countries with
infection duration between 61 and 75 days was averaged, and graphed at the x-value 68 days.
Data for graph derived from 200 countries.
For instance, for the early mask-wearing countries in which the infection had
arrived by January (Thailand, Japan, South Korea, Taiwan, Macau, Hong Kong,
Vietnam, Cambodia, Malaysia, the Philippines), the virus was present in the country by
80 or more days by April 16 (Table 2). If masks had no effect, we might have expected
these countries to have a mortality well over 200 deaths per million (Figure 1). Instead,
the mortality for these 10 regions was 2.1 per million (SD 2.5, Table 2)—approximately
a 100-fold reduction.
In order to provide some graphical idea of the scatter of the data when
exponential growth is assumed, we graphed per-capita mortality by May 9 on a
logarithmic scale as a function of the duration of the country’s outbreak not using masks
in all 200 countries (Figure 2). This simple model explained 28.4% of the variation in
Figure 2. Scatter-plot of per-capita mortality by May 9, 2020 as a function of the period of the
country’s outbreak without mask recommendations or norms. The dotted line represents the
best fit using least-squares linear regression. Data for graph derived from 200 countries. Start
of outbreak defined as 5 days before first case reported, or 23 days before the first death
(whichever was earlier).
Initial multivariable analyses.
An initial multivariable analysis was conducted including all 200 countries. By
multivariable linear regression, significant predictors of the logarithm of each country’s
per-capita coronavirus mortality included: duration of infection in the country, duration of
wearing masks (p<0.001), percentage of the population over age 60, and urbanization
(all p≤0.009, Appendix Table A2). The association of mortality with the timing of
international travel restrictions was of borderline statistical significance (p=0.051). The
model explained 48.3% of the variation in per-capita mortality (Table A2).
We also prepared a multivariable model to predict the logarithm of per-capita
coronavirus mortality in the 196 countries with obesity data. In this model, lockdown,
obesity, temperature, and urbanization were retained due to their plausibility as
important factors (Table 3). By multivariable linear regression, significant predictors of
the logarithm of each country’s per-capita coronavirus mortality included: duration of
infection in the country, duration of wearing masks, and percentage of the population
over age 60 (all p<0.001, Table 3). The associations of obesity and or urbanization with
increased mortality approached statistical significance (p=0.10, Table 3). When
controlling for the duration of infection in the country, there appeared to be a negative
association between mortality and time in lockdown (p=0.85) and time with international
travel restrictions (p=0.07), though neither association reached statistical significance
(Table 3). The model explained 51.0% of the variation in per-capita mortality.
Table 3. Predictors of (log) Country-wide Per-capita Coronavirus Mortality by May 9 by
Multivariable Linear Regression in 196 Countries.
Duration in country (wks)
0.139 to 0.281
Time wearing masks (wks)
-0.206 to -0.086
Time in internal lockdown
-0.108 to 0.089
Time since start of
-0.132 to 0.006
Population, age ≥ 60 (%)
0.028 to 0.069
-0.001 to 0.013
Obesity prevalence (%)
-0.003 to 0.032
Temperature, ambient (C)
-0.022 to 0.013
-8.44 to -6.88
Duration of infection in country from estimated date of first infection until 23 days before May 9,
2020 (i.e. April 16). Mask and lockdown durations run from the stated event (mask
recommendation or lockdown) or estimated date of first infection in the country (whichever was
later) until 23 days before May 9, 2020 (i.e. April 16). Model r2=0.510.
In countries not recommending masks, the per-capita mortality tended to
increase each week by a factor of 1.621, or 62.1%. In contrast, in countries
recommending masks, the per-capita mortality tended to increase each week by a
factor of 1.6210 * 0.7145 = 1.158, or just 15.8%. With international travel restrictions in
place (without masks), the per-capita mortality increased each week by
(1.6210)(0.8645) = 1.401, or 40.1%. Under lockdown (without masks), the per-capita
mortality increased each week by (1.6210)(0.9780) = 1.585, or 58.5%, i.e. slightly less
than the baseline condition (Table 3).
A country with 10% more of its population living in an urban environment than
another country tended to suffer a mortality 14.5% higher (100.0588 = 1.145, Table 3). A
country in which the percentage of the population age 60 or over is 10% higher than in
another country tended to suffer mortality 206% higher (100.485 = 3.06, Table 3). A
country with a prevalence of obesity 10% higher tended to suffer mortality 39% higher
(100.144 = 1.39, Table 3).
