Subject: Re: Our standing WB offer to support the government of Georgia during the COVID-19 crisis
From: Sebastian-A Molineus <[email-masked]>
To: "[email-masked]" <[email-masked]>, "[email-masked]" <[email-masked]>
Cc: "[email-masked]" <[email-masked]>, "[email-masked]" <[email-masked]>, Evgenij Najdov <[email-masked]>, Lire Ersado <[email-masked]>, Abdulaziz Faghi <[email-masked]>, Jan Van Bilsen <[email-masked]>
Date: Fri, 03 Apr 2020 17:37:31 +0000

My last email for the week and over the weekend, I promise, but I did think it important to share this scientific article confirming the effectiveness of surgical face masks (contrary what was initially reported) as it could influence preventive measures taken
by the govt. moving forward.

Respiratory virus shedding in exhaled breath and efficacy of face masks | Nature Medicine

https://www.nature.com/articles/s41591-020-0843-2

Respiratory virus shedding in exhaled breath and efficacy of face masks

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April 2020

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Abstract

We identified seasonal human coronaviruses, influenza viruses and rhinoviruses in exhaled breath and coughs of children and adults with acute respiratory illness. Surgical face masks significantly reduced detection of influenza virus
RNA in respiratory droplets and coronavirus RNA in aerosols, with a trend toward reduced detection of coronavirus RNA in respiratory droplets. Our results indicate that surgical face masks could prevent transmission of human coronaviruses and influenza viruses
from symptomatic individuals.

Main

Respiratory virus infections cause a broad and overlapping spectrum of symptoms collectively referred to as acute respiratory virus illnesses (ARIs) or more commonly the ‘common cold’. Although mostly mild, these ARIs can sometimes
cause severe disease and death1.
These viruses spread between humans through direct or indirect contact, respiratory droplets (including larger droplets that fall rapidly near the source as well as coarse aerosols with aerodynamic diameter >5 µm) and fine-particle aerosols (droplets and droplet
nuclei with aerodynamic diameter ≤5 µm)2,3.
Although hand hygiene and use of face masks, primarily targeting contact and respiratory droplet transmission, have been suggested as important mitigation strategies against influenza virus transmission4,
little is known about the relative importance of these modes in the transmission of other common respiratory viruses2,3,5.
Uncertainties similarly apply to the modes of transmission of COVID-19 (refs. 6,7).

Some health authorities recommend that masks be worn by ill individuals to prevent onward transmission (source control)4,8.
Surgical face masks were originally introduced to protect patients from wound infection and contamination from surgeons (the wearer) during surgical procedures, and were later adopted to protect healthcare workers against acquiring infection from their patients.
However, most of the existing evidence on the filtering efficacy of face masks and respirators comes from in vitro experiments with nonbiological particles9,10,
which may not be generalizable to infectious respiratory virus droplets. There is little information on the efficacy of face masks in filtering respiratory viruses and reducing viral release from an individual with respiratory infections8,
and most research has focused on influenza11,12.

Here we aimed to explore the importance of respiratory droplet and aerosol routes of transmission with a particular focus on coronaviruses, influenza viruses and rhinoviruses, by quantifying the amount of respiratory virus in exhaled
breath of participants with medically attended ARIs and determining the potential efficacy of surgical face masks to prevent respiratory virus transmission.

Results

We screened 3,363 individuals in two study phases, ultimately enrolling 246 individuals who provided exhaled breath samples (Extended Data Fig. 1).
Among these 246 participants, 122 (50%) participants were randomized to not wearing a face mask during the first exhaled breath collection and 124 (50%) participants were randomized to wearing a face mask. Overall, 49 (20%) voluntarily provided a second exhaled
breath collection of the alternate type.

Infections by at least one respiratory virus were confirmed by reverse transcription PCR (RT–PCR) in 123 of 246 (50%) participants. Of these 123 participants, 111 (90%) were infected by human (seasonal) coronavirus (n = 17),
influenza virus (n = 43) or rhinovirus (n = 54) (Extended Data Figs. 1 and 2),
including one participant co-infected by both coronavirus and influenza virus and another two participants co-infected by both rhinovirus and influenza virus. These 111 participants were the focus of our analyses.

There were some minor differences in characteristics of the 111 participants with the different viruses (Table 1a).
Overall, 24% of participants had a measured fever ≥37.8 °C, with patients with influenza more than twice as likely than patients infected with coronavirus and rhinovirus to have a measured fever. Coronavirus-infected participants coughed the most with an average
of 17 (s.d. = 30) coughs during the 30-min exhaled breath collection. The profiles of the participants randomized to with-mask versus without-mask groups were similar (Supplementary Table 1).

Table
1a Characteristics of individuals with symptomatic coronavirus, influenza virus or rhinovirus infection

Full
size table

We tested viral shedding (in terms of viral copies per sample) in nasal swabs, throat swabs, respiratory droplet samples and aerosol samples and compared the latter two between samples collected with or without a face mask (Fig. 1).
On average, viral shedding was higher in nasal swabs than in throat swabs for each of coronavirus (median 8.1 log10 virus copies per sample versus 3.9), influenza virus (6.7 versus 4.0)
and rhinovirus (6.8 versus 3.3), respectively. Viral RNA was identified from respiratory droplets and aerosols for all three viruses, including 30%, 26% and 28% of respiratory droplets and 40%, 35% and 56% of aerosols collected while not wearing a face mask,
from coronavirus, influenza virus and rhinovirus-infected participants, respectively (Table 1b).
In particular for coronavirus, we identified OC43 and HKU1 from both respiratory droplets and aerosols, but only identified NL63 from aerosols and not from respiratory droplets (Supplementary Table 2 and
Extended Data Fig. 3).

