Factors Affecting COVID-19 Outbreaks across the Globe: Role of Extreme Climate Change

Round 1

Reviewer 1 Report

Nath et al. selected 48 cities across 4 continents as COVID-19 (C19) epicenters and introduced a combined temperature-humidity profile to study the importance of environmental conditions in the spread of C19 pandemic. They concluded that “a tighter association of C19 pandemic with extreme hot climate.”

 

I believe the idea of this paper for combining the meteorological factors (temperature and humidity) to better describe the epidemic trend than when a single variable was analyzed is attractive enough for the community. It has been really interesting and essential if scientists can introduce the best fitted predictive model of the climatic conditions on transmission and the seasonal behavior of the virus. The subject of the paper is therefore within the “Sustainability” remit, and the manuscript is well written. However, I have some comments on the technical aspects and interpretations.

General comments:

I think the study presented a considerable risk of bias in the global warming impact on the spread of C19 pandemic;

• Authors simply and in a really sharp manner concluded that “the COVID-19 is an outcome of anthropogenic climate change due to greenhouse gas emission.” There are lots of recent studies showed that meteorological factors alone do not explain most of the variability of the COVID-19 outbreak (Mecenas et al., 2020 and references therein), however, they might facilitate the virus transmission. Public isolation policies, herd immunity, migration patterns, containment measures, population density, and cultural aspects directly influence how the spread of this disease occurs. According to Oliveiros et al. (2020), temperature and humidity contribute to a maximum of 18% of the variation, the remaining 82% being related to other factors. Thus, weather conditions in combination with social factors can play a role in coronavirus outbreaks, since this public health problem is too complex to be explained solely in relation of climatic conditions. Authors tried to touch the importance of only a couple of other criteria such as population distribution and international travel routes, unfortunately, in a very basic level, with an inappropriate presentation and insufficient interpretation.

 

• By screening 517 articles and reviewing 17 studies, Mecenas et al. (2020) observed a homogeneity in the findings regarding the effect of temperature and humidity on transmissibility of C19. They concluded that “warmer climate is less likely to spread the virus”, “wetter climate inhibits the virus spread” and “cold and dry conditions were potentiating factors on the spread of the virus”. How author explain this remarkable contradictory between the findings in the literatures with their own results?

 

• Authors claimed that the emission levels of CO2 are higher in the severe, high and medium C19 affected centers, and suggested a linkage between the two. Although the selected countries have been emitting large amount of GHGs to the atmosphere for years and coincidently they experienced the larger number of C19 cases in the first 3 months of the pandemic, it is very hard to simply and explicitly conclude that the local higher temperature caused by the local emitted CO2 in certain areas and directly linked to the C19 cases. Cumulative increase of the long lifetime species such as CO2 during these years has a global adverse impact on climate that could not be limited to the specific region of the emission sources. The explanations and arguments that were used to justify the CO2 emission effect are not correct. unless the authors quantitatively prove that it is the case through thorough analysis of the chain-of-event processes.

 

Therefore, the authors need to rephrase their manuscripts with much more careful analysis and presentation to achieve convincible results. Furthermore, the selected period in data analysis included less than four months which were only the winter months toward the summer in Northern Hemisphere. The selected period is also when almost none of the selected countries met even the first peak of the disease transmission. We have been witnessed of the variability in disease transmission during the whole year of 2020. Considering additional data for the rest of the year, I have serious doubts about reliability of most of the results and conclusions from this experiment.

 

Minor comments:

Page 1, line 15 (abstract) and Page 2, line 85; since it will be published in this year specify the year of study, add “2020”.

  

Page 3, line 88: Do you mean severity of illness? What is the point of showing the severity? Are you investigating the weather conditions impacts on severity of illness as well as the spread of the virus? Clarify if you study the effect of temperature and humidity on the rate of quantitative and qualitative progression of the pandemic?

 

Page 3, Table 1: Add a column to represent cumulative C19 counts by the period of the study.

