The Impact of High-Density Urban Wind Environments on the Distribution of COVID-19 Based on Machine Learning: A Case Study of Macau
Round 1
Reviewer 1 Report
This paper explains in a very interesting way the relationship between COVID19 and the urban environment, I think it is a very important contribution to the scientific community to learn from this negative global experience. However, research related to COVID19 has been constantly published for the last 3 years, but what is the likelihood of a repeat global pandemic? If there is a repeat pandemic, would it have the same characteristics as COVID19? Will the same conclusions be useful?
All in all, the paper is interesting and suitable for publication if some minor modifications are made. However, the scientific community should reflect on whether to continue research on an exceptional and occasional episode or to focus its efforts on solving problems that existed before COVID19 and continue to exist after COVID19.
It is proposed to complete this article with the following suggestions:
- Section 1.1 explains the location of Macau, it would be interesting to include a figure on this.
- The literature review is scarce. A lot of literature has been published on COVID19 and housing conditions, it is suggested to expand the bibliography:
Confinement, Comfort and Health: Analysis of the Real Influence of Lockdown on University Students during the COVID-19 Pandemic. DOI: 10.3390/ijerph18115572
A Mixed Approach on Resilience of Spanish Dwellings and Households during COVID-19 Lockdown. DOI: 10.3390/su122310198
COVID-19 and overdose prevention: Challenges and opportunities for clinical practice in housing settings. DOI: 10.1016/j.jsat.2020.108153
- The main objective of this research needs to be written up more comprehensively.
- Why has the ECOTECT software been used, and what does it offer in comparison to other options?
- How reliable are these wind simulation models, and have they undergone any kind of calibration beforehand?
- The conclusions obtained from this study focus exclusively on COVID19, however, designing cities based on COVID19 from now on does not seem reasonable. Could this study be applied to the improvement of other diseases? For example: asthma or other diseases related to humidity or air quality.
This reviewer would like to congratulate the authors for this article, as their contribution is of real interest to the scientific community. A high value methodology has been used. However, he would also like to encourage further research to apply this methodology to the mitigation of other diseases that the population currently suffers from and where wind can have an impact.
Minor editing of English language required.
Author Response
Response: Yes, I thought so too. A similar pandemic of COVID-19 may only happen once every hundreds of years. But every pandemic that has swept the world has historically brought many thoughts and actions to improve the living environment. What we want to express is that COVID-19 is a major emergency, but similar endemic diseases still exist. Although it is not as serious as COVID-19, it is also related to the wind environment, and their transmission routes may be similar. Although we are not medical staff, we can still analyze the environment from a macro-level urban level, providing reference for subsequent urban design and housing planning.
It is proposed to complete this article with the following suggestions:
- Section 1.1 explains the location of Macau, it would be interesting to include a figure on this.
Response: Thank you for your suggestion. I think it's very helpful. This is useful for other readers to understand the location of Macau. Therefore, we have added Figure 1 here. At the same time, the numbering of subsequent figures has also been modified.
- The literature review is scarce. A lot of literature has been published on COVID19 and housing conditions, it is suggested to expand the bibliography:
Confinement, Comfort and Health: Analysis of the Real Influence of Lockdown on University Students during the COVID-19 Pandemic. DOI: 10.3390/ijerph18115572
A Mixed Approach on Resilience of Spanish Dwellings and Households during COVID-19 Lockdown. DOI: 10.3390/su122310198
COVID-19 and overdose prevention: Challenges and opportunities for clinical practice in housing settings. DOI: 10.1016/j.jsat.2020.108153
Response: Thank you for your suggestion. We have perfected this part of the literature review, and at the same time, divided the literature review into three levels of titles, and drafted related topics. The list of references has also been improved.
- The main objective of this research needs to be written up more comprehensively.
Response: Thank you for your suggestion. We have rearranged our thinking and made changes to 1.3.
- Why has the ECOTECT software been used, and what does it offer in comparison to other options?
Response: Thanks for your comments. In this study, the use of ECOTECT software has the following advantages: (1) Building performance simulation: ECOTECT can simulate the performance of buildings under different wind conditions. With the software, researchers can accurately assess the impact of different wind environments on the spread of COVID-19 and gain insight into the relationship between the built environment and virus spread. (2) Data collection and analysis: ECOTECT provides a wealth of data collection tools that can obtain the environmental parameters required by the building, such as wind speed, wind direction, indoor and outdoor temperature, etc. These data are crucial for studying the association of urban wind environments with the spread of COVID-19. (3) Result visualization: ECOTECT provides an intuitive result visualization function. Through charts and images, researchers can clearly display and present the analysis results. These visualization tools are important to convey research findings and conclusions to judges and readers and contribute to a better understanding of the link between urban wind environments and the spread of COVID-19.To sum up, ECOTECT software played an important role in this study. It provides functions such as building performance simulation, data collection and analysis, and result visualization, providing strong support for researchers to explore the relationship between urban wind environments and COVID-19 transmission.
- How reliable are these wind simulation models, and have they undergone any kind of calibration beforehand?
