Space–Time Analysis of the COVID-19 Pandemic and Its Relationship with Socioeconomic and Demographic Variables in the Metropolitan Region of São Paulo, Brazil

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

see attached

Comments for author File: Comments.pdf

Author Response

The abstract ended abruptly w/o a satisfying conclusion statement.

We changed the summary. Thank you.

 

The introduction is very weak. Authors should add a brief summary on studies which have examined spatiotemporal patterns of the COVID-19 in São Paulo or in Brazil, what methods/models have been used to detect COVID-19 clusters, and highlight the significance and novelty of this particular study.

 

We have reinforced the introduction and brought in new references. We have highlighted the importance and novelty of this particular study in lines 71 to 87.

 

Line 96 – What is PA? Or a typo for WA?

 

Yes, WA, we adjusted.

 

Line 131 – Authors stated “When the population size significantly differs between the areas studied, adjustments must be made before modeling, either by excluding areas with large populations or by subdividing these areas into smaller populations”. It is not clear to me if authors made any adjustments to the WAs of the municipality of São Paulo and nearby municipalities, since these areas are smaller due to population size. If no adjustment was made, no evidence was provided to support the statement that “but it does not invalidate the quality of data presented in this study”.

 

In our study, population size does not differ significantly between the areas studied, requiring no adjustments before modeling, either by excluding areas with large populations or by subdividing areas into smaller populations. This is because WAs are designed based on population size, so that statistical analyses of the population census are possible. We removed the paragraph.

 

The 1st COVID case was detected on 2/25/20 in Brazil. In February, there were about 6 cases in the São Paulo State. The case count started to explode in March. I was surprised to see a high-death cluster (w RR=3.49) in February 2020 in Figure 5.

 

It was wrong. In February 2021. We fixed it. Thank you.

 

Line 248 – “Population density in high-risk clusters had a lower median than in low-risk clusters; however, this significant value may have been influenced by data amplitude”. I don’t understand the reasoning. Please revise.

 

We revised the sentence in the lines 288 to 292. Thank you.

 

Line 312 – “There were no significant differences between the population densities of the clusters in relation to the values found, with strong internal heterogeneity identified within the groups.” What values are we referring to here. Please revise.

 

We rewrote all discussion. This paragraph no more exists. Thank you

 

Line 332 – “other factors may be associated with the space-time inequality of cases and deaths, such as the prevalence of comorbidities in the population, risk behaviors like smoking and alcohol consumption, as well as conditions of vulnerability.” Please insert appropriate citations, if there are any.

 

We rewrote all discussion. This paragraph no more exists. Thank you

 

Line 336 – I feel Introduction is a better place for this paragraph than discussion.

 

We rewrote all discussion. This paragraph no more exists. Thank you

 

Discussion could be improved. It is OK to reiterate the main findings of the study in the

discussion. However, in multiple paragraphs, almost all of the content are results except one or two sentences. In addition, if time allows, authors could re-organize the discussion section so that the flow of the points is more organic.

 

We improved the discussion and it is more organic. Thank you.

 

Any limitation(s) in this study?

 

Yes. We have placed the limitations on lines 434 to 444. Thank you.

 

If time allows, authors could expand the last paragraph and turn it into a proper conclusion section.

 

We included a conclusion section. Thank you.

 

 

Minor issues/comments

 

Authors conducted the space-time SaTScan analyses separately for two continuous periods (Year 1 <March 2020 to February 2021> and Year 2 <from March 2021 to February 2022>). Personally, I think it might be more appropriate to run the space-time SaTScan analysis using 24 months of data instead of two sets of 12-month data. Nevertheless, it is quite possible that the results would be similar.

 

We first tried the analysis with the 24 months. But the spatiotemporal cluster of the first year was not identified. The months of March to May 2021 had surprisingly high rates of cases and deaths.

 

 

 

The resolution of the maps is low.

 

We changed the map. Line 115.

 

The term high-risk cluster is misleading. It might be better to call them what they are, i.e., high-incidence cluster or high-mortality cluster. Because the map doesn’t necessary mean that an individual residing in a high-incidence cluster is more likely to get COVID. This risk depends on many things. Also, it is most likely there are areas inside a high-incidence cluster that have statistically lower incidence.