Numbers of Viral Tests.
Among the 183 countries with viral (PCR) testing data by May 9, per-capita
testing performed at all 3 time points was positively associated with per-capita mortality
in univariate analysis (all p<0.001, Table 1). By May 9, 2020, low-mortality countries
had performed 1 test for every 575 members of the population, while high-mortality
countries had performed 1 test for every 81 members of the population (p<0.001, Table
To the multivariable model (Table 3), we added testing by May 9, using data from
179 countries with both testing and obesity data. Duration of infection in the country,
the duration that masks were recommended, and age at least 60 years continued to be
significant predictors of per-capita mortality (all p≤0.001, Appendix Table A3). The
model explained 52.5% of the variation in per-capita mortality. Each week the infection
persisted in a country without masks was associated with a 62.7% increase in per-
capita mortality (Table A3). In contrast, in countries where masks were recommended,
the per-capita mortality tended to increase each week by 19.1% (because
(1.6271)(0.7319) = 1.191, Table A3). In this model, the prevalence of obesity was
associated with increased country-wide per-capita mortality, though the association was
not significant (p=0.09). If the prevalence of obesity increased by 10% (e.g. from 10%
to 20% of a population), the per-capita mortality tended to increase by 47% (Table A3)
In this model, a 10-fold increase (i.e. one logarithm) in per-capita testing tended
to be associated with a 26.0% increase in reported per-capita mortality, though the
trend was not close to reaching statistical significance (p=0.38, Appendix Table A3).
If early testing lowers mortality, one might expect negative regression
coefficients. Testing on both April 16 and May 9 were added to the multivariable model
of Table 3, using data from the 158 countries with both obesity and testing data by
these dates. Per-capita testing (log) by April 16 was not negatively associated with per-
capita mortality (log) by May 9 (coefficient 0.211, 95% CI -0.305 to 0.868, p=0.34).
Likewise, testing on both April 4 (the earliest archived data) and May 9 were
added to the multivariable model of Table 3, using data from the 131 countries with both
obesity and testing data by these dates. Per-capita testing (log) by April 4 was not
significantly associated with per-capita mortality (log) by May 9 (coefficient -0.0535,
95% CI -0.380 to 0.273, p=0.75). Given the coefficient, a 10-fold (one log) increase in
early testing would be associated with a (non-significant) decrease in per-capita
mortality of 11.6%.
Only 5 countries had performed over 1 test for every 10 people in the country by
May 9, 2020 (in order of most testing to least): the Faeroe Islands, Iceland, the Falkland
Islands, the UAE, and Bahrain. The Faeroe and Falkland Islands reported no
coronavirus-related deaths. The highest per-capita mortality among this group was 29.0
per million population (or 1 in 34,480 people), seen in Iceland.
Containment and Testing Policies.
For 169 countries, containment, testing, and health policies were scored by
Oxford University.9 The following countries with mask policies by April 16 were included
in this analysis, but not in the previous multivariable model, for lack of data on numbers
of tests performed: China, Macau, Cameroon, Sierra Leone, and Sudan. In univariate
analysis, scores for school closing, cancelling public events, international travel
controls, and index of containment and health were significantly associated with lower
per-capita mortality (all p<0.05, Table 4). Policies regarding workplace closing,
restrictions on gatherings, closing public transport, stay at home requirements, internal
movement restrictions, public information campaigns, testing, and contact tracing were
not significant predictors of mortality (all p>0.05, Table 4). Likewise, overall indices of
stringency and government response were not associated with mortality (all p>0.05,
Table 4. Government policies in 169 countries with low and high per-capita coronavirus
mortality by May 9, 2020.
School closing (0-3)
Workplace closing (0-3)
Cancel public events (0-2)
Restrictions on gatherings (0-4)
Close public transport (0-2)
Stay at home requirements (0-3)
Internal movement restrictions (0-
International travel controls (0-4)
Income support (0-2)
Debt / contract relief (0-2)
Public information campaigns (0-
Testing policy (0-3)
Contact tracing (0-2)
Stringency Index (0-100)
Government response index (0-
Containment & health index (0-
Economic support index (0-100)
Government policies were scored by Oxford University.9 Characterization as low or high
mortality was defined by the median for all 200 countries.