Response: Thanks for your comments. This study places emphasis on the reliability of the wind simulation model, and steps are taken to ensure its accuracy and credibility. (1) This study collected actual wind environment data from the Macao Meteorological Bureau as a reference for the model in the study. These data include parameters such as wind speed and wind direction, reflecting the real wind environment in Macau. (2) Ecotect is a commonly used environmental simulation software, and some past research can provide a basis for its reliability [1]. (3) The results of the wind simulation model are basically consistent with the actual situation after internal review by the researchers. Therefore, this study controls the reliability of wind simulation results in terms of basic data, simulation tools, and internal inspection.
[1] Thiodore, J., and Srinaga, F., 2021, May. Open Space Scenario on Riverside Settlement to Access a comfortable wind environment. In IOP Conference Series: Earth and Environmental Science (Vol. 764, No. 1, p. 012022). IOP Publishing.
- The conclusions obtained from this study focus exclusively on COVID19, however, designing cities based on COVID19 from now on does not seem reasonable. Could this study be applied to the improvement of other diseases? For example: asthma or other diseases related to humidity or air quality.
Response: Thanks for your comments. This study did focus on exploring the relationship between the urban wind environment and the spread of COVID-19, and the conclusions reached are mainly applicable to the new coronavirus. It does not make sense to design cities on the basis of COVID-19 from now on because the epidemic situation and virus characteristics may change over time. At the same time, this study also has certain reference values for the improvement of other diseases. Although the transmission mechanism and characteristics of each disease are different, there may be some commonalities in the influencing factors of the urban wind environment on disease transmission. For example, the spread of diseases related to humidity or air quality, such as asthma, may also be affected by the urban wind environment [1].This study provides an analytical approach focusing on the urban wind environment and COVID-19, which can provide useful guidance for urban planning and public health departments to consider the transmission risks of different diseases when designing cities. However, since transmission mechanisms and risk factors may differ for each disease, further research and context-specific analyses are needed when applying this study to the improvement of other diseases. This involves an in-depth study and evaluation of the transmission pathways, environmental factors, and associated data for a particular disease. Therefore, although the conclusions of this study are mainly applicable to COVID-19, the research methods and analytical framework can provide useful references for the improvement of other diseases and provide inspiration for future related research in the fields of urban planning and public health.
This reviewer would like to congratulate the authors for this article, as their contribution is of real interest to the scientific community. A high value methodology has been used. However, he would also like to encourage further research to apply this methodology to the mitigation of other diseases that the population currently suffers from and where wind can have an impact.
Response: Thank you for your encouragement and congratulations. I hope that our improvement of the thesis this time can meet the requirements for publication.
Reviewer 2 Report
Please see comments in the attachment
Comments for author File: 
Comments.pdf
Author Response
Response: Thanks for your comments. Pixels in this study refer to the basic display unit in an image. In the picture of the wind simulation, the pixels of different colors represent the numerical value of the wind speed. In the COVID-19 heat map, white to gray pixels represent the extent of an outbreak, and black pixels represent no outbreaks.In addition, we will make necessary supplements and modifications to the picture titles in the article.
Work is well written and carefully researched. It has a logical order of sections.
A certain disadvantage of the work is the fact that it refers to the conditions of Macau, which is correctly indicated in the title. The research results are undoubtedly very useful for Macau, but it is doubtful whether they will be of any use to other locations. The authors should emphasize and explain in more detail research limitations related to:
- what is the scientific soundness of the paper? What is the degree of scientific universality? Whether it concerns the results or only the method and whether the method used is suitable for any other location?
Response: Thanks for your comments. This study is scientifically sound and, to a certain extent, universal. This study uses systematic research methods (such as Ecotect wind environment simulation, generative confrontation network (CGAN), etc.) and reliable data sources (such as climate statistics from the Macao Meteorological Bureau) to make sure that the research is scientific and reliable.This study uses Generative Adversarial Networks (CGAN) as a main method to generate urban wind environment data and COVID-19 hotspot distribution maps. As mentioned in the literature review, GAN is a machine-learning-based tool that has been widely used in several fields and has a solid scientific foundation. The method achieves accurate simulation and generation of real data by training a generator network and a discriminator network. Generative adversarial networks have shown outstanding performance in tasks such as image generation, data augmentation, and simulation and have been extensively researched and validated.Based on the existing urban wind environment data and COVID-19 epidemic data, this study generates reliable and accurate wind environment data and COVID-19 hotspot distribution maps through generative adversarial networks. In the research, the training and verification of the model were carried out, and the comparison and analysis with the actual data were carried out. Through comparative analysis, the study found that the difference between the data generated by the model and the actual data was not significant (Figures 7 and 8 in the paper), which further verified the scientificity and applicability of the method used.Although the generative adversarial network was used to simulate the relationship between the COVID-19 epidemic and the wind environment in this study, the scientific and universality of this method are not limited to COVID-19 and can also be applied to other similar problems. Generative adversarial networks can generate simulation results similar to real data based on different input data and objectives. Therefore, in the research of other diseases or health problems related to humidity, air quality, and other factors, the method of generative adversarial networks can be used to explore the relationship between them and the urban wind environment.
