From the journal Environmental Science: Atmospheres Peer review history

18-Jul-2021

Dear Dr Hoffmann:

Manuscript ID: EA-ART-02-2021-000013
TITLE: Speech-generated Aerosol Settling Times and Viral Viability Predict COVID-19 Transmission Efficiency

Thank you for your submission to Environmental Science: Atmospheres, published by the Royal Society of Chemistry. I sent your manuscript to reviewers and I have now received their reports which are copied below. It has been challenging to find reviewers who felt they had the necessary time and expertise to review your manuscript and I thank you for your patience during the time it has taken as a consequence to obtain the necessary amount of reviews of your manuscript.

I have now carefully evaluated your manuscript and the reviewers’ reports, and the reports indicate that major revisions are necessary.

Please submit a revised manuscript which addresses all of the reviewers’ comments. Further peer review of your revised manuscript may be needed. When you submit your revised manuscript please include a point by point response to the reviewers’ comments and highlight the changes you have made. Full details of the files you need to submit are listed at the end of this email.

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The Royal Society of Chemistry requires all submitting authors to provide their ORCID iD when they submit a revised manuscript. This is quick and easy to do as part of the revised manuscript submission process. We will publish this information with the article, and you may choose to have your ORCID record updated automatically with details of the publication.

Please also encourage your co-authors to sign up for their own ORCID account and associate it with their account on our manuscript submission system. For further information see: https://www.rsc.org/journals-books-databases/journal-authors-reviewers/processes-policies/#attribution-id

Environmental Science: Atmospheres strongly encourages authors of research articles to include an ‘Author contributions’ section in their manuscript, for publication in the final article. This should appear immediately above the ‘Conflict of interest’ and ‘Acknowledgement’ sections. I strongly recommend you use CRediT (the Contributor Roles Taxonomy from CASRAI, https://casrai.org/credit/) for standardised contribution descriptions. All authors should have agreed to their individual contributions ahead of submission and these should accurately reflect contributions to the work. Please refer to our general author guidelines http://www.rsc.org/journals-books-databases/journal-authors-reviewers/author-responsibilities/ for more information.

I look forward to receiving your revised manuscript.

Yours sincerely,
Dr Nønne Prisle
Associate Editor, Environmental Sciences: Atmospheres

************

Reviewer 1

This study investigated the effects of meteorological conditions including relative humidity and temperature on the transmission of COVID-19. It was claimed that the weather conditions would influence the settling time and virus half-life, which would further influence the transmission.

I think the conclusions were not reliable. If we look at a larger picture, the temperature normally inversely correlates with the relative humility over a year. In winter, there are lower temperatures and higher relative humidity than those in summer. According to Figure 3, the settling time would be shorter in winter and the half-life would remain nearly the same. Then we could get the conclusion that the disease is difficult to transmit in winter, which is not the case. It is also difficult to identify consistent effects of settling time and half-life from Figure 5.

This study only utilized the outdoor weather condition, but the ambient air would rapidly dilute the virus. As a result, the transmission risk outdoors would be much lower compared with indoor risk. It is more reasonable to consider the indoor environment rather than the outdoor weather condition.

Reviewer 2

This manuscript attempts a risk analysis for aerosol transmission for SARS-CoV-2. This reviewer thinks that the contribution is useful, but could be very more so if connections are made to recent works of other groups that have also considered the same problem. The drop sizes considered appear to be different from those reported by

Small droplet aerosols in poorly ventilated spaces and SARS-CoV-2 transmission
GA Somsen, C van Rijn, S Kooij, RA Bem, D Bonn
The Lancet Respiratory Medicine 8 (7), 658-659 (2020)

who point out that it is the aerosol persistence that should be quantified. This led them to perform a risk analysis similar to the one performed in the manuscript.

Aerosol persistence in relation to possible transmission of SARS-CoV-2
S Smith, G Somsen, C van Rijn, S Kooij, L van der Hoek, R Bem, D Bonn
Physics of Fluids 32 (10) (2020)

where also the results of the Bax group (NEJM, PNAS) were shown to be well described by their droplet persistence calculation, inclusing environmental conditions. It would be easy to include rudimentary ventilation models in this (I in fact saw one member of the group presenting this). However, as the authors of the manuscript are undoubtedly aware of, these mostly assume homogeniety of the aerosols in a given space, which is of course hardly reasonable. This should be discussed. I also think that most people would use Wells-Riley to make estimates such as the ones discussed in the paper. The authors should explain why they do not.