A multivariable model in 169 countries found that duration of the infection,
duration masks were recommended, prevalence of age at least 60 years, obesity, and
international travel restrictions were independently predictive of per-capita mortality
(Table 5). The model explained 66.8% of the variation in per-capita mortality. At
baseline, each week of the infection in a country without masks was associated with an
increase in per-capita mortality of 50.9% (Table 5). In contrast, for each week that
masks were worn, the per-capita mortality was associated with a lesser increase of
12.4% each week (given that 1.5085 (0.7449) = 1.124, Table 5).
International travel restrictions were scored by Oxford as: (0) no measures, (1)
screening, (2) quarantine arrivals from high-risk regions; and ban on arrivals from some
(3) or all (4) regions. The international travel restrictions were scored as 4 in
Greenland, 3.8 in Bermuda, 3.6 in Israel, 3.5 in Czechia and New Zealand, 3.1 in
Taiwan, and 2.9 in Australia, and at the other extreme, were scored as 1.1 in Sweden,
and as 0 in Iran, Luxembourg, and the UK.
International travel restrictions were associated with lower mortality, regardless of
whether incorporated in the model as time since onset, or as mean score during the
outbreak. We present the model based on the former because of the strength of the
association, and for consistency with the models presented previously. The regression
analysis suggested that for each week of travel restrictions (without masks), the per-
capita mortality increased by 25.1% (given that 1.5085 (0.8291) = 1.251, Table 5).
Table 5. Predictors of (log) Country-wide Per-capita Coronavirus Mortality by May 9 by
Multivariable Linear Regression in 169 Countries.
Duration in country (wks)
0.118 to 0.239
Time wearing masks (wks)
-0.178 to -0.077
Time in lockdown (wks)
-0.076 to 0.093
Time since start of
-0.140 to -0.023
Population, age ≥ 60 (%)
0.051 to 0.087
-0.0004 to 0.013
Obesity prevalence (%)
0.003 to 0.036
Temperature, ambient (C)
-0.007 to 0.023
Testing policy (0-3)
-0.207 to 0.232
Contact tracing (0-2)
-0.353 to 0.010
-8.57 to -7.20
Duration of infection in country from estimated date of first infection until 23 days before May 9,
2020 (i.e. April 16). Mask and lockdown durations run from the stated event (mask
recommendation or lockdown) or estimated date of first infection in the country (whichever was
later) until 23 days before May 9, 2020 (i.e. April 16). Policies on testing, contact tracing, and
international travel controls were scored by Oxford University. Model r2=0.668.
Per-capita mortality was not significantly associated with policies regarding either
testing policy (p=0.91), or contact tracing (p=0.06, Table 5). Testing policy was scored
as: no policy (0), symptomatic with exposure, travel history, hospitalization, or key
occupation (1), all symptomatic (2), or open to anyone (3). Testing policy tended to be
positively associated with mortality. Contact tracing was scored as: none (0), some
cases (1), or all cases (2), and tended to be inversely related with per-capita mortality
(though not significantly). These countervailing associations meant that as compared
with a country with no testing or tracing policy, a country which opened testing to the
entire public with comprehensive contact tracing might be associated with a reported
change in mortality of
10(3*0.0122+2*(-0.172)) = 0.493, i.e. a 51.7% reduction in per-capita mortality (though
statistical significance was not demonstrated). Thus, testing and tracing may be
important factors, but seem unlikely to account for the majority of the 100-fold variation
in per-capita mortality between low and high mortality countries early in the course of
Surveys of mask wearing by the public during the exposure period were available
for 41 countries (see above). To determine the influence that actual mask-wear, as
opposed to mask policies, might have on the model, we scored countries as mask-
wearing if at least 50% of the public wore a mask, and non-mask wearing if less than
50% of the population did so.
Based on surveys, Canada, Finland, France, Germany, and Malawi were not
considered mask-wearing countries at any time during the exposure period (ending April
16). In contrast, Italy was scored as mask-wearing beginning March 19,53 Spain53 and
India52 beginning March 21, Saudi Arabia beginning April 1,53 Russia beginning April 4,
Singapore beginning April 10,53 and the United States, Brazil and Mexico beginning
In this survey-modified model in 200 countries, duration of the outbreak, duration
of mask wear, proportion of the population age 60 or over, and urbanization were all
significant predictors of per-capita mortality (all p<0.01, Appendix Table A4). Time since
the start of international travel restrictions tended to be inversely associated with
mortality (p=0.051). Each week that the infection persisted in the country without masks
was associated with a 59.9% increase in per-capita mortality. On the other hand, when
masks were worn, the per-capita mortality only increased by 9.3% weekly,
(1.5993)(0.6836) = 1.093, (Appendix Table A5). The model explained 48.3% of the
variance in mortality.