Fig.
1: Efficacy of surgical face masks in reducing respiratory virus shedding in respiratory droplets and aerosols of symptomatic individuals with coronavirus, influenza virus or rhinovirus infection.

a–c, Virus copies per sample collected in nasal swab (red), throat swab (blue) and respiratory droplets collected for 30min
while not wearing (dark green) or wearing (light green) a surgical face mask, and aerosols collected for 30min while not wearing (brown) or wearing (orange) a face mask, collected from individuals with acute respiratory symptoms who were positive for coronavirus
(a), influenza virus (b) and rhinovirus (c), as determined by RT–PCR in any samples. Pvalues for mask intervention as predictor
of log10 virus copies per sample in an unadjusted univariate Tobit regression model which allowed for censoring at the lower limit of detection of the RT–PCR assay are shown, with significant
differences in bold. For nasal swabs and throat swabs, all infected individuals were included (coronavirus, n=17; influenza virus, n=43; rhinovirus, n=54). For
respiratory droplets and aerosols, numbers of infected individuals who provided exhaled breath samples while not wearing or wearing a surgical face mask, respectively were: coronavirus (n=10 and 11), influenza virus (n=23
and 28) and rhinovirus (n=36 and 32). A subset of participants provided exhaled breath samples for both mask interventions (coronavirus, n=4; influenza virus, n=8;
rhinovirus, n=14). The box plots indicate the median with the interquartile range (lower and upper hinge) and ±1.5×interquartile range from the first and third quartile (lower and upper whiskers).

Full
size image

Table
1b Efficacy of surgical face masks in reducing respiratory virus frequency of detection and viral shedding in respiratory droplets and aerosols of symptomatic individuals with coronavirus, influenza virus or rhinovirus infection

Full
size table

We detected coronavirus in respiratory droplets and aerosols in 3 of 10 (30%) and 4 of 10 (40%) of the samples collected without face masks, respectively, but did not detect any virus in respiratory droplets or aerosols collected
from participants wearing face masks, this difference was significant in aerosols and showed a trend toward reduced detection in respiratory droplets (Table 1b).
For influenza virus, we detected virus in 6 of 23 (26%) and 8 of 23 (35%) of the respiratory droplet and aerosol samples collected without face masks, respectively. There was a significant reduction by wearing face masks to 1 of 27 (4%) in detection of influenza
virus in respiratory droplets, but no significant reduction in detection in aerosols (Table 1b).
Moreover, among the eight participants who had influenza virus detected by RT–PCR from without-mask aerosols, five were tested by viral culture and four were culture-positive. Among the six participants who had influenza virus detected by RT–PCR from with-mask
aerosols, four were tested by viral culture and two were culture-positive. For rhinovirus, there were no significant differences between detection of virus with or without face masks, both in respiratory droplets and in aerosols (Table 1b).
Conclusions were similar in comparisons of viral shedding (Table 1b). In addition,
we found a significant reduction in viral shedding (Supplementary Table 2)
in respiratory droplets for OC43 (Extended Data Fig. 4) and influenza B virus
(Extended Data Fig. 5) and in aerosols for NL63 (Extended Data Fig. 4).

We identified correlations between viral loads in different samples (Extended Data Figs. 6–8)
and some evidence of declines in viral shedding by time since onset for influenza virus but not for coronavirus or rhinovirus (Extended Data Fig. 9).
In univariable analyses of factors associated with detection of respiratory viruses in various sample types, we did not identify significant association in viral shedding with days since symptom onset (Supplementary Table 3)
for respiratory droplets or aerosols (Supplementary Tables 4–6).

A subset of participants (72 of 246, 29%) did not cough at all during at least one exhaled breath collection, including 37 of 147 (25%) during the without-mask and 42 of 148 (28%) during the with-mask breath collection. In the subset
for coronavirus (n = 4), we did not detect any virus in respiratory droplets or aerosols from any participants. In the subset for influenza virus (n = 9), we detected virus in aerosols but not
respiratory droplets from one participant. In the subset for rhinovirus (n = 17), we detected virus in respiratory droplets from three participants, and we detected virus in aerosols in five participants.

Discussion

Our results indicate that aerosol transmission is a potential mode of transmission for coronaviruses as well as influenza viruses and rhinoviruses. Published studies detected respiratory viruses13,14such
as influenza12,15 and
rhinovirus16 from
exhaled breath, and the detection of SARS-CoV17and
MERS-CoV18 from
air samples (without size fractionation) collected from hospitals treating patients with severe acute respiratory syndrome and Middle East respiratory syndrome, but ours demonstrates detection of human seasonal coronaviruses in exhaled breath, including the
detection of OC43 and HKU1 from respiratory droplets and NL63, OC43 and HKU1 from aerosols.

Our findings indicate that surgical masks can efficaciously reduce the emission of influenza virus particles into the environment in respiratory droplets, but not in aerosols12.
Both the previous and current study used a bioaerosol collecting device, the Gesundheit-II (G-II)12,15,19,
to capture exhaled breath particles and differentiated them into two size fractions, where exhaled breath coarse particles >5 μm (respiratory droplets) were collected by impaction with a 5-μm slit inertial Teflon impactor and the remaining fine particles ≤5 μm
(aerosols) were collected by condensation in buffer. We also demonstrated the efficacy of surgical masks to reduce coronavirus detection and viral copies in large respiratory droplets and in aerosols (Table 1b).
This has important implications for control of COVID-19, suggesting that surgical face masks could be used by ill people to reduce onward transmission.

Among the samples collected without a face mask, we found that the majority of participants with influenza virus and coronavirus infection did not shed detectable virus in respiratory droplets or aerosols, whereas for rhinovirus
we detected virus in aerosols in 19 of 34 (56%) participants (compared to 4 of 10 (40%) for influenza and 8 of 23 (35%) for coronavirus). For those who did shed virus in respiratory droplets and aerosols, viral load in both tended to be low (Fig. 1).
Given the high collection efficiency of the G-II (ref. 19)
and given that each exhaled breath collection was conducted for 30 min, this might imply that prolonged close contact would be required for transmission to occur, even if transmission was primarily via aerosols, as has been described for rhinovirus colds20.
Our results also indicate that there could be considerable heterogeneity in contagiousness of individuals with coronavirus and influenza virus infections.