So in sum, I think the analysis is probably OK, but if everybody does such analyses in their own corner, no consensus on the best method will be reached. In view of the hestitations of the WHO and CDC to even admit that the airborne route is an important one, I think this is what should be strived for in this community. If the authors could revise their manuscript along those lines, this would be very helpful

REVIEWER REPORT(S):
Referee: 1

Comments to the Author
This study investigated the effects of meteorological conditions including relative humidity and temperature on the transmission of COVID-19. It was claimed that the weather conditions would influence the settling time and virus half-life, which would further influence the transmission.

I think the conclusions were not reliable. If we look at a larger picture, the temperature normally inversely correlates with the relative humility over a year. In winter, there are lower temperatures and higher relative humidity than those in summer. According to Figure 3, the settling time would be shorter in winter and the half-life would remain nearly the same. Then we could get the conclusion that the disease is difficult to transmit in winter, which is not the case. It is also difficult to identify consistent effects of settling time and half-life from Figure 5.
Response: We thank the reviewer for the comments. However, not all climate types on Earth have wet winters and dry summers, which could be the cause of disagreement between the present study and the reviewer’s views. For example, in the five counties investigated in this study, two have their average monthly relatively humidity relatively constant throughout the year:
https://weather-and-climate.com/average-monthly-Humidity-perc,houston,United-States-of-America
https://weather-and-climate.com/average-monthly-Humidity-perc,san-jose-california-us,United-States-of-America
and one has its average monthly relative humidity higher in the summer than winter:
https://weather-and-climate.com/average-monthly-Humidity-perc,Los-Angeles,United-States-of-America
As a result, the settling time can be longer in the winter. Combined with the typically longer virus half-life in the winter, viral transmission is typically more facile in the winter, as one would expect.
Figure 5 may be perplexing to interpret at first, but upon closer examination, Harris, King and Maricopa Counties show faster transmission with a longer virus half-life, while LA County had increased transmission rates at longer settling times. The different trends between LA County vs Harris, King and Maricopa Counties may be a result of their different policies and human behaviours not captured by the input variables in this work. This explanation was modified in the manuscript for better clarity as below:
Page 13, Line 276-277: “The different trends between LA county vs. Harris, King and Maricopa counties may be a result of their different policies and human behaviours not captured by the input variables in this work.”

This study only utilized the outdoor weather condition, but the ambient air would rapidly dilute the virus. As a result, the transmission risk outdoors would be much lower compared with indoor risk. It is more reasonable to consider the indoor environment rather than the outdoor weather condition.

Response: Although the models in this work use the outdoor weather input variables and transmission can occur indoors, the outdoor temperature usually positively correlates with the indoor environment. The correlation coefficient (slope of linear regression), however, depends on the season and location. For example, Massachusetts has Toutdoor ~ 0.04Tindoor at T < ~10℃, and Toutdoor ~ 0.41Tindoor at T > ~10℃ [1]. South Korea has Toutdoor ~ 0.13Tindoor at T < ~15℃, and Toutdoor ~ 0.47Tindoor at T > ~15℃ [2]. The indoor absolute humidity also tracks the outdoor humidity across seasons and diverse locations [3]. As a result, the outdoor transmission risk predicted in this work tracks can be used as a surrogate for the indoor transmission risk. This paragraph is modified in the manuscript to improve clarity as following:
Page 16, Line 336-343: “Although the models in this work use the outdoor weather input variables and transmission can occur indoors, the outdoor temperature correlates positively with the indoor environment52, 53. The correlation coefficient (slope of linear regression), however, depends on the season and location. For example, Massachusetts has Toutdoor ~ 0.04Tindoor at T < ~10℃, and Toutdoor ~ 0.41Tindoor at T > ~10℃.54 South Korea has Toutdoor ~ 0.13Tindoor at T < ~15℃, and Toutdoor ~ 0.47Tindoor at T > ~15℃.55 The indoor absolute humidity also tracks the outdoor humidity across seasons and diverse locations.53 As a result, the outdoor transmission risk predicted in this work tracks with, and can be used as a surrogate for the indoor transmission risk.”
[1] J. L. Nguyen, J. Schwartz and D. W. Dockery. The relationship between indoor and outdoor temperature, apparent temperature, relative humidity, and absolute humidity, Indoor Air, 2014, 24, 103-112.
[2] K. Lee and D. Lee, The Relationship Between Indoor and Outdoor Temperature in Two Types Of Residence, Energy Procedia, 2015, 78, 2851-2856.
[3] J. L. Nguyen and D. W. Dockery, Daily indoor-to-outdoor temperature and humidity relationships: a sample across seasons and diverse climatic regions, Int J Biometeorol, 2016, 60, 221-229.