 

Page 3, Table 1:

1. Be careful, you mentioned the name of states for the US. not cities.
2. Clarify what you mean by the distance from waterbody for the states. Do you mean the distance from waterbody of the capitals of the states?
3. How important were them in your analysis? explain it. If you meant showing the distance as a criterion for determining the relative humidity you should be careful about topography of the region as well. For instance, in California, where expands along the ocean, towns inside the land sometimes experience huge different relative humidity than coastal towns at a short distance.

 

Page 4, line 102:

Your analysis show though population in the African continent were dense the countries are not recognized as the COVID-19 epicenters and detected the lower number of C19 cases. Explain it why. Could it be due to less mass testing? As many of the underdeveloped countries that presents deficiency in the health care system and may have not done enough testing to detect the actual spread of this virus (Bukhari et al., 2020).

 

Page 5, Figure 2: be more organized with subfigures, name them in order (a, b, and c) as you discussed them in the text. You may want to move figure 2c on the right-hand side of figure 2a.

 

Page 5, line 147: clarify “current period” by clearly mentioning the study period (Jan 1 – April 25, 2020) and clarify that the historical period is also for the same period in these years?

Page 6, line 183: Add the figure legends for right columns of the Supplementary Figures 4-8.

Page 6, line 185: you mentioned that “daily COVID-19 counts vary quasi-linearly with T and RH, but in the opposite direction.” But it is very hard to even visually recognize the claimed strong correlations as you discussed and plotted them separately. Plot time series or scatter plots of daily C19 counts, T and RH in a single plot for each epicenter to better represent and help readers to clearly see the correlations? As authors did for their similar study by Sasikumar et al. (2020).

Page 7, line 207: replace “It addition” with “In addition”.

Page 8, line 245: replace “ Figure 3b” with “ Figure 2b”.

Page 8, line 263: in Supplementary information 1, that you mentioned, one paragraph is written twice.

Page 8, line 274-276: rephrase the sentence. It is not clear.

Page 8, line 278-280 and page 10, line 302-303: rephrase them that sharp and not-proved claim!

Page 9, Figure 4:

1) add the number of C19 counts for the regions on the figure where you represented the possible factors that might play role in the virous spread.

2) what did the different size of circles show in the figure? Explain it.

3) Color for high and low temperatures are difficult to distinguish. Change the color.

 

Page 9, line 288: mention the specific period.

 

Page 10, line 299-300: What is the point of this comparison? Did you expect the C19 counts peak at the mean temperature of 16 countries?

 

References:

Mecenas P., da Rosa Moreira Bastos R.T., Rosario Vallinoto A.C., Normando D., Effects of temperature and humidity on the spread of COVID-19: A systematic review. (2020)  PLoS ONE,  15  (9 September) , art. no. e0238339

 

Oliveiros B, Caramelo L, Ferreira NC, Caramelo F.: Role of temperature and humidity in the modulation of the doubling time of COVID-19 cases. (2020). Available from: https://www.medrxiv.org/content/10.1101/2020.03.05.20031872v1.

 

Bukhari Q, Jameel Y. Will coronavirus pandemic diminish by summer? (2020).Available from: https://ssrn.com/abstract=3558757 https://doi.org/10.2139/ssrn.3556998

 

 

Author Response

Reply to the Comments

First of all we are thankful to the reviewer for reviewing our manuscript and providing valuable comments and suggestions. Below are the point by point replies to the comments and changes made in the revised manuscript are shown in red font.

Nath et al. selected 48 cities across 4 continents as COVID-19 (C19) epicenters and introduced a combined temperature-humidity profile to study the importance of environmental conditions in the spread of C19 pandemic. They concluded that “a tighter association of C19 pandemic with extreme hot climate.”

 I believe the idea of this paper for combining the meteorological factors (temperature and humidity) to better describe the epidemic trend than when a single variable was analyzed is attractive enough for the community. It has been really interesting and essential if scientists can introduce the best fitted predictive model of the climatic conditions on transmission and the seasonal behavior of the virus. The subject of the paper is therefore within the “Sustainability” remit, and the manuscript is well written. However, I have some comments on the technical aspects and interpretations.