The major limitation of our study was the large proportion of participants with undetectable viral shedding in exhaled breath for each of the viruses studied. We could have increased the sampling duration beyond 30 min to increase
the viral shedding being captured, at the cost of acceptability in some participants. An alternative approach would be to invite participants to perform forced coughs during exhaled breath collection12.
However, it was the aim of our present study to focus on recovering respiratory virus in exhaled breath in a real-life situation and we expected that some individuals during an acute respiratory illness would not cough much or at all. Indeed, we identified
virus RNA in a small number of participants who did not cough at all during the 30-min exhaled breath collection, which would suggest droplet and aerosol routes of transmission are possible from individuals with no obvious signs or symptoms. Another limitation
is that we did not confirm the infectivity of coronavirus or rhinovirus detected in exhaled breath. While the G-II was designed to preserve viability of viruses in aerosols, and in the present study we were able to identify infectious influenza virus in aerosols,
we did not attempt to culture coronavirus or rhinovirus from the corresponding aerosol samples.

Methods

Study design

Participants were recruited year-round from March 2013 through May 2016 in a general outpatient clinic of a private hospital in Hong Kong. As routine practice, clinic staff screened all individuals attending the clinics for respiratory
and any other symptoms regardless of the purpose of the visit at triage. Study staff then approached immediately those who reported at least one of the following symptoms of ARI for further screening: fever ≥37.8 °C, cough, sore throat, runny nose, headache,
myalgia and phlegm. Individuals who reported ≥2 ARI symptoms, within 3 d of illness onset and ≥11 years of age were eligible to participate. After explaining the study to and obtaining informed consent from the participants, a rapid influenza diagnostic test,
the Sofia Influenza A + B Fluorescent Immunoassay Analyzer (cat. no. 20218, Quidel), was used to identify influenza A or B virus infection as an incentive to participate. All participants provided a nasal swab for the rapid test and an additional nasal swab
and a separate throat swab for subsequent virologic confirmation at the laboratory. All participants also completed a questionnaire to record basic information including age, sex, symptom severity, medication, medical conditions and smoking history. In the
first phase of the study from March 2013 to February 2014 (‘Influenza Study’), the result of the rapid test was used to determine eligibility for further participation in the study and exhaled breath collection, whereas in the second phase of the study from
March 2014 to May 2016 (‘Respiratory Virus Study’), the rapid test did not affect eligibility. Eligible participants were then invited to provide an exhaled breath sample for 30 min in the same clinic visit.

Before exhaled breath collection, each participant was randomly allocated in a 1:1 ratio to either wearing a surgical face mask (cat. no. 62356, Kimberly-Clark) or not during the collection. To mimic the real-life situation, under
observation by the study staff, participants were asked to attach the surgical mask themselves, but instruction on how to wear the mask properly was given when the participant wore the mask incorrectly. Participants were instructed to breathe as normal during
the collection, but (natural) coughing was allowed and the number of coughs was recorded by study staff. Participants were then invited to provide a second exhaled breath sample of the alternate type (for example if the participant was first assigned to wearing
a mask they would then provide a second sample without a mask), but most participants did not agree to stay for a second measurement because of time constraints. Participants were compensated for each 30-min exhaled breath collection with a supermarket coupon
worth approximately US$30 and all participants were gifted a tympanic thermometer worth approximately US$20.

Ethical approval

Written informed consent was obtained from all participants ≥18 years of age and written informed consent was obtained from parents or legal guardians of participants 11–17 years of age in addition to their own written informed consent.
The study protocol was approved by the Institutional Review Board of The University of Hong Kong and the Clinical and Research Ethics Committee of Hong Kong Baptist Hospital.

Collection of swabs and exhaled breath particles

Nasal swabs and throat swabs were collected separately, placed in virus transport medium, stored and transported to the laboratory at
2–8 °C and the virus transport medium was aliquoted and stored at −70 °C until further analysis. Exhaled breath particles were captured and differentiated into two size fractions, the coarse fraction containing particles with aerodynamic diameter >5 μm
(referred to here as ‘respiratory droplets’), which included droplets up to approximately 100 µm in diameter and the fine fraction with particles ≤5 μm (referred to here as ‘aerosols’) by the G-II bioaerosol collecting device12,15,19.
In the G-II device, exhaled breath coarse particles >5 μm were collected by a 5-μm slit inertial Teflon impactor and the remaining fine particles ≤5 μm were condensed and collected into approximately 170 ml of 0.1% BSA/PBS. Both the impactor and the condensate
were stored and transported to the laboratory at
2–8 °C. The virus on the impactor was recovered into 1 ml and the condensate was concentrated into 2 ml of 0.1% BSA/PBS, aliquoted and stored at −70 °C until further analysis. In a validation study, the G-II was able to recover over 85% of fine particles
>0.05 µm in size and had comparable collection efficiency of influenza virus as the SKC BioSampler19.

Laboratory testing

Samples collected from the two studies were tested at the same time. Nasal swab samples were first tested by a diagnostic-use viral panel, xTAG Respiratory Viral Panel (Abbott Molecular) to qualitatively detect 12 common respiratory
viruses and subtypes including coronaviruses (NL63, OC43, 229E and HKU1), influenza A (nonspecific, H1 and H3) and B viruses, respiratory syncytial virus, parainfluenza virus (types 1–4), adenovirus, human metapneumovirus and enterovirus/rhinovirus. After
one or more of the candidate respiratory viruses was detected by the viral panel from the nasal swab, all the samples from the same participant (nasal swab, throat swab, respiratory droplets and aerosols) were then tested with RT–PCR specific for the candidate
virus(es) for determination of virus concentration in the samples. Infectious influenza virus was identified by viral culture using MDCK cells as described previously21,
whereas viral culture was not performed for coronavirus and rhinovirus.