We changed. Thank you.

 

Please specify that the statistics are for high-incidence clusters in Table 1.

 

We included. Thank you.

 

Line 199 – “The interquartile range of cluster 3 was also much higher than the first and especially the third quartile of clusters 1 and 2”. The definition of interquartile is the difference between the 75th and 25th percentiles of the data. Please revise.

 

We removed the paragraph. Thank you.

 

Please revise the order of RRs in the legend of Figure 5 top panel, so that they are properly sorted. I have somewhat impaired vision. It is difficult for me to differentiate so many shaded colors in this map. There is a typo in the figure legend - June, not Juno. For consistency, how about changing the subtitle of the figures to “space-time cluster of deaths due to COVID-19 in Year 1 (March 2020 through Feb. 2021)” and “space-time cluster of deaths due to COVID-19 in

Year 2 (March 2021 through Feb. 2022)”? <This suggestion applies to other table/figure titles as well.>

We fulfill the request on all maps.

 

In Table 1, the asterisk indicates that areas in cluster 3 is statistically different (higher or lower) compared to areas in clusters 1 or 2 on a specific demographic or SES indicator. It is better to use an asterisk for significant difference between clusters 3 and 1, and asterisks (or another symbol) between clusters 3 and 2.

In the test we performed, we were unable to make this difference. H0 is that there is no difference between the groups.

Reviewer 2 Report

Comments and Suggestions for Authors

Identifying the impact of the COVID-19 pandemic and analyzing the relationships between it and socioeconomic and demographic factors is significant for control and surveillance actions. However, I recommend a major revision prior to publication. Here are some suggestions for improvement.

1.     The author emphasized the important role of GIS in the Abstract and Introduction sections. However, what is the research focus and innovation of this research? It is suggested to reflect in the above sections to improve reading and understanding.

2.     The Introduction section is seriously short of summarizing and expounding the relevant research. A literature overview of the current research topic should be supplemented. Additionally, what are the aims and values of this study?

3.     The clarity of Figures needs to be further improved. In addition, it should also pay attention to (1) The colors of various regions or clusters in the figure are too close to make it difficult to read. It is suggested to adjust them appropriately; (2) Although subgraphs A and B are distinguished in the name of the figures, they are not found on figures, such as Figure 2, Figure 3, Figure 4, Figure 5(4A? 4B?).

4.     In the Materials and Methods section, all the research methods are simply described. The author should consider adding formulas or principles appropriately to enhance understanding. In addition, where is the GIS method mentioned above reflected?

5.     It is suggested to add an analytical framework to clearly summarize and present all the contents.

6.     The socioeconomic variables obtained from the 2010 census? Although the author said that it is the most recent census available. The influence of the mismatch of data on the research results should be further informed and discussed.

7. Although the term of this study is "Space-Time Analysis of the COVID-19 Pandemic and Its Relationship with Socioeconomic and Demographic Variables", there is a lack of in-depth discussion on their relationship, especially in the abstract and discussion section.

8. Last but not least, what are the important findings in this research? Is it similar to other research results? If so, where is the innovation of this article? It is suggested to explain it in the article

Comments for author File: Comments.pdf

Comments on the Quality of English Language

The language needs to be polished

Author Response

1. The author emphasized the important role of GIS in the Abstract and Introduction sections. However, what is the research focus and innovation of this research? It is suggested to reflect in the above sections to improve reading and understanding.

 

The research focus and innovation of the research was improved. Line 71 to 86. Thank you.

 

2. The Introduction section is seriously short of summarizing and expounding the relevant research. A literature overview of the current research topic should be supplemented. Additionally, what are the aims and values of this study?

The Introduction section and literature overview were supplemented. The aims and values of the study was clarified on the line 61 to 70.

 

3. The clarity of Figures needs to be further improved. In addition, it should also pay attention to (1) The colors of various regions or clusters in the figure are too close to make it difficult to read. It is suggested to adjust them appropriately; (2) Although subgraphs A and B are distinguished in the name of the figures, they are not found on figures, such as Figure 2, Figure 3, Figure 4, Figure 5(4A? 4B?).

We respond to requests. Thank you.

 

4. In the Materials and Methods section, all the research methods are simply described. The author should consider adding formulas or principles appropriately to enhance understanding. In addition, where is the GIS method mentioned above reflected?