General comments:

I think the study presented a considerable risk of bias in the global warming impact on the spread of C19 pandemic;

Comment 1: Authors simply and in a really sharp manner concluded that “the COVID-19 is an outcome of anthropogenic climate change due to greenhouse gas emission.” There are lots of recent studies showed that meteorological factors alone do not explain most of the variability of the COVID-19 outbreak (Mecenas et al., 2020 and references therein), however, they might facilitate the virus transmission. Public isolation policies, herd immunity, migration patterns, containment measures, population density, and cultural aspects directly influence how the spread of this disease occurs. According to Oliveiros et al. (2020), temperature and humidity contribute to a maximum of 18% of the variation, the remaining 82% being related to other factors. Thus, weather conditions in combination with social factors can play a role in coronavirus outbreaks, since this public health problem is too complex to be explained solely in relation of climatic conditions. Authors tried to touch the importance of only a couple of other criteria such as population distribution and international travel routes, unfortunately, in a very basic level, with an inappropriate presentation and insufficient interpretation.

 Reply: Thanks for the suggestions. We agreed with reviewer’s comments and have discussed and referred the above references in the revised version. Line 77-87.

We have chosen the time period of the analysis from 01^st Jan-25^th Apr, 2020, at the initial phase of the outbreak i.e. prior to the community transmission phase. During this phase the spread depends more on the background environmental conditions. Sasikumar et al., (2020) has selected 20 densely populated cities of India as COVID-19 hotspots and reported a strong covariability with local temperature at the initial phase of the outbreak. They showed that local temperature accounts approximately 65–85% of the explained variance; i.e., the spread of COVID-19 depends strongly on local temperature rise prior to the community transmission phase.

Comment 2: By screening 517 articles and reviewing 17 studies, Mecenas et al. (2020) observed a homogeneity in the findings regarding the effect of temperature and humidity on transmissibility of C19. They concluded that “warmer climate is less likely to spread the virus”, “wetter climate inhibits the virus spread” and “cold and dry conditions were potentiating factors on the spread of the virus”. How author explain this remarkable contradictory between the findings in the literatures with their own results?

Reply: We discussed these points in Line 247-259. These results are partly contradictory to the previous findings as suggested by the reviewer, which is probably due to higher capability of SARS-Cov-2 to adapt in diverse environmental conditions. Secondly, we observe that the increase in COVID-19 counts depend more on the environmental conditions at the initial stage of the outbreaks i.e. prior to the community transmission phase.

In the current study, we observe that the epicenters are mostly clustered at temperatures within 0^o-10^o C, however at the later stage, COVID-19 counts are higher in the warmer (South Africa, Brazil, and India; Sasikumar et al., 2020²¹) and colder (Russia, Canada) countries, as well.

Comment 3: Authors claimed that the emission levels of CO2 are higher in the severe, high and medium C19 affected centers, and suggested a linkage between the two. Although the selected countries have been emitting large amount of GHGs to the atmosphere for years and coincidently they experienced the larger number of C19 cases in the first 3 months of the pandemic, it is very hard to simply and explicitly conclude that the local higher temperature caused by the local emitted CO2 in certain areas and directly linked to the C19 cases. Cumulative increase of the long lifetime species such as CO2 during these years has a global adverse impact on climate that could not be limited to the specific region of the emission sources. The explanations and arguments that were used to justify the CO2 emission effect are not correct. unless the authors quantitatively prove that it is the case through thorough analysis of the chain-of-event processes.

Reply: We agree with the reviewer’s comment and understand that a quantitative assessment is necessary with lot many cases and for longer timescale (Line 387-389). Moreover, such a short duration of dataset is not suitable for quantitative analysis. Here we argues qualitatively and establish a tighter association between COVID-19 outbreaks and extreme climate change, which is as follows,

Weber & Stilianakis (2008)¹⁶ and Pyankova et al. (2018)¹⁷ reported that the existence and transmission of SARS-CoV virus and Middle East Respiratory Syndrome-Coronavirus (MERS-CoV-2012) in the atmosphere depends strongly on the environmental factors e.g. temperature, humidity, solar intensity etc. Secondly, the impact of climate change on epi­demiology of zoonotic disease²² and their transmission from animal species to human^23,24 are well reported. Line 70-73.