Statistical analyses

The primary outcome of the study was virus generation rate in tidal breathing of participants infected by different respiratory viruses and the efficacy of face masks in preventing virus dissemination in exhaled breath, separately
considering the respiratory droplets and aerosols. The secondary outcomes were correlation between viral shedding in nose swabs, throat swabs, respiratory droplets and aerosols and factors affecting viral shedding in respiratory droplets and aerosols.

We identified three groups of respiratory viruses with the highest frequency of infection as identified by RT–PCR, namely coronavirus (including NL63, OC43, HKU1 and 229E), influenza virus and rhinovirus, for further statistical
analyses. We defined viral shedding as log10 virus copies per sample and plotted viral shedding in each sample (nasal swab, throat swab, respiratory droplets and aerosols); the latter two
were stratified by mask intervention. As a proxy for the efficacy of face masks in preventing transmission of respiratory viruses via respiratory droplet and aerosol routes, we compared the respiratory virus viral shedding in respiratory droplet and aerosol
samples between participants wearing face masks or not, by comparing the frequency of detection with a two-sided Fisher’s exact test and by comparing viral load (defined as log10 virus
copies per sample) by an unadjusted univariate Tobit regression model, which allowed for censoring at the lower limit of detection of the RT–PCR assay. We also used the unadjusted univariate Tobit regression to investigate factors affecting viral shedding
in respiratory droplets and aerosols without mask use, for example age, days since symptom onset, previous influenza vaccination, current medication and number of coughs during exhaled breath collection. We investigated correlations between viral shedding
in nasal swab, throat swab, respiratory droplets and aerosols with scatter-plots and calculated the Spearman’s rank correlation coefficient between any two types of samples. We imputed 0.3 log10 virus
copies ml−1 for undetectable values before transformation to log10 virus copies per sample. All analyses were conducted
with R v.3.6.0 (ref. 22)
and the VGAM package v.1.1.1 (ref. 23).

Reporting Summary

Further information on research design is available in the Nature
Research Reporting Summary linked to this article.

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Acknowledgements

This work was supported by the General Research Fund of the University Grants Committee (grant no. 765811), the Health and Medical Research Fund (grant no. 13120592)
and a commissioned grant of the Food and Health Bureau and the Theme-based Research Scheme (project no. T11-705/14-N) of the Research Grants Council of the Hong Kong SAR Government. We acknowledge colleagues including R. O. P. Fung, A. K. W. Li, T. W. Y. Ng,
T. H. C. So, P. Wu and Y. Xie for technical support in preparing and conducting this study and enrolling participants; J. K. M. Chan, S. Y. Ho, Y. Z. Liu and A. Yu for laboratory support; S. Ferguson, W. K. Leung, J. Pantelic, J. Wei and M. Wolfson for technical
support in constructing and maintaining the G-II device; V. J. Fang, L. M. Ho and T. T. K. Lui for setting up the database; and C. W. Y. Cheung, L. F. K. Cheung, P. T. Y. Ching, A. C. H. Lai, D. W. Y. Lam, S. S. Y. Lo, A. S. K. Luk and other colleagues at
the Outpatient Center and Infection Control Team of Hong Kong Baptist Hospital for facilitating this study.

Author information

These authors jointly supervised this work: Donald K. Milton, Benjamin J. Cowling.

Affiliations

WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine,
The University of Hong Kong, Hong Kong, China

Nancy H. L. Leung

, Daniel K. W. Chu

, Eunice Y. C. Shiu

, Benien J. P. Hau

, Hui-Ling Yen

, Dennis K. M. Ip

, J. S. Malik Peiris

, Wing-Hong Seto

, Gabriel M. Leung

& Benjamin J. Cowling

Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

Kwok-Hung Chan

Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA

James J. McDevitt

Department of Surgery, Queen Mary Hospital, Hong Kong, China

Benien J. P. Hau

Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China

Yuguo Li

Department of Pathology, Hong Kong Baptist Hospital, Hong Kong, China

Wing-Hong Seto

Maryland Institute for Applied Environmental Health, School of Public Health, University of Maryland, College Park, MD, USA

Donald K. Milton

Contributions

All authors meet the International Committee of Medical Journal Editors criteria for authorship. The study protocol was drafted by N.H.L.L. and B.J.C. Data were collected by N.H.L.L., E.Y.C.S. and B.J.P.H. Laboratory testing was
performed by D.K.W.C. and K.-H.C. Statistical analyses were conducted by N.H.L.L. N.H.L.L. and B.J.C. wrote the first draft of the manuscript, and all authors provided critical review and revision of the text and approved the final version.

Corresponding author

Correspondence to Benjamin J. Cowling.

Ethics declarations

Competing interests

B.J.C. consults for Roche and Sanofi Pasteur. The authors declare no other competing interests.

Additional information

Peer review information Alison Farrell was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended
Data Fig. 1

Participant enrolment, randomization of mask intervention and identification of respiratory virus infection.

Extended
Data Fig. 2 Weekly number of respiratory virus infections identified by RT-PCR in symptomatic individuals who had provided exhaled breath samples (respiratory droplets and aerosols) during the study period.

Blue, coronavirus; red, influenza virus; yellow, rhinovirus; green, other respiratory viruses including human metapneumovirus, parainfluenza virus, respiratory syncytial virus and adenovirus; white, no respiratory virus infection
identified.

Extended
Data Fig. 3 Respiratory virus shedding in (a) nasal swab, (b) throat swab, (c) respiratory droplets and (d) aerosols in symptomatic individuals with coronavirus NL63, coronavirus OC43, coronavirus HKU1, influenza A and influenza B virus infection.