 

To improve understanding, we have included new explanation in lines 157 to 178.

 

5. Sugere-se adicionar uma estrutura analítica para resumir e apresentar claramente todo o conteúdo.

 

We have clarified the content of lines 170 to 178. Thank you.

 

6. The socioeconomic variables obtained from the 2010 census? Although the author said that it is the most recent census available. The influence of the mismatch of data on the research results should be further informed and discussed.

 

The influence of the mismatch of data on the research results was included at discussion section on line 425 to 430. Thank you.

 

7. Although the term of this study is "Space-Time Analysis of the COVID-19 Pandemic and Its Relationship with Socioeconomic and Demographic Variables", there is a lack of in-depth discussion on their relationship, especially in the abstract and discussion section.

We in-depth discussion the Relationship with Socioeconomic and Demographic Variables on the line 366 to 409.

 

8. Last but not least, what are the important findings in this research? Is it similar to other research results? If so, where is the innovation of this article? It is suggested to explain it in the article.

 

The findings and innovation of research was clarified on the line 407 – 422. Thank you

Reviewer 3 Report

Comments and Suggestions for Authors

In the introduction, the authors could better contextualize the entry
of the SARS-CoV-2 coronavirus in the state of São Paulo.

The methodology used is very well detailed, with analyses both by year and by month, which allowed us to obtain precise data on the evolution of the disease
during this period.

In the discussion, it could be more detailed which factors contributed to the expected number of cases being well below the forecasted by the analysis (Figure 2b).The authors could better explain Figure 5, which shows a variation in the evolution of the locations with the highest mortality rates during
the pandemic, and why the BBIP population became so vulnerable to COVID-19.

The article is well-organized, uses clear language, and meets the proposed objectives.

Author Response

1 - In the introduction, the authors could better contextualize the entry of the SARS-CoV-2 coronavirus in the state of São Paulo.

We review the introduction and contextualized the entry of the SARS-CoV-2 coronavirus in the state of São Paulo. Line 41 to 59. Thank you.

 

2 - The methodology used is very well detailed, with analyses both by year and by month, which allowed us to obtain precise data on the evolution of the disease during this period.

Thank you.

 

3 - In the discussion, it could be more detailed which factors contributed to the expected number of cases being well below the forecasted by the analysis (Figure 2b). The authors could better explain Figure 5, which shows a variation in the evolution of the locations with the highest mortality rates during the pandemic, and why the BBIP population became so vulnerable to COVID-19.

 

Factors contributed to the expected number of cases being well below the forecasted by the analysis (Figure 2b) – Line 317 to 320. We explain why the BBIP population has become so vulnerable to COVID-19 in lines 388 to 398. Thank you.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

 

 

Review Report

 

Authors applied the SaTScan software to the monthly observed vs. the expected number of COVID-10 cases/deaths after adjusting for sex and age in the Metropolitan Region of São Paulo (MRSP) from March 2020 to February 2021 and March 2021 to February 2022. Spatiotemporal clusters with statistically high incidence, as well as clusters with high/low mortality, were identified in different areas and in different time periods. The socioeconomic and demographic characteristics of these clusters were examined. All clusters were identified in densely occupied areas. Findings showed that the spread of COID-19 was related to income and ethnicity, as well as to the circulation dynamics of a metropolitan region.

 

Major Issues/Comments

 

·         The authors should clearly explain how the expected number of cases were estimated in the method section. e.g., are they age-adjusted?

·         Line 161 - The null hypothesis (H0) should be that the observed number of cases is the same as the expected. Please correct.

·         Line 407 - “we observed that although no low-mortality clusters of disease incidence were found, the low-risk clusters of mortality from COVID-19 were located in the center southwest region of the city of São Paulo”. This statement is contradicting to the results. In Figure 5, there are 2 low-mortality cluster in the Year 1 and 1 in Year 2. Or maybe the authors meant to say there were no low-incidence cluster in the center southwest region of the city of São Paulo, but there was a low-mortality cluster? Please revised.

·         Table 1 - Wrong info on the study period: March 2020 to February 2022, not 2021. Please correct.

