A Fine-Grained Simulation Study on the Incidence Rate of Dysentery in Chongqing, China

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I'm grateful for your fascinating research. Several minor recommendations were made to enhance the manuscript.

1) It is better to change the term "products" to the best terms. For example, "grained scale products" can be changed by "grained scale spatial units" or "cell grids" instead of "grid products" etc. You may use another suitable term.

2) Usually, we put the abbreviation in parentheses and the full form before it. For example, "initialized gradient boosted decision trees (IGBDT)" invested "IGBDT (initialized gradient boosted decision trees)".

3) How many patients were studied? Not mentioned in the abstract.

4) Access to the codes you utilized in your study, like Markdown files, is tremendously beneficial to both readers and reviewers. If the data you used for your study is publishable, it is also preferable to include it as an appendix. If it is possible, share it with us in your revision step.

 

Thank you.

Author Response

Point 1: It is better to change the term "products" to the best terms. For example, "grained scale products" can be changed by "grained scale spatial units" or "cell grids" instead of "grid products" etc. You may use another suitable term.

Response: Thank you for your kind suggestions. We have decided to adopt your proposed change from "grid products" to "grained scale products" for all relevant sections in the manuscript.

 

Point 2: Usually, we put the abbreviation in parentheses and the full form before it. For example, "initialized gradient boosted decision trees (IGBDT)" invested "IGBDT (initialized gradient boosted decision trees)".

Response: Thank you for your kind suggestions. We have implemented the suggested format throughout the entire manuscript, replacing all instances involving abbreviations and their full forms with a structure similar to " initialized gradient boosted decision trees (IGBDT)."

 

Point 3: How many patients were studied? Not mentioned in the abstract.

Response: Thank you for your questions and suggestions. To obtain the total number of dysentery cases in Chongqing from 2015 to 2021, we multiplied the dysentery incidence rate in Chongqing (source link: https://data.cnki.net/yearBook/single?id=N2021100072) by the population of Chongqing (source link: https://data.cnki.net/yearBook/single?id=N2022110023), and then summed the results. This calculation yielded an approximate total of 37,140,800 patients. Finally, we added statements in the Abstract (Page 1, Line 10-11) and Study area (Page 3, Line 109-111) to explain the total number of dysentery patients in Chongqing during the period from 2015 to 2021.

 

Point 4: Access to the codes you utilized in your study, like Markdown files, is tremendously beneficial to both readers and reviewers. If the data you used for your study is publishable, it is also preferable to include it as an appendix. If it is possible, share it with us in your revision step.

Response: Thank you very much for your suggestion. The data and experimental codes used in this study are indeed publishable. We will include the codes and data as an appendix for your access.

Reviewer 2 Report

Comments and Suggestions for Authors

I congratulate the authors for their study. It was a good study about the association of dysentery and spatial criteria. In the study, factors related to the spread of dysentery were examined and which factors were more effective were investigated. Using machine learning techniques, the factors of dysentery have been revealed in a descriptive way. Below I have stated a few minor suggestions for authors.

 

Line 60: You used GDP as abbreviation. The first use should not be an abbreviation.

Line 63: Since you have used random forest as RF before, continue as RF. You have already explained its abbreviation in the line above.

Figure 1: It should be stated which map the legend used belongs to or shown within that figure. Because Figure 1(a) and Figure 1(b) contain data at different rates.

    Also, the color tones in Figure 1(b) and the legend seem to be slightly different (especially the darkest color). I recommend you review it.

 

   It would be better for your map if you write the region names in Figure 1(b).

Line 244: You mentioned the Yangtze River basin, but readers have difficulty finding these areas on maps. Therefore, it will be more understandable if you show the areas you want to specify on the map.

Figure 2: In your previous map, you used “km” as the unit of scale. But you used “miles” in this map. It would be beneficial to use a common unit of scale. Also show the borders of the regions within Chongqing on this map and your other maps below. In this way, the maps will be more understandable.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Socioeconomic factors, meteorological factors, topographic factors and air quality factors were used as inputs of the IGBDT to map the statistical dysentery incidence rate data of Chongqing..