For nasal swabs and throat swabs, all infected individuals identified by RT-PCR in any collected samples were included: coronavirus NL63 (n = 8), coronavirus OC43 (n = 5), coronavirus HKU1 (n = 4), influenza A virus (n = 31) and
influenza B virus (n = 14). For respiratory droplets and aerosols, only infected individuals who provided exhaled breath samples while not wearing a surgical face mask were included: coronavirus NL63 (n = 3), coronavirus OC43 (n = 3), coronavirus HKU1 (n = 4),
influenza A virus (n = 19) and influenza B virus (n = 6). The box plots indicate the median with the interquartile range (lower and upper hinge) and ± 1.5 × interquartile range from the first and third quartile (lower and upper whisker). Dark blue, coronavirus
NL63; light blue, coronavirus OC43; brown, coronavirus HKU1; red, influenza A virus; orange, influenza B virus.

Extended
Data Fig. 4 Efficacy of surgical face masks in reducing respiratory virus shedding in respiratory droplets and aerosols of symptomatic individuals with seasonal coronaviruses including (a) coronavirus NL63, (b) coronavirus OC43 and (c) coronavirus HKU1.

The figure shows the virus copies per sample collected in nasal swab (red), throat swab (blue), respiratory droplets collected for 30 min while not wearing (dark green) or wearing (light green) a surgical face mask and aerosols collected
for 30 min while not wearing (brown) or wearing (orange) a face mask, collected from individuals with acute respiratory symptoms who were positive for coronavirus NL63, coronavirus OC43 and coronavirus HKU1 as determined by RT-PCR in any samples. P values
for mask intervention as predictor of log10virus copies per sample in an unadjusted univariate Tobit regression model which allowed for censoring at the lower limit of detection of the
RT-PCR assay are shown, with significant differences in bold. For nasal swabs and throat swabs, all infected individuals were included (coronavirus NL63, n = 8; coronavirus OC43, n = 5; coronavirus HKU1, n = 4). For respiratory droplets and aerosols, numbers
of infected individuals who provided exhaled breath samples while not wearing or wearing a surgical face mask, respectively were: coronavirus NL63 (n = 3 and 5), coronavirus OC43 (n = 3 and 4), coronavirus HKU1 (n = 4 and 2). A subset of participants provided
exhaled breath samples for both mask interventions (coronavirus NL63, n = 0; coronavirus OC43, n = 2; coronavirus HKU1, n = 2).

Extended
Data Fig. 5 Efficacy of surgical face masks in reducing respiratory virus shedding in respiratory droplets and aerosols of symptomatic individuals with seasonal influenza viruses including (a) influenza A and (b) influenza B virus.

The figure shows the virus copies per sample collected in nasal swab (red), throat swab (blue), respiratory droplets collected for 30 min while not wearing (dark green) or wearing (light green) a surgical face mask and aerosols collected
for 30 min while not wearing (brown) or wearing (orange) a face mask, collected from individuals with acute respiratory symptoms who were positive for influenza A and influenza B virus as determined by RT-PCR in any samples. P values
for mask intervention as predictor of log10 virus copies per sample in an unadjusted univariate Tobit regression model which allowed for censoring at the lower limit of detection of the
RT-PCR assay are shown, with significant differences in bold. For nasal swabs and throat swabs, all infected individuals were included (influenza A virus, n = 31; influenza B virus, n = 14). For respiratory droplets and aerosols, numbers of infected individuals
who provided exhaled breath samples while not wearing or wearing a surgical face mask, respectively were: influenza A virus (n = 19 and 19), influenza B virus (n = 6 and 10). A subset of participants provided exhaled breath samples for both mask interventions
(influenza A virus, n = 7; influenza B virus, n = 2).

Extended
Data Fig. 6 Correlation of coronavirus viral shedding between different samples (nasal swab, throat swab, respiratory droplets and aerosols) in symptomatic individuals with seasonal coronavirus infection.

For nasal swabs and throat swabs, all infected individuals were included (n = 17). For respiratory droplets and aerosols, only infected individuals who provided exhaled breath samples while not wearing a surgical face mask were included
(n = 10). r, the Spearman’s rank correlation coefficient.

Extended
Data Fig. 7 Correlation of influenza viral shedding between different samples (nasal swab, throat swab, respiratory droplets and aerosols) in symptomatic individuals with seasonal influenza infection.

For nasal swabs and throat swabs, all infected individuals were included (n = 43). For respiratory droplets and aerosols, only infected individuals who provided exhaled breath samples while not wearing a surgical face mask were included
(n = 23). r, the Spearman’s rank correlation coefficient.

Extended
Data Fig. 8 Correlation of rhinovirus viral shedding between different samples (nasal swab, throat swab, respiratory droplets and aerosols) in symptomatic individuals with rhinovirus infection.

For nasal swabs and throat swabs, all infected individuals were included (n = 54). For respiratory droplets and aerosols, only infected individuals who provided exhaled breath samples while not wearing a surgical face mask were included
(n = 36). r, the Spearman’s rank correlation coefficient.

Extended
Data Fig. 9 Respiratory virus shedding in respiratory droplets and aerosols stratified by days from symptom onset for (a) coronavirus, (b) influenza virus or (c) rhinovirus.

The figures shows the virus copies per sample collected in nasal swab (red), throat swab (blue), respiratory droplets (dark green) and aerosols (brown) collected for 30 min while not wearing a surgical face mask, stratified by the
number of days from symptom onset on which the respiratory droplets and aerosols were collected. For nasal swabs and throat swabs, all infected individuals were included (coronavirus, n = 17; influenza virus, n = 43; rhinovirus, n = 54). For respiratory droplets
and aerosols, numbers of infected individuals who provided exhaled breath samples while not wearing or wearing a surgical face mask, respectively were: coronavirus (n = 10 and 11), influenza virus (n = 23 and 28), rhinovirus (n = 36 and 32). A subset of participants
provided exhaled breath samples for both mask interventions (coronavirus, n = 4; influenza virus, n = 8; rhinovirus, n = 14). The box plots indicate the median with the interquartile range (lower and upper hinge) and ± 1.5 × interquartile range from the first
and third quartile (lower and upper whisker).