Global warming has induced extreme weather events have strong negative impact on the biodiversity and seasonality of different vector borne diseases²⁵ (Line 89-91). It is reported that CO₂ emission due to unprecedented fossil fuel burning is the root cause of regional and global warming. An extreme hotter climate may induce excessive heat stress on the zoonotic species and it is providing a suitable environment for the viruses to adapt to the newer climate, as well. It could alter the relationship among the infectious agents, host species, and their interactions with the human's immune system (Line 374-380).

Therefore, from the above arguments it is evident that outbreaks of the infectious diseases have close association with the warming induced extreme climate change. However, a quantitative assessment is necessary with lot many cases and for longer timescale.

Comment 4: Therefore, the authors need to rephrase their manuscripts with much more careful analysis and presentation to achieve convincible results. Furthermore, the selected period in data analysis included less than four months which were only the winter months toward the summer in Northern Hemisphere. The selected period is also when almost none of the selected countries met even the first peak of the disease transmission. We have been witnessed of the variability in disease transmission during the whole year of 2020. Considering additional data for the rest of the year, I have serious doubts about reliability of most of the results and conclusions from this experiment.

Reply: We have selected the time period from 01st Jan to 25th Apr, 2020 i.e. the initial phase of the outbreaks. This is the period when almost none of the selected countries met the first peak of the disease transmission. During this period the transmission in most of the epicenters depend mainly on the background environmental conditions. E.g. over 20 cities of India, Sasikumar et al., (2020) have reported a strong covariability with local temperature at the initial phase of the outbreak. They showed that local temperature accounts approximately 65–85% of the explained variance; i.e., the spread of COVID-19 depends strongly on local temperature rise prior to the community transmission phase.  

Minor comments:

Comment 1: Page 1, line 15 (abstract) and Page 2, line 85; since it will be published in this year specify the year of study, add “2020”.

Reply: Changes made as suggested. Line 34-35.

Comment 2: Page 3, line 88: Do you mean severity of illness? What is the point of showing the severity? Are you investigating the weather conditions impacts on severity of illness as well as the spread of the virus? Clarify if you study the effect of temperature and humidity on the rate of quantitative and qualitative progression of the pandemic?

Reply: We define the severity of COVID-19 from its cumulative COVID-19 counts over the epicenters. The Figure 1 represents the distribution of COVID-19 cases globally. The regions with higher cumulative counts are extremely severe, while with less cumulative counts are less severe. The aim is to identify the regions, which are worst affected at the initial phase of the outbreak. We discussed these points in Line 102-105 and in Line 115.

Comment 3: Page 3, Table 1: Add a column to represent cumulative C19 counts by the period of the study.

Reply: Column added as suggested.

Comment 4: Page 3, Table 1:

1. Be careful, you mentioned the name of states for the US. not cities.

Reply: Corrected as suggested. Line 564.

1. Clarify what you mean by the distance from waterbody for the states. Do you mean the distance from waterbody of the capitals of the states?

Reply: Discussed in the revised manuscript, as suggested. Line 239-245.

1. How important were them in your analysis? explain it. If you meant showing the distance as a criterion for determining the relative humidity you should be careful about topography of the region as well. For instance, in California, where expands along the ocean, towns inside the land sometimes experience huge different relative humidity than coastal towns at a short distance.

Reply: Since we are aiming to investigate the environmental factors underlying the spread of COVID-19, we observe that most of the epicenters are close to the larger water bodies like sea, ocean or lakes. It indicates that relative humidity in most of the epicenters is high, which may facilitate a favorable environment for the transmission of SARS-CoV-2. Line 239-242.

 Regarding the topography, we agree with the reviewer’s comment. We discussed this point in Line 242-245.