Referee: 2

Comments to the Author
This manuscript attempts a risk analysis for aerosol transmission for SARS-CoV-2. This reviewer thinks that the contribution is useful, but could be very more so if connections are made to recent works of other groups that have also considered the same problem. The drop sizes considered appear to be different from those reported by

Small droplet aerosols in poorly ventilated spaces and SARS-CoV-2 transmission
GA Somsen, C van Rijn, S Kooij, RA Bem, D Bonn
The Lancet Respiratory Medicine 8 (7), 658-659 (2020)

who point out that it is the aerosol persistence that should be quantified. This led them to perform a risk analysis similar to the one performed in the manuscript.

Aerosol persistence in relation to possible transmission of SARS-CoV-2
S Smith, G Somsen, C van Rijn, S Kooij, L van der Hoek, R Bem, D Bonn
Physics of Fluids 32 (10) (2020)

where also the results of the Bax group (NEJM, PNAS) were shown to be well described by their droplet persistence calculation, inclusing environmental conditions. It would be easy to include rudimentary ventilation models in this (I in fact saw one member of the group presenting this). However, as the authors of the manuscript are undoubtedly aware of, these mostly assume homogeniety of the aerosols in a given space, which is of course hardly reasonable. This should be discussed. I also think that most people would use Wells-Riley to make estimates such as the ones discussed in the paper. The authors should explain why they do not.

So in sum, I think the analysis is probably OK, but if everybody does such analyses in their own corner, no consensus on the best method will be reached. In view of the hestitations of the WHO and CDC to even admit that the airborne route is an important one, I think this is what should be strived for in this community. If the authors could revise their manuscript along those lines, this would be very helpful

Response: We thank the reviewer for the comments. The droplet size of 6 um referenced in this work is the mode of measured speech-generated droplets, which is different from the measured cough-generated droplets of 5 um by Smith et al. Here we use the size representing the speech-generated droplets to take into account the asymptomatic transmission of SARS-CoV-2 which is at its most contagious prior to symptom onset. The following text is modified in the manuscript to make this connection:
Page 10, Line 189-195: “In order to investigate the gravity settling of the speech-generated droplets, the settling velocity and dimensionless numbers of the Stokes-Cunningham modification were estimated for droplets of 6 μm size (Figure S1), which is used as the peak initial size of speech-generated droplets36. It can be noted that this is very similar to the average diameter of cough-generated droplet size of 5 μm. This work uses the size representing the speech-generated droplets considering asymptomatic transmission of SARS-CoV-237 which is at its most contagious before symptom onset38.”
Smith et al., Stadnytskyi et al., and Anfinrud et al. are referenced and compared with this work. The assumption of homogeneity as well as risk assessment models such as Wels-Riley are discussed in the following added text:
Page 15, Line 304-321: “Other works have analysed the link between virus-laden aerosol settling and SARS-CoV-2 transmission from different perspectives. Smith et al provided a useful model for that assesses aerosol transmission of SARS-CoV-2 through respiratory droplet physics. The study calculated the number of virus particles inhaled via indirect airborne transmission by calculating the persistence (settling time) of cough-generated aerosols, and concluded that aerosol transmission is a possible but not efficient route of transmission of SARS-CoV-2. This conclusion as well as evidence suggested by Stadnytskyi et al and Anfinrud et al agree with the conclusion of the present work to the extent that indirect airborne transmission is a possible route of transmission of SARS-CoV-2. WHO in the most recent update (Apr 30, 2021) has also acknowledged aerosol transmission as one of the major routes of transmission for SARS-CoV-2. Homogeneity of the aerosols in the space studied is often assumed in these approaches to translate aerosol persistence to aerosol inhaled, which can be far from reality. One advantage of this work is that by predicting transmission from aerosol persistence (and virus viability) via data analysis tools, homogeneity is not assumed. Because the infection risk assessment is embedded in the data analysis step connecting aerosol persistent and transmission, mathematical infection risk assessment models such as Wells-Riley and dose-response are also not required in this work. This approach reduces uncertainties introduced into the model as the infection threshold of SARS-CoV-2 is still unclear.”