Comment:

1. Why do you choose 'Socioeconomic factors, meteorological factors, topographic factors and air quality factors' ? Why not others? Please justify.

2. Why Chongqing? Not other cities like Beijing?

3. Why dysentery? Not other diseases? 

4. How do you relate your findings to the idea of UN-SGDs?

5. From the social point of view, can you finding solutions the problem of dysentery incidence in Chongqing? How and why?

 

 

Author Response

Point 1: Why do you choose 'Socioeconomic factors, meteorological factors, topographic factors and air quality factors'? Why not others? Please justify.

Response: Thank you for your question. The reason we chose 'socioeconomic factors, meteorological factors, topographical factors, and air quality factors' is because, after reviewing an extensive body of literature, we found that these factors have a significant impact on the incidence of dysentery and are well-supported by extensive research.

Socioeconomic factors [1, 2], such as population and economic development status, have a significant impact on the spread and incidence of diseases. Regions with low income, lower levels of education, and poor sanitation conditions are often more vulnerable to infectious diseases like dysentery. Meteorological factors [3-5] such as temperature, precipitation, and humidity, can influence water source contamination and bacterial proliferation, thereby affecting the transmission of dysentery. Seasonal weather changes may also be associated with dysentery outbreaks. Moreover, topographical factors [6, 7]，such as slope and elevation differences, impact the distribution of water sources and the direction of water flow. This can influence water source contamination and the availability of water supply systems, thereby affecting the prevalence of dysentery. Air quality factors [8, 9], such as PM2.5 and PM10, have adverse effects on health and can weaken the immune system, showing a strong correlation with dysentery incidence.

Furthermore, our selection of influencing factors was based on the feasibility of the research and the availability of data. The focus of this study is to use machine learning to downscale the incidence of dysentery to fine-grained grid products. Therefore, the factors we chose must have data available at a grid-scale resolution. For instance, in socioeconomic factors, we included products like nighttime lights and population. In meteorological factors, we considered products such as precipitation and relative humidity. For topographical factors, we incorporated products like Digital Elevation Models (DEMs) and slope. In terms of air quality factors, we included products like PM_2.5 and PM₁₀.

Of course, there are other factors that may influence the transmission of dysentery, such as gender differences between males and females [10]，and the frequency of flooding events[11, 12], among others. However, based on the two reasons mentioned above, we ultimately selected "socioeconomic factors, meteorological factors, topographical factors, and air quality factors" as the influencing factors for this study. In future research, we will consider a more comprehensive range of factors to investigate the incidence of dysentery.

In the Introduction section, we have further elaborated on the reasons for our choice of influencing factors, making the logic more comprehensive (Page 2, Line 60-65).

1. Kotloff, K.L., et al., Shigellosis. Lancet (North American Edition), 2018. 391(10122): p. 801-812.
2. Holt, K.E., et al., Shigella sonnei genome sequencing and phylogenetic analysis indicate recent global dissemination from Europe. Nature genetics, 2012. 44(9): p. 1056-1059.
3. Zhang, X.X., et al., Spatiotemporal variations in the incidence of bacillary dysentery and long-term effects associated with meteorological and socioeconomic factors in China from 2013 to 2017. Science of the Total Environment, 2021. 755.
4. Gao, L., et al., Meteorological Variables and Bacillary Dysentery Cases in Changsha City, China. American Journal of Tropical Medicine and Hygiene, 2014. 90(4): p. 697-704.
5. Li, Z.J., et al., Identifying high-risk areas of bacillary dysentery and associated meteorological factors in Wuhan, China. Scientific Reports, 2013. 3(1): p. 3239.
6. Zhang, Y., et al., Spatio-temporal analysis of bacillary dysentery in Sichuan province, China, 2011-2019. BMC Infectious Diseases, 2021. 21(1): p. 1-10.
7. Zuo, S., et al., The direct and interactive impacts of hydrological factors on bacillary dysentery across different geographical regions in central China. Science of The Total Environment, 2021. 764: p. 144609.
8. Deryugina, T., et al., The mortality and medical costs of air pollution: Evidence from changes in wind direction. American Economic Review, 2019. 109(12): p. 4178-4219.
9. Han, X., et al., Effects of ambient temperature and air pollutants on bacillary dysentery from 2014 to 2017 in Lanzhou, China. 2020.
10. Khezzani, B., et al., Incidence rates of dysentery among humans in Lemghaier province, Algeria. Germs, 2022. 12(2): p. 195-202.
11. Ma, Y., et al., Associations between floods and bacillary dysentery cases in main urban areas of Chongqing, China, 2005-2016: a retrospective study. Environmental Health and Preventive Medicine, 2021. 26(1): p. 1-9.
12. Xin, X., et al., Association between floods and the risk of dysentery in China: a meta-analysis. International Journal of Biometeorology, 2021. 65(7): p. 1245-1253.