Comment 5: Page 4, line 102:

Your analysis show though population in the African continent were dense the countries are not recognized as the COVID-19 epicenters and detected the lower number of C19 cases. Explain it why. Could it be due to less mass testing? As many of the underdeveloped countries that presents deficiency in the health care system and may have not done enough testing to detect the actual spread of this virus (Bukhari et al., 2020).

Reply: We agree with the reviewer that deficiency in the health care system and less mass testing may not detect the actual spread of the virus. We discussed this point in Line 156-158.

In addition to the above factor there is few more reasons e.g. 1) Despite higher population density, African continent had experienced less number of SARS-CoV-2 cases, which is possibly due to lesser number of airports and limited international air traffic movements (Line 153-155), 2) Secondly, emissions of the particulate matters often block the natural immune system of the hosts and make them vulnerable to the infections.  Over the African continent, CO₂ emissions are much less compare to the Asia, Europe and North America (Line 285-286).

 Comment 6: Page 5, Figure 2: be more organized with subfigures, name them in order (a, b, and c) as you discussed them in the text. You may want to move figure 2c on the right-hand side of figure 2a.

Reply: Changes made as suggested. Page 8.

Comment 7: Page 5, line 147: clarify “current period” by clearly mentioning the study period (Jan 1 – April 25, 2020) and clarify that the historical period is also for the same period in these years?

Reply: Sorry for the inconvenience. We clarified the dates in the revised version. Line 34-35, Line 124, Line 193-196, Line 319-320, Line 331-332.

Comment 8: Page 6, line 183: Add the figure legends for right columns of the Supplementary Figures 4-8.

Reply: Figure legends added in the right column of Figure 4-8.

Comment 9: Page 6, line 185: you mentioned that “daily COVID-19 counts vary quasi-linearly with T and RH, but in the opposite direction.” But it is very hard to even visually recognize the claimed strong correlations as you discussed and plotted them separately. Plot time series or scatter plots of daily C19 counts, T and RH in a single plot for each epicenter to better represent and help readers to clearly see the correlations? As authors did for their similar study by Sasikumar et al. (2020).

Reply: Thanks for the suggestion. We plotted the time series of T and RH together in a single plot for each of the countries in Supplementary figure 3-8.

Since we have used the NCEP data with a horizontal resolution of 2.5 x 2.5 deg, the timeseries of T and RH may not differ much between the epicenters within the country. Therefore, a country wide timeseries is better representing the variability of COVID-19 count, as a function of T and RH.

Comment 10: Page 7, line 207: replace “It addition” with “In addition”.

Reply: Corrected as suggested. Line 267.

Comment 11: Page 8, line 245: replace “ Figure 3b” with “ Figure 2b”.

Reply: Replaced as suggested. Line 321.

Comment 12: Page 8, line 263: in Supplementary information 1, that you mentioned, one paragraph is written twice.

Reply: Paragraph deleted as suggested.

Comment: 13: Page 8, line 274-276: rephrase the sentence. It is not clear.

Reply: Sentence rephrased as suggested. Line 349-350.

Comment 14: Page 8, line 278-280 and page 10, line 302-303: rephrase them that sharp and not-proved claim!

Reply: We agree with the reviewer. Therefore, we added the word “probably” in the above sentences. Line 351-356.

Comment 15: Page 9, Figure 4:

1) add the number of C19 counts for the regions on the figure where you represented the possible factors that might play role in the virous spread.

Reply: C19 counts added in figure 4 for the regions.

2) what did the different size of circles show in the figure? Explain it.

Reply: It has explained in Line 361.

3) Color for high and low temperatures are difficult to distinguish. Change the color.

Reply: The color has changed as suggested.

Comment 16: Page 9, line 288: mention the specific period.

Reply: Period mentioned as suggested. Line 319-320.

Comment 17: Page 10, line 299-300: What is the point of this comparison? Did you expect the C19 counts peak at the mean temperature of 16 countries?