19-Oct-2021

Dear Dr Hoffmann:

Manuscript ID: EA-ART-02-2021-000013.R1
TITLE: Speech-generated Aerosol Settling Times and Viral Viability Predict COVID-19 Transmission Efficiency

Thank you for your submission to Environmental Science: Atmospheres, published by the Royal Society of Chemistry. I sent your manuscript to reviewers and I have now received their reports which are copied below.

I have carefully evaluated your manuscript and the reviewers’ reports, and the reports indicate that major revisions are necessary. I recognize that it has been challenging to find available reviewers for your manuscript and therefore hope that the requested revision will present a chance to both address the reviewer's comments and also update the recent literature, which naturally in this particular topic is changing day-by-day.

Please submit a revised manuscript which addresses all of the reviewers’ comments. Further peer review of your revised manuscript may be needed. When you submit your revised manuscript please include a point by point response to the reviewers’ comments and highlight the changes you have made. Full details of the files you need to submit are listed at the end of this email.

Please submit your revised manuscript as soon as possible using this link:

*** PLEASE NOTE: This is a two-step process. After clicking on the link, you will be directed to a webpage to confirm. ***

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(This link goes straight to your account, without the need to log on to the system. For your account security you should not share this link with others.)

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You should submit your revised manuscript as soon as possible; please note you will receive a series of automatic reminders. If your revisions will take a significant length of time, please contact me. If I do not hear from you, I may withdraw your manuscript from consideration and you will have to resubmit. Any resubmission will receive a new submission date.

The Royal Society of Chemistry requires all submitting authors to provide their ORCID iD when they submit a revised manuscript. This is quick and easy to do as part of the revised manuscript submission process. We will publish this information with the article, and you may choose to have your ORCID record updated automatically with details of the publication.

Please also encourage your co-authors to sign up for their own ORCID account and associate it with their account on our manuscript submission system. For further information see: https://www.rsc.org/journals-books-databases/journal-authors-reviewers/processes-policies/#attribution-id

Environmental Science: Atmospheres strongly encourages authors of research articles to include an ‘Author contributions’ section in their manuscript, for publication in the final article. This should appear immediately above the ‘Conflict of interest’ and ‘Acknowledgement’ sections. I strongly recommend you use CRediT (the Contributor Roles Taxonomy from CASRAI, https://casrai.org/credit/) for standardised contribution descriptions. All authors should have agreed to their individual contributions ahead of submission and these should accurately reflect contributions to the work. Please refer to our general author guidelines http://www.rsc.org/journals-books-databases/journal-authors-reviewers/author-responsibilities/ for more information.

I look forward to receiving your revised manuscript.

Yours sincerely,
Dr Nønne Prisle
Associate Editor, Environmental Sciences: Atmospheres