- the research covered only residential areas. Would the results not be different in the case of areas with a high density of public utility buildings, e.g. hospitals (this problem was signaled in point 3.3). The covid hotspots seem to be a bigger problem in the case of buildings and their complexes that generate a large number of users - the so-called “urban junctions”.
Response: Thanks for your comments. This research mainly focuses on the relationship between the daily wind environment in residential areas and the spread of COVID-19. The purpose of the research is to find universal problems and draw conclusions. For special climate conditions, building types, and urban spaces, future research will be worthwhile. One of the key points In Section 3.3 of the article, the importance of the hospital as a special building is pointed out, and it is mentioned that when the model generates the COVID-19 hotspot distribution map, the accuracy of the hospital area may be affected to a certain extent. As an important public facility building, hospitals have different personnel flow and activity patterns from residential areas and may face higher epidemic risks and transmission challenges. Therefore, when assessing and predicting the spread of COVID-19 in hospital areas, more detailed and in-depth research is required, combined with hospital-specific environmental factors and control measures for analysis.Buildings and complexes that generate a large number of users, such as so-called "urban interchanges", may indeed face greater challenges. These areas often have a higher turnover and density of people, which may increase the risk of COVID-19 transmission. Therefore, studying the relationship between the wind environment at urban intersections and the spread of COVID-19 is a direction worthy of further research. For these special areas, more factors need to be considered, such as the concentration of people, building layout and usage patterns, ventilation systems, etc., to more comprehensively assess their relevance to the spread of the epidemic.Although this study only focuses on residential areas, public facilities, buildings, and urban intersections have an important impact on the spread of the epidemic. Therefore, future research can further expand the scope, deeply explore the relationship between the characteristics of the wind environment and the spread of the epidemic in these special areas, and formulate corresponding prevention and control strategies.
- the topic of the need to take into account more factors in future research should be developed and the meaning of the simple relationship between COVID hotspots and wind conditions should be explained against this background. It would be advisable to suggest the use of the systemic method in future more complex studies.
Response: Thanks for your comments. We agree with you that future research should consider more factors and adopt a systematic approach to more fully understand the complex relationship between COVID-19 virus hotspots and the wind environment. This study mainly focuses on the influence of the wind environment on the spread of COVID-19, but the spread of the epidemic is a complex process involving the interaction of multiple factors. Therefore, future research can integrate wind environmental factors with other factors, such as humidity, air quality, human flow patterns, etc., to gain a more comprehensive understanding.Also, you mentioned the implications of a simple relationship between COVID-19 virus hotspots and wind conditions. In this study, it was found that there is a certain correlation between wind environment factors and the distribution of COVID-19 virus hotspots, and different types of wind environments have different effects on the distribution of hotspots (Chapter Four of the article). This means that urban planning and public health departments can reduce the risk of epidemic transmission through reasonable urban design and wind environment control. However, this study only focuses on one aspect of the spread of the COVID-19 virus, and other factors such as social distance, personal behavior, hygiene measures, etc. are equally important. Therefore, future studies can consider these factors more systematically and use an integrated approach to explore the complexity of epidemic transmission. For example, multiple methods, such as mathematical models and crowd behavior simulations, can be combined to more comprehensively and accurately analyze the mechanism and influencing factors of the spread of the epidemic.
In addition, the work is only theoretical in some parts. It is hard to imagine implementing the Design Principles (p.4.3) in practice under the influence of Covid hotspots only. Covid is in the decline but the buildings remain for many years. This fact should also be commented on.
Response: Thanks for your comments. Some parts of this research are still at the theoretical stage, which may limit its direct application in practice. This study aims to explore the relationship between the urban wind environment and the spread of COVID-19, provide new perspectives for urban planning and public health departments to formulate strategies, and propose some design principles and guidelines to help reduce the risk of epidemic spread.However, the application of these principles in practice may face some challenges. Especially in the context of the current tapering of the pandemic, architectural and urban planning decisions need to consider long-term sustainability and variability. The lifespan of a building may span multiple pandemic cycles, so design decisions need to take into account a variety of factors, including special needs during the pandemic and future sustainability goals. In addition, the new coronavirus is not the only disease. Other diseases, such as asthma, are related to factors such as humidity and air quality. Therefore, in the implementation of design principles, the impact and needs of other diseases should be considered, and professionals in related fields such as urban planners, architects, and public health experts should actively cooperate through field observations, simulation experiments, case studies, etc. Methodology, validation, and refinement of design principles and guidelines to ensure their feasibility and effectiveness in practice.We will supplement the above content in the discussion of the article.
Other remarks:
What is the difference between p.2 and p.3 in the Abstract?
Response: Thank you for reminding. We double-checked and indeed some sentences were repeated. We made changes.
Round 2
Reviewer 2 Report
The paper has been revised correctly. I can recommend it to be published now, as it presents very high scientific level.