These results confirm that in the first 4 months of 2020, there was marked
variation between countries in mortality related to COVID-19. Countries in the lower
half of mortality experienced an average COVID-19-related per-capita mortality of 0.99
deaths per million population, in contrast with an average of 93.3 deaths per million in
the remaining countries. Depending on the model and dataset evaluated, statistically
significant independent predictors of per-capita mortality included urbanization, fraction
of the population age 60 years or over, prevalence of obesity, duration of the outbreak
in the country, international travel restrictions, and the period of the outbreak subject to
cultural norms or government policies favoring mask-wearing by the public.
These results support the universal wearing of masks by the public to suppress
the spread of the coronavirus.1 Given the low levels of coronavirus mortality seen in the
Asian countries which adopted widespread public mask usage early in the outbreak, it
seems highly unlikely that masks are harmful.
On April 30, 2020, we originally published the finding that the logarithm of per-
capita coronavirus mortality is linearly and positively associated with the duration of the
outbreak without mask norms or mandates .46 This key finding was recently confirmed
by Goldman Sachs chief economist Jan Hatzius, who cited our work.107 The regression
analysis performed by Goldman Sachs confirms that, for prediction of both infection
prevalence and mortality, the significance of the duration of mask mandates or norms in
the model persists after controlling for age of the population, obesity, population density,
and testing policy.107
One major limitation is that evidence concerning the actual prevalence of mask-
wearing by the public is unavailable for most countries. Our survey of the literature is
one of the more complete evaluations of the question to date. Available scholarship
and surveys do corroborate reports in the news media that mask wear was common in
public in many Asian countries, including Japan, the Philippines, Hong Kong, Vietnam,
Malaysia, Taiwan, Thailand, China, Indonesia, India, Myanmar and Bangladesh (Table
2). Internet search data are consistent with interest in masks developing much earlier in
the course of the pandemic in Asia than elsewhere.108,109 Mask wear was widespread in
some low-mortality countries even before, or in the absence of, a formal government
In addition, it is likely that the policies favoring mask-wearing in parts of the
Middle East, Africa, Latin America and the Caribbean were markers of a general cultural
acceptance of masks that helped to limit spread of the virus. Had there been adequate
survey data to fully reflect the early wearing of masks in these regions, it is possible that
the association of masks with lower mortality would be even stronger.
Conversely, in Western countries which had no tradition of mask-wearing, and
which only recommended (rather than mandated) mask-wearing by the public, such as
the United States, the practice has been steadily increasing, but change has not been
Much of the randomized controlled data on the effect of mask-wearing on the
spread of respiratory viruses relates to influenza. One recent meta-analysis of 10 trials
in families, students, or religious pilgrims found that the relative risk for influenza with
the use of face masks was 0.78, a 22% reduction, though the findings were not
statistically significant.110 Combining all the trials, there were 29 cases in groups
assigned to wear masks, compared with 51 cases in control groups.110 The direct
applicability of these results to mask-wearing at the population level is uncertain. For
instance, there was some heterogeneity in methods of the component trials, with one
trial assigning mask wearing to the person with a respiratory illness, another to his close
contacts, and the remainder to both the ill and their contacts.110 Mask-wearing was
inconsistent. The groups living together could not wear a mask when bathing, sleeping,
eating, or brushing teeth.111-113 In one of the studies reviewed, parents wore a mask
during the day, but not at night when sleeping next to their sick child.113 In a different
trial, students were asked to wear a mask in their residence hall for at least 6 hours
daily (rather than all the time).111 The bottom line is that it is nearly impossible for
people to constantly maintain mask wear around the people with whom they live. In
contrast, wearing a mask when on public transit or shopping is quite feasible. In
addition, as an infection propagates through multiple generations in the population, the
benefits multiply exponentially. Even if one accepts that masks would only reduce
transmissions by 22%, then after 10 cycles of the infection, mask-wearing would reduce
the level of infection in the population by 91.7%, as compared with a non-mask wearing
population, at least during the period of exponential growth (because 0.7810 = 0.083). It
is highly unlikely that entire countries or populations will ever be randomized to either
wear, or not wear, masks. Public policies can only be formulated based on the best
Some countries which used masks were better able to maintain or resume
normal business and educational activities. For instance, in Taiwan, schools reopened
on February 21, 2020, with parents directed to purchase 4 to 5 masks per week for
Limits on international travel were significantly associated with lower per-capita
mortality from coronavirus. On the other hand, nationwide policies to ban large
gatherings and to close schools or businesses, tended to be associated with lower
mortality, though not in a statistically significant fashion. However, businesses, schools,
and individuals made decisions to limit contact, independent of any government
policies. The adoption of numerous public health policies at the same time can make it
difficult to tease out the relative importance of each.