************

Reviewer 3

I was asked to referee this paper which apparently has already been refereed once. The issue of airborne transmission has, of course, been discussed many times, from many perspectives, though reading this paper one might not know that, e.g., see publications by Milton, Morawska, Bazant and Bush, etc. and many others. Also, I fail to see how some of the major claims in the paper can be supported, e.g. on p. 18 we read “To the best of our knowledge, the present work is the first to use weather-derived, transmission-mechanisms-based input variables that include aerosol settling times and virus viability to predict transmission. Predictive power of the models presented is more conclusive in determining the role of weather in transmission”. In addition, other important variables are neglected as there is no discussion of indoors versus outdoors, the data is only from April 2020 when all indicators are that case rates were likely underreported, as for example, as the authors recognize, asymptomatic spread means that case numbers were necessarily underreported, etc. The use of the slip correction for small particles seems useful (but see my remark 4 below) though I wish there were more recent data to support its use since 100 year old references to experimental data for this problem do not give me so much confidence. The journal may wish to publish the paper since some may extract something useful, but given the vagueness of the approach in my view, and the variables excluded, and the very large literature on related themes that are nowhere recognized or cited, I fail to see how this approach is helpful for “the predictions” the authors claim (nor do I see how there is evidence supporting the claim of a predictive result/approach in this paper).
Other remarks:
1) Abstract: “Our results confirm that airborne aerosol transmission is an important pathway for the spread of SARS-CoV-2.” – Well that may be true but this has been stated many times in the open literature so the authors could acknowledge that. They are not concluding anything new. There are articles with the same statements already in mid-2020 (if not earlier), though the US health authorities and the public were slow to respond.
2) Abstract: “Furthermore, the infection spreading rates can be predicted using historical weather data.” I fail to see evidence for this in this paper.
3) p. 3: “Facile flu transmission” – facile? Surely this is not the proper descriptor.
4) p. 4: “Because it assumes no-slip boundary condition, it underestimates the terminal settling velocity for small particles of size < 1 μm.” This sentence is surely wrong. The mean free path in air at atmospheric pressure and room temperature is 70 nm or thereabouts; the correction for slip for a particle 200 nm (a little bigger than the virus) will only be a little bigger than Stokes law, which is used for a huge array of problems involving Brownian particles. Although there may be some authors that wish it not to be true, it is remarkably robust, even down to length scales below which the author describe. Furthermore, there is no consideration given to the effects of natural turbulence in the air and Brownian motion, which would mean that particles tend to remain in the air longer than predictions based only on sedimentation.

I have a difficult time drawing any conclusions from this paper since there are so many variables, possibly very important, that are nowhere in their models. Also, there have been detailed studies of the air flows in speech, including trying to address issues of humidity (unlike the simple model in this paper) since the exhaled air is typically humid, e.g., Extended Lifetime of Respiratory Droplets in a Turbulent Vapor Puff and Its Implications on Airborne Disease Transmission, by Chong et al., Phys. Rev. Lett. 126, 034502 (published Jan 2021). There are several papers of this type in the literature and others estimating drop shrinkage due to humidity while accounting for salt concentration etc., e.g. R. Netz (I think in PNAS).
p. 18: “Airborne speech-generated aerosol transmission is a significant transmission route of SARS-CoV-2 and its transmission rate can be predicted using aerosol settling time and viral viability from historical weather data.” This statement is surely an overstatement.
Also, we then read: “For future efforts on effectively slowing down the transmission, these findings support implementation of control measures including social distancing, enforcing mask wearing, and systematic preventive measures such as improved ventilation in both community and healthcare settings.” Surely, the authors can indicate that all of these ideas have been written about many times, in research papers and the public press, and many institutions had already implemented these ideas by fall 2020, at least in some parts of the US.
Minor:
a) p. 4: “In a study focused of ON the viability of SARS-CoV-2 on surfaces confirms,” – the authors miss an important point which that I believe already a few months after the virus was identified there were reports that the property of the surface (metal, paper, cardboard, etc.) mattered.
b) Figure 2 caption: “The Reynold’s number” -> his name was Reynolds

Disclaimer: This text has been copied from the PDF response to reviewers and does not include any figures, images or special characters.