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Leung, N.H.L., Chu, D.K.W., Shiu, E.Y.C. et al. Respiratory virus shedding in exhaled breath and efficacy of face masks. Nat Med(2020). https://doi.org/10.1038/s41591-020-0843-2

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Received02 March 2020

Accepted20 March 2020

Published03 April 2020

DOIhttps://doi.org/10.1038/s41591-020-0843-2

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Kind regards,

Sebastian

Sebastian Molineus

Regional Director for the South Caucasus

Europe and Central Asia, The World Bank

T: +995 (32) 291 30 96

M:+995
(577) 78 78 21

M: +1
(202) 492 3914

www.worldbank.org/en/region/eca

www.linkedin.com/in/molineus

Follow me on Twitter @SMolineus

Sent from my iPhone

On Apr 3, 2020, at 19:33, Sebastian-A Molineus wrote:

 Dear colleagues -

Please find below and attached an update on social protection measures from across the world.

FYI, the number of countries with measures in place is now triple-digit; more cash transfers than ever; COVID-related social assistance is benefiting almost 600 million
people; lots of action in social insurance (mostly paid sick leave) as well as labor markets (largely wage subsidies).

Here are stylized facts to help synthesize current global trends:

Fact #1. As of today, a total of 106 countries have introduced or adapted social protection and jobs programs in response to COVID-19. This is an 26% increase since last
week (when countries were 84), while the number of programs grew by almost 50%, i.e., from 283 to 418. Among classes of interventions, social assistance (non-contributory transfers) keeps being the most widely used (including a total of 241 programs), followed
by actions in social insurance (116) and supply-side labor market interventions (61).

Fact #2. Within social assistance, cash transfer programs are clearly the most widely used intervention by governments: these include 124 programs in 71 countries, with
54 new initiatives introduced specifically as COVID-19 response in 36 countries. Those 124 programs would increase to 149 if social pensions, public works, childcare support and one-off universal basic income (or helicopter money) are considered. Such overall
cash-based portfolio represents over one-third of total social protection programs (35.6%) (see pie below) and 61.8% of social assistance schemes.

Fact #3. More data points on coverage levels are also starting to emerge, especially in social assistance. A preliminary estimate of the number of beneficiaries specifically
supported via COVID-related introductions, expansions, and adaptations of programs is 594 million. Those beneficiaries include both individuals (for programs like public works) and households (e.g., for conditional cash transfers), pending on how they are
reported. On one hand, such estimate is conservative given that not all programs report coverage (especially planned schemes); on the other hand, the estimate also includes schemes for which programs envisioned administrative adaptations, such as providing
the same level of benefits but paid in a more user-friendly way. Clearly, global coverage levels are largely driven by India, but sizable levels can be observed in several countries, especially in Asia.

Fact #4. In terms of social insurance, paid sick leave is the most frequently-adopted measure, including in countries like Algeria, El Salvador, Finland and Lebanon.
Unemployment benefits are also widely used, including for example in Romania, Russia, and South Africa. Deferring or subsidizing social contributions are observed in Montenegro, Germany and the Netherlands among others.

Fact #5. Labor market interventions are another key way in which governments are providing support to formal and informal sector workers (i.e., we don’t include demand-side
actions on the labor markets). Wage subsidies account for 59% of the global labor market portfolio, with programs being implemented in Jamaica, Kosovo, Malaysia and Thailand. Activation measures (worker trainings) are also being considered inter alia in Bosnia
and Herzegovina, China and Romania.

Fact #6. Compared to last week, programs are less unevenly distributed across regions and country income groups. Importantly, measures are being introduced in low-income
countries, although only on social assistance and insurance. In those contexts, social assistance measures mostly include administrative adaptations, in-kind transfers, school feeding, and utility waivers. As such, there appears to be very limited cash transfer
program expanded or introduced (Tajikistan is one example).

Please find attached additional information. I hope you are able to enjoy a bit of the weekend with your families.

Best regards,

Sebastian

Sebastian Molineus

Regional Director for the South Caucasus

Europe and Central Asia, The World Bank

T: +995 (32) 291 30 96

M:+995 (577) 78 78 21

M: +1
(202) 492 3914

www.worldbank.org/en/region/eca

www.linkedin.com/in/molineus

Follow me on Twitter @SMolineus

Sent from my iPad

On Apr 3, 2020, at 17:07, Sebastian-A Molineus wrote:

Dear all – I attach for information the Korea case study shared with us by the government of Korea, in case of interest.

Kind regards,

Sebastian

Sebastian Molineus

Regional Director for the South Caucasus

Europe
and Central Asia

T
+995 (32) 291 6238

M
+995 (577) 78 7821

M
+1 (202) 492-3914

E
[email-masked]

W
www.worldbank.org/en/region/eca

@smolineus

www.linkedin.com/in/molineus/

From: Sebastian-A Molineus

Sent: Friday, March 27, 2020 7:24 PM

To: [email-masked]; [email-masked]

Cc: [email-masked]; [email-masked]; Evgenij Najdov ; Lire Ersado ; Abdulaziz Faghi ; Jan Van Bilsen

Subject: RE: Our standing WB offer to support the government of Georgia during the COVID-19 crisis

Dear Ministers, Dear Ekaterine and Ivane –

Please find attached an updated World Bank paper on Social Protection and Jobs Responses to COVID-19: A Real-Time Review of Country Measures.  I trust you will find this paper useful as you design your social protection policy measures
along with our teams within the framework of the upcoming Fast Track COVID-19 Response Facility that your government has requested.