 Reply: Weber & Stilianakis (2008)¹⁶ and Pyankova et al. (2018)¹⁷ reported that the existence and transmission of SARS-CoV virus and Middle East Respiratory Syndrome-Coronavirus (MERS-CoV-2012) in the atmosphere depends strongly on the environmental factors e.g. temperature, humidity, solar intensity etc. Secondly, the impact of climate change on epi­demiology of zoonotic disease²² and their transmission from animal species to human^23,24 are well reported. Line 70-73.

Global warming induced extreme weather events have strong negative impact on the biodiversity and seasonality of different vector borne diseases²⁵ (Line 89-91). It is reported that CO₂ emission due to unprecedented fossil fuel burning is the root cause of regional and global warming. An extreme hotter climate may induce excessive heat stress on the zoonotic species and it is providing a suitable environment for the viruses to adapt to the newer climate, as well. It could alter the relationship among the infectious agents, host species, and their interactions with the human's immune system (Line 374-380).

Therefore, from the above arguments it is evident that outbreaks of the infectious diseases have close association with the warming induced extreme climate change. From our present analysis we observed that COVID-19 count peaks at temperature which lies in the severe-extreme domain of the historical temperature distribution spectrum.

Comment 18: References:

Mecenas P., da Rosa Moreira Bastos R.T., Rosario Vallinoto A.C., Normando D., Effects of temperature and humidity on the spread of COVID-19: A systematic review. (2020)  PLoS ONE,  15  (9 September) , art. no. e0238339

Oliveiros B, Caramelo L, Ferreira NC, Caramelo F.: Role of temperature and humidity in the modulation of the doubling time of COVID-19 cases. (2020). Available from: https://www.medrxiv.org/content/10.1101/2020.03.05.20031872v1.

 Bukhari Q, Jameel Y. Will coronavirus pandemic diminish by summer? (2020).Available from: https://ssrn.com/abstract=3558757 https://doi.org/10.2139/ssrn.3556998

Reply: References (19, 20, and 35) added as suggested.

Author Response File: Author Response.pdf

Reviewer 2 Report

The subject and scope of the article are topical and important for explaining the causes of the current pandemic. I would consider the title in order to see if it really corresponds to its content. While the problem of the pandemic is clearly marked, climate change occurs as one of the analysed factors (next to population density, pollution and international air traffic).

Methods are described only briefly in the introduction. Although details about data sources was given in Appendix, the description of applied methods is still missing. According Journal’s requirements it should be a separate subsection Materials and Methods. 

There is also no clear discussion of the results, no reference to other research, that show a relationship between air pollution and a greater incidence of COVID -19.

Minor remarks:

• in keywords: instead of ’population’ maybe better: ‘population density’, because this factor was considered in the article,
• according to Journal’s requirements references should be given in brackets.

Author Response

Reply to the Comments

First of all we are thankful to the reviewer for reviewing our manuscript and providing valuable comments and suggestions. Below are the point by point replies to the comments and changes made in the revised manuscript are shown in red font.

Comment 1: The subject and scope of the article are topical and important for explaining the causes of the current pandemic. I would consider the title in order to see if it really corresponds to its content. While the problem of the pandemic is clearly marked, climate change occurs as one of the analysed factors (next to population density, pollution and international air traffic).

Reply: Thanks for the suggestion. We now revised the manuscript to make it more appropriate.

Comment 2: Methods are described only briefly in the introduction. Although details about data sources was given in Appendix, the description of applied methods is still missing. According Journal’s requirements it should be a separate subsection Materials and Methods. 

Reply: We apologize for the inconvenience. The methods are now discussed in Materials and methods section. Line 582-604.

Comment 3: There is also no clear discussion of the results, no reference to other research, that show a relationship between air pollution and a greater incidence of COVID -19.

Reply: We apologize for the inconvenience. We now added the discussions and references in the revised version. Line 164-174.

Minor remarks:

Comment 1: in keywords: instead of ’population’ maybe better: ‘population density’, because this factor was considered in the article,

Reply: Changes made as suggested. Line 46.

Comment 2: according to Journal’s requirements references should be given in brackets.

Reply: Changes made as suggested.

 

Author Response File: Author Response.pdf