REVIEWER REPORT(S):
Referee: 3

Comments to the Author
I was asked to referee this paper which apparently has already been refereed once. The issue of airborne transmission has, of course, been discussed many times, from many perspectives, though reading this paper one might not know that, e.g., see publications by Milton, Morawska, Bazant and Bush, etc. and many others.
We thank the reviewer for the recommendation. Milton, Bazant and Bush references are added in the text. Aerosol size distribution measurement by Morawska was a basis of this work and was extensively referenced in the methods and results sections.
Also, I fail to see how some of the major claims in the paper can be supported, e.g. on p. 18 we read “To the best of our knowledge, the present work is the first to use weather-derived, transmission-mechanisms-based input variables that include aerosol settling times and virus viability to predict transmission. Predictive power of the models presented is more conclusive in determining the role of weather in transmission”.
The statement on the model’s predictive power has been modified to reflect the scope of our study more accurately, which is to investigate the value of incorporating the weather-related aerosol property variables into transmission modeling, instead of producing a most accurate COVID transmission model. The revision is listed below.
On p. 18 lines 383-389, this section of the paragraph is modified to: “Overall, the evidence on weather influence of transmission has been contradictory and inconclusive. We note that the present work does not aim to prove that aerosol settling time and virus viability are exclusively important on predicting transmission rate. The fitting and prediction performance of the models presented suggests that weather plays a considerable role in transmission. Thus, the incorporation of weather-derived, transmission-mechanisms-based input variables, including aerosol settling times and virus viability, into epidemiological prediction model may worth further investigation.”
In addition, other important variables are neglected as there is no discussion of indoors versus outdoors, the data is only from April 2020 when all indicators are that case rates were likely underreported, as for example, as the authors recognize, asymptomatic spread means that case numbers were necessarily underreported, etc.
In the most recent version, indoors vs outdoors is discussed on p. 16 lines 349-356:” Although the models in this work use the outdoor weather input variables and transmission can occur indoors, the outdoor temperature correlates positively with the indoor environment59, 60. The correlation coefficient (slope of linear regression), however, depends on the season and location. For example, Massachusetts has Toutdoor ~ 0.04Tindoor at T < ~10℃, and Toutdoor ~ 0.41Tindoor at T > ~10℃.61 South Korea has Toutdoor ~ 0.13Tindoor at T < ~15℃, and Toutdoor ~ 0.47Tindoor at T > ~15℃.62 The indoor absolute humidity also tracks the outdoor humidity across seasons and diverse locations.60 As a result, the outdoor transmission risk predicted in this work tracks with, and can be used as a surrogate for the indoor transmission risk.”
The authors recognize that a limited number of variables are included in this model, and variables not included as model input likely contributed considerably to the fitting residual. However, the scope of the present work is not to predict transmission as accurately as possible, but to 1) investigate the significance of weather on COVID-19 transmission, and 2) deduce the role of airborne transmission via aerosols. This work intends to inspire future transmission modelling work to include weather as input variables, and substantiate the suspended aerosol route as a primary route of transmission.
Although case rates were likely underreported in 2020 when the data for this work were obtained, spanning this analysis for longer time would introduce additional variables such as the level of underreporting and vaccination. In the limited timespan of this study, the health policy in the US was largely unchanged hence minimizes the model fitting residual.
The use of the slip correction for small particles seems useful (but see my remark 4 below) though I wish there were more recent data to support its use since 100 year old references to experimental data for this problem do not give me so much confidence.
The authors recognize that the empirical constant has been measured 100 years ago. However, unlike biology and epidemiology where published postulates can often be disproved in 50 years, fluid mechanical constants often remain relatively unchanged over 100 years. The empirical constant of 2.52 in the Cunningham correction equation has been invoked in recent publications (Cetin et al 2020 and Shimasaki et al 2021). The invocation of the Knudsen number is based on first principle. More detailed response can be found in the response to the reviewer’s comment #4.
Cetin, Yunus Emre, Mete Avci, and Orhan Aydin. "Effect of air change rate on particle dispersion from inlet opening under varying particle source strengths." International Journal of Ventilation (2020): 1-18.
Shimasaki, Noriko, and Hideaki Morikawa. "Prevention of COVID-19 Infection with Personal Protective Equipment." Journal of Disaster Research 16, no. 1 (2021): 61-69.
The journal may wish to publish the paper since some may extract something useful, but given the vagueness of the approach in my view, and the variables excluded, and the very large literature on related themes that are nowhere recognized or cited, I fail to see how this approach is helpful for “the predictions” the authors claim (nor do I see how there is evidence supporting the claim of a predictive result/approach in this paper).
In this revised manuscript, we have incorporated more references on related topics, as discussed in detail in the following responses. Regarding the reviewer’s concern on the choice of variables, we revised the framing of the goal and made clarifications on the scope of our study. The relevant revisions are listed below.
On p.2 lines 33-36, the concluding sentences in abstract are edited to: “Corroborating with previous health science studies, from the perspective of meteorology-modulated transmission, our results strengthen that airborne aerosol transmission is an important pathway for the spread of SARS-CoV-2. Furthermore, historical weather data can improve the prediction accuracy of infection spreading rates.”
On p.5 lines 100-103, the ending of the introduction is edited to: “A good model fitting and prediction performance would indicate that speech-generated airborne aerosols are a significant transmission route for COVID-19 and that the weather-affected speech-generated aerosol properties may be incorporated to assist further predictive model development.”
On p. 18 lines 387-389, the conclusion is edited to: “Thus, the incorporation of weather-derived, transmission-mechanisms-based input variables, including aerosol settling times and virus viability, into epidemiological prediction model may worth further investigation.”