 

Point 2: Why Chongqing? Not other cities like Beijing?

Response: Thank you for your question. There are some significant reasons for choosing Chongqing over other cities, such as Beijing. Firstly, during the period from 2015 to 2021, the Chongqing region in China reported approximately 37,140 cases of dysentery. Its average incidence rate was significantly higher than the national average and ranked fourth among all provinces in the country, with an incidence rate of 16.91 cases per 100,000 people. These data clearly highlight the pressing need to address dysentery transmission and control issues within the Chongqing region.

Secondly, Chongqing's geographical environment is highly complex, situated in a mountainous terrain with multiple rivers converging. This geographical condition could potentially increase the complexity of dysentery transmission. And, as a representative province in the southwestern region of China, Chongqing boasts a substantial population and diverse economic activities. Therefore, studying dysentery in Chongqing not only provides valuable insights for the region itself but also offers useful experiences and lessons for areas with similar geographical and social conditions. This contributes to a better understanding of dysentery transmission and control in both China and other regions. Consequently, research on Chongqing holds significant academic and practical research value.

Furthermore, due to the lag and confidentiality of dysentery incidence rate data, we conducted extensive searches in the health statistics yearbooks of various provinces. We found that only Chongqing Municipality had publicly accessible dysentery incidence rate data for various years across its districts and counties (source link: https://data.cnki.net/yearBook/).

Therefore, considering the availability of data and the unique characteristics of Chongqing, we ultimately chose Chongqing as our study area. We have further refined and supplemented the reasons for selecting Chongqing as our study area (Page 3, Line 109-115).

 

Point 3: Why dysentery? Not other diseases?

Response: Thank you for your question. Dysentery is an intestinal infectious disease, which remains a severe global public health issue, characterized by its high contagiousness and complex transmission pathways, especially in developing countries [1-3]. According to a report from the World Health Organization (https://www.who.int/), diarrhoeal is the second leading cause of death among children under the age of five. Approximately 525,000 children under the age of five die from diarrhoeal each year, and there are approximately 1.7 billion cases of diarrhoeal in children worldwide every year. And, dysentery is a significant subtype of diarrhea.

        Certainly, it is not our intention to diminish the importance of other diseases. In our future research, we plan to employ similar methods and approaches to address other prevalent and serious diseases, such as tuberculosis and dengue fever, among others.

Due to the significance of dysentery, we have chosen it as the subject of our research. In our Introduction section, we provide a comprehensive and strengthened rationale for why we have selected dysentery as our research focus (Page 1, Line 34-38).

 

1. Khezzani, B., et al., Incidence rates of dysentery among humans in Lemghaier province, Algeria. Germs, 2022. 12(2): p. 195-202.
2. Xin, X., et al., Association between floods and the risk of dysentery in China: a meta-analysis. International Journal of Biometeorology, 2021. 65(7): p. 1245-1253.
3. Du, Z., et al., Association between distribution of bacillary dysentery and meteorological factors in Beijing, 2004-2015. Zhonghua Liu Xing Bing Xue za Zhi, 2018. 39(5): p. 656-660.