As usual, we stand ready to support and answer any questions you may have.

Kind regards,

Sebastian

Sebastian Molineus

Regional Director for the South Caucasus

Europe
and Central Asia

T
+995 (32) 291 6238

M
+995 (577) 78 7821

M
+1 (202) 492-3914

E
[email-masked]

W
www.worldbank.org/en/region/eca

@smolineus

www.linkedin.com/in/molineus/

From: Sebastian-A Molineus

Sent: Thursday, March 26, 2020 7:12 PM

To: [email-masked];
[email-masked];
[email-masked]; [email-masked]

Cc: [email-masked];
[email-masked];
[email-masked]; [email-masked]; Evgenij Najdov <[email-masked]>; Lire Ersado <[email-masked]>; Abdulaziz Faghi
<[email-masked]>; Jan Van Bilsen <[email-masked]>

Subject: RE: Our standing WB offer to support the government of Georgia during the COVID-19 crisis

Dear colleagues –

Please find attached a note on ‘Managing the Employment Impacts of the COVID-19 Crisis’, produced by the World Bank Jobs Group. It reviews a variety of available policy options in a succinct and practical manner, and I hope you find it
useful and timely.

As always, please let me know if you have any questions or would like for us to organize a follow-up discussion with our World Bank experts.

Thank you and kind regards,

Sebastian

Sebastian Molineus

Regional Director for the South Caucasus

Europe
and Central Asia

T
+995 (32) 291 6238

M
+995 (577) 78 7821

M
+1 (202) 492-3914

E
[email-masked]

W
www.worldbank.org/en/region/eca

@smolineus

www.linkedin.com/in/molineus/

From: Sebastian-A Molineus

Sent: Tuesday, March 24, 2020 6:27 PM

To: [email-masked];
[email-masked];
[email-masked]; [email-masked]

Cc: [email-masked];
[email-masked];
[email-masked]; Evgenij Najdov <[email-masked]>; Lire Ersado <[email-masked]>; Abdulaziz Faghi <[email-masked]>;
Jan Van Bilsen <[email-masked]>;
[email-masked]

Subject: RE: Our standing WB offer to support the government of Georgia during the COVID-19 crisis

Dear colleagues –

FYI, I am attaching two scientific articles from Harvard University and ISI/ GISC on the effectiveness of social distancing strategies, as well as two World Bank papers, the first of which looks at the lessons-learned from Italy’s COVID-19
response and the second reviewing Global Social Protection Responses to COVID-19, which I know you are contemplating as we speak.  I have summarized key take-aways below:

https://dash.harvard.edu/handle/1/42638988: The SARS-CoV-2 pandemic is straining healthcare resources worldwide, prompting social distancing measures to reduce transmission intensity. The amount
of social distancing needed to curb the SARS-CoV-2 epidemic in the context of seasonally varying transmission remains unclear. Using a mathematical model, we assessed that one-time interventions will be insufficient to maintain COVID-19 prevalence within the
critical care capacity of the United States. Seasonal variation in transmission will facilitate epidemic control during the summer months but could lead to an intense resurgence in the autumn. Intermittent distancing measures can maintain control of the epidemic,
but without other interventions, these measures may be necessary into 2022. Increasing critical care capacity could reduce the duration of the SARS-CoV-2 epidemic while ensuring that critically ill patients receive appropriate care.

https://covid-19-sds.github.io/assets/pdfs/Preliminary_Report_Effectiveness_of_social_distance_strategies_COVID-19.pdf:
Key findings 1. School closures do not have a major impact on controlling the epidemic, despite closing them, infections keep occurring within the households and the community layers. 2. Passive social distance strategies are not enough to contain the epidemic,
indicating that active strategies need to be established. For instance, large scale testing, remote symptoms monitoring, isolation and contact tracing. 3. School closures and self-distancing at 90% of adoption is a feasible strategy for minimizing the effects
of the epidemic, but only if they are applied for a long period of time. 4. A full confinement is not feasible and will not solve the problem, without active measures in place after the confinement, since there would be a new outbreak. 5. If high resolution
mobility data is available, our data-driven approach with real world data can be easily replicated for new cities or countries to measure the impact of social distance strategies and the epidemic.

Early lessons-learned from Italy: In response to previous epidemics of SARS and MERS, China, Singapore, and South Korea overhauled their emergency systems and strengthened public health and disease surveillance response systems, which enabled a swift
response to the COVID-19 pandemics. Different countries worldwide have different levels of preparedness and have adopted different measures to combat COVID-19 pandemic, offering vital insight into the response. Lack of swift disease detection and containment
measures can lead to overwhelmed health systems swiftly, and exceeding healthcare capacity can further exacerbate the community spread of SARS-CoV-2/COVID-19.  Timely disease control measures need to be accompanied with surge capacity to curb the exponential
spread of COVID-19. The evidence suggests that travel restrictions only work if coupled with rapid testing, physical distancing, isolation, infection prevention and Control in HCWs etc. to break the chain of transmission.  In a globalized world where epidemics
and pandemics are increasingly common, pandemic surge planning using the 4 S framework (Space, Stuff, Staff, and System) can enable bolstered surge response. The proposed recommendations contain short, medium, and long-term measures to operationalize surge
response to COVID-19 in Italy; including short-term measures to scale up surge response using the 4 S framework; medium and long-term measures of gap analysis for legislative and institutional reforms, and health system strengthening respectively.