Colder average monthly temperature was associated with higher levels of
COVID-19 mortality in univariate analysis, but not when accounting for other
independent variables. One reason that outdoor temperature might have limited
association with the spread of the virus is that most viral transmission occurs indoors.114
We acknowledge that using the average temperature in the country’s largest city during
the outbreak does not model the outbreak as precisely as modelling mortality and
temperature separately in each of the thousands of cities around the world. However,
to a first approximation, our method did serve to control for whether the country’s
climate was tropical, temperate, or polar, and whether the outbreak began in late Winter
(Northern hemisphere) or late Summer (Southern hemisphere). Environmental factors
which could influence either human behavior or the stability and spread of virus particles
are worthy of further study.
Presumably, high levels of testing might identify essentially all coronavirus-
related deaths, and still higher levels of testing, combined with contact tracing, might
lower mortality. Statistical support for the benefit of mass testing could not be
demonstrated. It seems likely that countries which test at a low level are missing many
cases. We identified just 5 countries (Iceland, the Faeroe Islands, the UAE, the
Falkland Islands, and Bahrain) which had tested over one tenth of their population by
May 9. All 5 countries had a mortality of 29 per million (1 in 34,480 people) or less. The
degree to which these results would apply to larger, less isolated, or less wealthy
countries is unknown. Statistical support for benefit of high levels of testing might be
demonstrated if additional and more diverse countries are able to test at this level. The
benefits of contact tracing policies with respect to mortality were of marginal statistical
One limitation of our study is that the ultimate source of mortality data is often
from governments which may not have the resources to provide a full accounting of
their public health crises, or an interest in doing so. It should be noted that the benefit
of wearing masks persisted in a model which excluded data from China (because no
testing data were available, Appendix Table A3). We also acknowledge that country-
wide analyses are subject to the ecologic fallacy.
The source for mortality and testing data we selected is publicly available,7 has
been repeatedly archived,11 contains links to the source government reports for each
country, and agrees with other coronavirus aggregator sites.115 In the interest of
transparency, we presented the per-capita mortality data in Appendix Table A1. One
might question whether any of these data sites or governments provide a complete and
accurate picture of coronavirus mortality. But we must remember that this information
does not exist in a vacuum. Independent sources confirm when mortality has been
high. Social media alerted the world to the outbreaks in Wuhan, Iran, Italy, and New
York. News reports have used aerial photography to confirm the digging of graves in
Iran, New York, and Brazil. Long lines were seen to retrieve remains at crematoria in
Wuhan. Mortuary facilities were inadequate to meet the demand in New York, and
Guayaquil.S85 Conversely, signs of health system overload have been noted to be
absent in the countries reporting low mortality. The health systems in Hong Kong,
Taiwan, Japan, and South Korea are believed to be transparent. Reporters in Vietnam
have even called hospitals and funeral homes to confirm the absence of unusual levels
of activity.S297 Therefore, while no data source is perfect, we believe that the data used
in the paper are consistent with observations from nongovernmental sources, and are
comparable in reliability to those in other scholarly works.
It is not the case that countries which reported no deaths due to coronavirus
simply were not exposed to the virus. All 200 countries analyzed did report COVID-19
cases. Several countries which traditionally use masks and sustained low mortality (or
none) are close to and have strong travel links to China. Some of these countries
reported cases early in the global pandemic (Table 2). Community transmission has
been described in Vietnam.116
The pandemic is a matter of universal concern, but ophthalmologists have
specific reasons to understand and prevent infection with SARS-CoV-2. The virus can
cause a conjunctivitis, and has been identified in tears.117,118 It is possible that
transmission can occur by conjunctival exposure to droplets.117 Ophthalmology was
among the specialties whose residents were at higher risk of coronavirus infection.119
COVID-19 claimed the lives of 3 ophthalmologists from Wuhan Central Hospital,
including 33-year-old Li Wenliang, who was admonished for sharing news of the novel
pneumonia online.117,S61 As of April 15, 2020, at least 8 ophthalmologists had died from
In summary, older age of the population, urbanization, obesity, and longer
duration of the outbreak in a country were independently associated with higher
country-wide per-capita coronavirus mortality. International travel restrictions were
associated with lower per-capita mortality. However, other containment measures,
testing and tracing polices, and the amount of viral testing were not statistically
significant predictors of country-wide coronavirus mortality, after controlling for other
variables. In contrast, societal norms and government policies supporting mask-
wearing by the public were independently associated with lower per-capita mortality
from COVID-19. The use of masks in public is an important and readily modifiable
public health measure.