 

Point 4: How do you relate your findings to the idea of UN-SGDs?

Response: Thank you for your question. The United Nations New Development Agenda typically refers to the Sustainable Development Goals (SDGs) adopted by the United Nations in 2015. The third goal of the United Nations' sustainable development is "Good Health and Well-being," aiming to eliminate the prevalence of diseases such as HIV/AIDS, tuberculosis, malaria, and other infectious diseases by 2030 (https://www.un.org/en/exhibits/page/sdgs-17-goals-transform-world).

Although dysentery is not explicitly mentioned in the SGDs, it remains a significant infectious disease with a substantial impact on public health, particularly in developing countries. This study, using machine learning and its related influencing factors, fine-scaled the statistical data of dysentery incidence rates in Chongqing from 2015 to 2021 (at a resolution of 1 km) and explored the importance and relevance of these factors. The ultimate conclusion is that socioeconomic and meteorological factors are the most significant contributors, together accounting for approximately 76% of the variance.

Our research provides practical support for achieving the United Nations Sustainable Development Goal of "Good Health and Well-being." Firstly, our study has generated dysentery incidence grained scale products (1km), which assists government and healthcare organizations in accurately identifying high-risk dysentery areas. This enables them to allocate resources efficiently and implement targeted governance and monitoring to reduce the spread of dysentery. Secondly, our research has unveiled the crucial influencing factors behind dysentery incidence rates, offering guidance for policy formulation and intervention measures. This contributes to the reduction of infectious disease transmission and the improvement of public health, ultimately aligning with the United Nations Sustainable Development Goal of "Good Health and Well-being." Furthermore, our research approach provides a new perspective and research method for studying other prevalent infectious diseases, contributing to the collective efforts to achieve "Good Health and Well-being."

We have enhanced and supplemented the relationship with the United Nations development goals (Page 1, Line 43-45).

 

Point 5: From the social point of view, can you finding solutions the problem of dysentery incidence in Chongqing? How and why?

Response: Thank you for your question. Firstly, based on the research findings in this article, dysentery primarily occurs in densely populated and economically underdeveloped areas. Therefore, from a societal perspective, it is crucial to implement targeted measures in densely populated and economically disadvantaged regions. Since dysentery is mainly a water and foodborne disease, these measures may include improving sanitation facilities, ensuring the provision of clean drinking water, and actively promoting hygiene education and awareness campaigns. As economic development often correlates with improvements in social infrastructure and sanitation facilities [1, 2], governments should strive to promote economic activities and focus on raising economic levels to enhance social infrastructure, including sanitation facilities and water supply systems. These measures help reduce the transmission of dysentery, improve public health standards, and ultimately address the dysentery issue in Chongqing.

Furthermore, this study obtained dysentery incidence rate grained scale products for Chongqing from 2015 to 2021 (1km). This grid data provides a powerful tool for various stakeholders, helping government and health institutions to more accurately pinpoint specific blocks within densely populated and economically underdeveloped areas that pose a high risk for dysentery. This allows them to allocate resources strategically and implement targeted governance and monitoring measures to reduce the transmission of dysentery. Compared to the traditional methods based on administrative divisions, this fine-grained monitoring is more precise and effective, contributing to a decrease in dysentery transmission. We have added policy recommendations and measures in the manuscript's conclusion (Page 13, Line 453-466).

 

1. Srinivasu, B., P.S.J.J.o.b.m. Rao, and S.s. research, Infrastructure development and economic growth: Prospects and perspective. 2013. 2(1): p. 81-91.
2. Gnade, H., P.F. Blaauw, and T.J.D.S.A. Greyling, The impact of basic and social infrastructure investment on South African economic growth and development. 2017. 34(3): p. 347-364.