Other remarks:
1) Abstract: “Our results confirm that airborne aerosol transmission is an important pathway for the spread of SARS-CoV-2.” – Well that may be true but this has been stated many times in the open literature so the authors could acknowledge that. They are not concluding anything new. There are articles with the same statements already in mid-2020 (if not earlier), though the US health authorities and the public were slow to respond.
In addition to literature cited in the introduction section, the sentence in the abstract is edited to acknowledge previous efforts by the scientific community on p. 2 lines 33-36: “Corroborating with previous health science studies, from the perspective of meteorology-modulated transmission, our results strengthen that airborne aerosol transmission is an important pathway for the spread of SARS-CoV-2.”
2) Abstract: “Furthermore, the infection spreading rates can be predicted using historical weather data.” I fail to see evidence for this in this paper.
The two text quotes below showcase that weather-derived settling time and viral viability can predict transmission within one sigma prediction interval. In addition, this sentence is modified in the abstract to: “Furthermore, historical weather data can improve the prediction accuracy of infection spreading rates.”
On page 12 lines 248-250 for figure 4:” The model fittings follow the major trends of the actual data and capture most of their peaks and troughs; the actual data of the last 4 days also fall inside the one-sigma prediction intervals despite simplicity of the models used.”
On page 14 lines 299-300 for figure 6:” The observed increase in new cases line falls within the one-sigma prediction interval for the last 21 days of available data.”

3) p. 3: “Facile flu transmission” – facile? Surely this is not the proper descriptor.
The word ‘facile’ throughout the manuscript is changed to improve clarity. Lines 44-46 on p. 3 are edited to: “Faster flu transmission during winter months is often linked to lower temperatures and relative humidity than occur during the summer”
4) p. 4: “Because it assumes no-slip boundary condition, it underestimates the terminal settling velocity for small particles of size < 1 μm.” This sentence is surely wrong. The mean free path in air at atmospheric pressure and room temperature is 70 nm or thereabouts; the correction for slip for a particle 200 nm (a little bigger than the virus) will only be a little bigger than Stokes law, which is used for a huge array of problems involving Brownian particles. Although there may be some authors that wish it not to be true, it is remarkably robust, even down to length scales below which the author describe. Furthermore, there is no consideration given to the effects of natural turbulence in the air and Brownian motion, which would mean that particles tend to remain in the air longer than predictions based only on sedimentation.
The authors recognize the robustness of Stokes drag calculation in the context of atmospheric particle settling, though math indicates that an error of 25%-120% exists if the Cunningham slip correction factor is not considered for some particle sizes relevant in this paper.
Equation (6) calculates the mean free path of air at 298K is 95nm. The Cunningham slip correction factor calculated through equations (4) through (6) for particle with a diameter of 200nm in air is 2.2 i.e. the terminal settling velocity of the particle is 2.2 times faster than calculated from uncorrected Stokes law. For particle diameter of 1µm, the correction factor is 1.24. These examples are added in the manuscript text on p. 4 lines 66-68:” In air at 25 °C, the terminal velocity accounting for slip correction is 1.24 times faster than calculated from uncorrected Stokes’ Law for a 1 μm-diameter particle, and 2.2 times faster for a 200 nm-diameter particle.” The difference of this slip correction may be significant in some applications and insignificant in others. In this study, including the slip correction improves the model accuracy.