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Acknowledgements / Disclosures.
Financial Disclosures: The authors have no conflicts of interest.
Author contributions: Design of the study (CL, EI); collection of data (CL, EI, JL, MH);
management and analysis of data (CL, EI); interpretation of the data (CL, EI, JL, CM,
AG); preparation of the manuscript (CL,EI,JL); review and approval of the manuscript
(CL, EI, JL, MH, CM, AG).
Appendix. Supplemental Tables.
Table A1. Per-capita COVID-19 Mortality by May 9 and Date of Mask
Recommendation or Widespread Use Based on Cultural Norms.
(per M. pop.)
by May 9.
Widely Used by
Antigua & Barbuda
Bosnia & Herzegov.
British Virgin Is.
Central Afric. Rep.
Dem. Rep. Congo
Isle of Man
Papua New Guinea
Saint Kitts & Nevis
São Tomé & Príncipe
St. Vincent & Gren.
Trinidad & Tobago
Turks and Caicos
United Arab Emir.
Table A2. Predictors of (log) Country-wide Per-capita Coronavirus Mortality by May 9
by Multivariable Linear Regression in 200 Countries.
Duration in country (weeks)
0.131 to 0.277
Time wearing masks (weeks)
-0.224 to -0.106
Time since international travel
-0.139 to 0.0004
Time in internal lockdown
-0.092 to 0.110
Population, age≥60 (%)
0.035 to 0.076
0.002 to 0.014
-0.018 to 0.017
-8.43 to -6.88
Duration of infection in country from estimated date of first infection until 23 days before May 9, 2020 (i.e.
April 16). Mask and lockdown durations run from the stated event (mask recommendation or lockdown)
or estimated date of first infection in the country (whichever was later) until 23 days before May 9, 2020
(i.e. April 16). Model r2=0.483.
Table A3. Predictors of (log) Country-wide Per-capita Coronavirus Mortality by May 9
by Multivariable Linear Regression in 179 Countries.
Duration in country
0.136 to 0.287
Time wearing masks
-0.199 to -0.072
Time in lockdown (weeks)
-0.113 to 0.102
controls (time since start,
-0.135 to 0.013
Population, % age 60 or
0.015 to 0.061
-0.002 to 0.013
Obesity prevalence (%)
-0.003 to 0.036
-0.026 to 0.010
Testing (log per cap., by
-0.127 to 0.328
-8.54 to -6.08
Based on 179 countries with both obesity and testing data by May 9. Duration of infection in country from
estimated date of first infection until 23 days before May 9, 2020 (i.e. April 16). Mask and lockdown
durations run from the stated event (mask recommendation or lockdown) or estimated date of first
infection in the country (whichever was later) until 23 days before May 9, 2020 (i.e. April 16). Model
Table A4. Predictors of (log) Country-wide Per-capita Coronavirus Mortality by May 9
by Multivariable Linear Regression in 200 Countries, with Mask Wear Determined by
Recommendations and Surveys (When Available).
Duration in country (weeks)
0.131 to 0.277
Time wearing masks (weeks)
-0.224 to -0.106
Time in lockdown (weeks)
-0.092 to 0.110
Time since start of international
travel controls (weeks)
-0.139 to 0.0004
Population, age≥60 (%)
0.035 to 0.076
0.002 to 0.014
-0.018 to 0.017
-8.434 to -6.882
` Duration of infection in country from estimated date of first infection until 23 days before May 9, 2020
(i.e. April 16). Mask and lockdown durations run from the stated event (mask recommendation or
lockdown) or estimated date of first infection in the country (whichever was later) until 23 days before May
9, 2020 (i.e. April 16). Model r2=0.483.
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