A Global Review of Social Protection Responses to COVID-19: As of March 20, 2020, a total of 45 countries have introduced, adapted or expanded social protection programs in response to COVID-19.
The most widely used measures include: cash transfers (30 programs), followed by wage subsidies (11), subsidized sick leave (10), and various forms of subsidized social security contributions and unemployment insurance.  A total of 13 new cash transfer programs
have been introduced, like for example in Bolivia, India, Iran and Peru.  A universal, one-off cash payment to all citizens will occur in Hong-Kong and Singapore.  New in-kind schemes have also been launched, such as food vouchers in Taiwan and Seattle in
the United States. Countries are adapting existing social assistance programs in various ways, by for instance: (i) anticipating payments of future cash transfer programs (Colombia and Indonesia); (ii) ensuring additional payments, often on a one-off basis
(e.g., Argentina, Armenia, Australia, Turkey); (iii) providing more generous benefit levels (e.g., China); (iv) increasing the coverage of existing cash schemes (e.g., Brazil) and public works (Uzbekistan); (v) enhancing agility by suspending conditionalities
in the UK and Italy; and (vi) providing innovative design solutions, such as school feeding programs delivering food directly to children’s homes or nearby centers (Jamaica and India’s Kerala state) or adapting their financing (Japan).  Income support in the
form of childcare vouchers or allowances were provided in Italy, Poland and South Korea.  Other social assistance programs include support for homeless populations as planned in Spain; utility subsidies waiving fees for basic services are present in El Salvador;
and wavers for loans and other financial obligations (e.g., Bolivia).  Many countries provide cash benefits to crisis-affected self-employed workers (e.g., Ireland, Portugal, New Zealand) and those in the informal sector (India). Some countries (e.g., Netherland)
are reducing work time among the wage employed, combined with paid sick leave. Sweden is reducing the administrative time required for sick-leave payments, while Switzerland is doing so for the unemployment insurance process.  Delivery innovations are also
emerging in Jordan (new cash program using same registration form of existing schemes), Japan (uploading transfers on phones), and Romania (enhanced electronic processes for benefits).

I hope you find these useful.

Kind regards,

Sebastian

Sebastian Molineus

Regional Director for the South Caucasus

Europe
and Central Asia

T
+995 (32) 291 6238

M
+995 (577) 78 7821

M
+1 (202) 492-3914

E
[email-masked]

W
www.worldbank.org/en/region/eca

@smolineus

www.linkedin.com/in/molineus/

From: Sebastian-A Molineus

Sent: Sunday, March 22, 2020 12:31 PM

To: [email-masked];
[email-masked];
[email-masked]

Cc: [email-masked];
[email-masked];
[email-masked]; Evgenij Najdov <[email-masked]>; Lire Ersado <[email-masked]>; Abdulaziz Faghi <[email-masked]>;
Jan Van Bilsen <[email-masked]>

Subject: RE: Our standing WB offer to support the government of Georgia during the COVID-19 crisis

Dear Ministers and Governor, Dear Natia, Ivane, and
Koba -

please find attached a global compendium of financial sector policy measures relevant to combatting the economic fall-out from COVID-19.  The document remains a work in progress
and is in draft form, but given the speed at which everything is evolving I’d rather share this document with you sooner than later.  I will of course continue to share relevant updates with you.  I also share with you a set of broader policy measures undertaken
by the EU member countries, again for info.

COVID-19 outbreak: Classification of Policy Measures Related to the Financial Sector

Draft March 18, 2020

Monetary and liquidity measures

Easing of policy rates

Liquidity support (e.g., OMO/repo, standing facilities, FX, minimum reserve requirements, collateral)

Credit easing (e.g. purchases of corporate, government, MBS paper; outright support to SMEs)

Easing Emergency Liquidity Assistance (e.g., loosening of collateral criteria)

Financial institution measures

Prudential and integrity

Easing/draw down of capital buffers (e.g., counter-cyclical, capital conservation)

Easing limits on large exposures

Easing of liquidity requirements (in foreign and local currency)

Forbearance of NPL classification, past due classification

Suspension of accounting standards (e.g. IFRS 9) or provisioning rules

Lower certain risks weights (e.g., loans with government guarantees)

Easing of macro-prudential measures (e.g., LTVs, DTIs)

Restrictions on dividend payments

Limit foreign exposures of banks and non-bank financial institutions

Ensure compliance of critical conduct and integrity rules to mitigate market abuse

Support for borrowers in affected sectors (e.g., SMEs, tourism, exporters)

Encourage private institutions to provide short-term cash support, waive fees and penalties, etc.

Moratorium on repayments, incl. mortgages (e.g., missed payments added to principal)

Support targeted restructuring of loans

State (partial) guarantees on loans

State subsidies on borrowers’ repayments

State loans to affected companies, sectors (e.g., through state banks or C)

Crisis management

State guarantees on bank liabilities (e.g., deposit guarantees to avert runs)

Freeze on deposit withdrawals

Freeze on withdrawal of open-ended funds

Capital injections, bailouts, bail-ins, and nationalization

Additional (backstop) funding to deposit guarantee schemes

Other measures

Intensification of industry consultation, monitoring of large companies, and key markets

Review business continuity and disaster recovery plans

Review of supervisory reporting requirements and methods as staff cannot access systems

Closing of bank branches and ATMs to prevent COVID-19 spread

Stimulate use of digital payments to prevent COVID-19 spread

Review regulations (KYC) to allow for remote interactions (e.g. refinancing mortgages, SME loans)

Financial markets measures

Market support

FX market interventions by Central Bank

FX swap lines with other Central Banks

Outright asset purchases (e.g., securities of affected companies, sectors)

Market intervention

Halting of trading, bans on (naked) short selling

Temporary restrictions on cross-border capital (out)flows

Public Debt Management measures

Establish basis for decision-making and developing communications strategy

Identify funding from other sources to reduce pressure on traditional wholesale market borrowing

Adapt the funding program to shifts in the demand for government paper

Ensure minimal functionality in the primary and secondary markets

Kind regards,

Sebastian

Sebastian Molineus

Regional Director for the South Caucasus

<20200321_Korea_Response.pdf>