·         Figure 5 - “Space-time clusters of COVID-19 deaths in the first year of during the pandemic. (4A)… (4B)…”.

·         Line 429 – What is an AP scale?

·         Line 446 – What is WP?

 

Suggestions

 

·         Please use high-resolution (with 600+ DPI) images for all maps and plots.

·         Table 1

o   For consistency with the text, how about using the terms Year 1 (or the 1^st study period) and Year 2 (or the 2^nd study period) in the table? e.g., high-incidence cluster in Year 1.

o   How about changing the table title to “Median and interquartile range of socioeconomic indicators of the weighting areas in the 246 MRSP from March 2020 to February 2021 in Year 1 (March 2020 to April 2021) and Year 2 (March 2021 to April 2022)…”

·         Please use consistent languages when referring to the 2 study periods in all tables and figures.

·         It looks like how to define the study period(s) (i.e., 1 period w 24 months vs 2 periods with 12 months each) affects the findings. The authors could discuss this either a sort of sensitivity test or a limitation of the SatScan analysis.  

·         Lines 364 to 366 – Introduction might be a better place for this paragraph. In the discussion, we usually talk about how our results support or fail to substantiate the hypothesis.

Author Response

 

• The authors should clearly explain how the expected number of cases were estimated in the method section. e.g., are they age-adjusted?

 

The explanation has been included in lines 166 to 177. Thank you.

 

• Line 161 - The null hypothesis (H0) should be that the observed number of cases is the same as the expected. Please correct.

We have made the change. Thank you.

 

• Line 407 - “we observed that although no low-mortality clusters of disease incidence were found, the low-risk clusters of mortality from COVID-19 were located in the center southwest region of the city of São Paulo”. This statement is contradicting to the results. In Figure 5, there are 2 low-mortality cluster in the Year 1 and 1 in Year 2. Or maybe the authors meant to say there were no low-incidence cluster in the center southwest region of the city of São Paulo, but there was a low-mortality cluster? Please revised.

We revised. Thank you.

 

• Table 1 - Wrong info on the study period: March 2020 to February 2022, not 2021. Please correct.

We have corrected the text. Thank you.

 

• Figure 5 - “Space-time clusters of COVID-19 deaths in the first year of during the pandemic. (4A)… (4B)…”.

 

We included the word.

 

• Line 429 – What is an AP scale?

Sorry, it is WA (weighting areas). We change it.

 

• Line 446 – What is WP?

Sorry, it is WA (weighting areas). We change it.

 

 

Suggestions

 

• Please use high-resolution (with 600+ DPI) images for all maps and plots.

 

We now use high-resolution (with 600+ DPI) images for all maps. But the plots are output from SatScan software and we cannot change the resolution. We try to improve the resolution of the plots in image editing software.

• Table 1

o   For consistency with the text, how about using the terms Year 1 (or the 1^st study period) and Year 2 (or the 2^nd study period) in the table? e.g., high-incidence cluster in Year 1.

We have made the change. Thank you.

o   How about changing the table title to “Median and interquartile range of socioeconomic indicators of the weighting areas in the 246 MRSP from March 2020 to February 2021 in Year 1 (March 2020 to April 2021) and Year 2 (March 2021 to April 2022)…”

We have made the change. Thank you.

• Please use consistent languages when referring to the 2 study periods in all tables and figures.

We have complied with the request. Thank you.

 

• It looks like how to define the study period(s) (i.e., 1 period w 24 months vs 2 periods with 12 months each) affects the findings. The authors could discuss this either a sort of sensitivity test or a limitation of the SatScan analysis.  

 

We included in the discussion on lines 450 to 460. Thank you.

 

• Lines 364 to 366 – Introduction might be a better place for this paragraph. In the discussion, we usually talk about how our results support or fail to substantiate the hypothesis.

 

We place the paragraph in the introduction on lines 70 to 72. Thank you.

Reviewer 2 Report

Comments and Suggestions for Authors

I still insist that the description in the Introduction and Methods section is not enough to accept publication. In addition, the name of Figure 5 needs to be checked further.

Comments on the Quality of English Language

Minor editing of English language required.

Author Response

I still insist that the description in the Introduction and Methods section is not enough to accept publication. In addition, the name of Figure 5 needs to be checked further.

We improved the introduction and method. Thank you.