I have a difficult time drawing any conclusions from this paper since there are so many variables, possibly very important, that are nowhere in their models. Also, there have been detailed studies of the air flows in speech, including trying to address issues of humidity (unlike the simple model in this paper) since the exhaled air is typically humid, e.g., Extended Lifetime of Respiratory Droplets in a Turbulent Vapor Puff and Its Implications on Airborne Disease Transmission, by Chong et al., Phys. Rev. Lett. 126, 034502 (published Jan 2021). There are several papers of this type in the literature and others estimating drop shrinkage due to humidity while accounting for salt concentration etc., e.g. R. Netz (I think in PNAS).
We thank the reviewer for the recommendation. The purpose of this work is actually not to make the most accurate transmission predictions by including as many input variables as feasible, but to demonstrate the predictive power of weather input variables, urge future work to include those input variables, and confirm the indirect airborne transmission as a significant route of transmission for SARS-CoV-2. Per the reviewer’s comment, Chong et al and Netz et al are referenced in appropriate sections of the manuscript. It may be of interest to note that this work also accounts for the salt concentrations in speech-generated aerosols, their effect on surface tension and equilibrium aerosol size after evaporation.
p. 11 lines 229-230: “The evaporation and settling calculations agree with the classic Wells model.”
p. 18 lines 389-392: “Future work in model development should also include additional variables that play a role in airborne or surface-based transmission such as wind speeds, turbulence (especially those created by speech which can lengthen the suspension time by 30-150 times63), and UVB intensity.”

p. 18: “Airborne speech-generated aerosol transmission is a significant transmission route of SARS-CoV-2 and its transmission rate can be predicted using aerosol settling time and viral viability from historical weather data.” This statement is surely an overstatement.
In response to the reviewer’s concern on overstatement of the model’s predictive power, the statements about predictive power have been toned down and the relevant revisions are listed below.
The sentences on p. 18 lines 376-379 are edited to: “Airborne speech-generated aerosol transmission is a significant transmission route of SARS-CoV-2. Including aerosol settling time and viral viability from historical weather data as input variables can improve the accuracy of transmission rate prediction.”
The sentence in lines 35-36 in the abstract is edited to: “Furthermore, historical weather data can improve the prediction accuracy of infection spreading rates.”
Also, we then read: “For future efforts on effectively slowing down the transmission, these findings support implementation of control measures including social distancing, enforcing mask wearing, and systematic preventive measures such as improved ventilation in both community and healthcare settings.” Surely, the authors can indicate that all of these ideas have been written about many times, in research papers and the public press, and many institutions had already implemented these ideas by fall 2020, at least in some parts of the US.
The corresponding sentences on p. 18 lines 379-382 are edited to: “Corroborating with publications and public actions over the past year, the findings of this study support implementation of control measures including social distancing, enforcing mask wearing, and systematic preventive measures such as improved ventilation in both community and healthcare settings.”


Minor:
a) p. 4: “In a study focused of ON the viability of SARS-CoV-2 on surfaces confirms,” – the authors miss an important point which that I believe already a few months after the virus was identified there were reports that the property of the surface (metal, paper, cardboard, etc.) mattered.
The information has been incorporated per the reviewer’s comment. Indeed the surface material affects SARS-CoV-2 viability, however since this work focuses on suspended aerosols, deposited aerosols are not discussed in further detail to avoid confusion.
This sentence on p. 4 lines 79-81 is edited to: ” In a study focused on the viability of SARS-CoV-2 on surfaces, investigators reported an extension of viability over longer times at low temperatures and humidities.22, 23 ”
Reference for surface material affecting SARS-CoV-2 viability: https://doi.org/10.1016/j.cocis.2021.101481


b) Figure 2 caption: “The Reynold’s number” -> his name was Reynolds
The typo in line 406 was corrected to ‘Reynolds number’


Best regards,
Alan Gu
PhD Candidate, California Institute of Technology

25-Nov-2021

Dear Dr Hoffmann:

Manuscript ID: EA-ART-02-2021-000013.R2
TITLE: Speech-generated Aerosol Settling Times and Viral Viability Can Improve COVID-19 Transmission Prediction

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Reviewer 4

The authors provide an interesting study of correlations between the effects of temperature and relative humidity on aerosol settling times and viral viability with COVID transmission. The results are interesting and provide additional data for the community to consider as it works to develop ever more effective models for COVID transmission. The authors have responded carefully and substantively to each of the prior reviewers comments, including toning down their statements of research priority and significance. Furthermore, the manuscript is clearly written. Thus, I recommend that it be accepted for publication.