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Influences of Obstacle Factors on the Transmission Trends of Respiratory Infectious Diseases in Indoor Public Places

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posted on 31.05.2022, 16:09 authored by Ziwei CuiZiwei Cui, Ming Cai, Yao Xiao, Zheng Zhu, Gongbo Chen

 Public facilities are important transmission places for respiratory infectious diseases (e.g., COVID-19), due to the frequent crowd interactions inside. Usually, changes of obstacle factors can affect the movements of human crowds and result in different epidemic transmission among individuals. Most related studies only focus on the specific scenarios, but the common rules are usually ignored for the impacts of obstacles’ spatial elements on the epidemic transmission. To tackle these problems, this study aims to evaluate the impacts of three spatial factors of obstacles (i.e., size, quantity, and placement) on infection spreading trends in two-dimension, which can provide scientific and concise spatial design guidelines for indoor public places. Firstly, we used the obstacle area proportion as the indicator of the size factor, gave the mathematical expression of the quantity factor, and proposed the walkable-space distribution indicator to represent the placement factor. Secondly, two epidemic spreading indicators (i.e., daily new cases and people’s average exposure risk) were estimated based on the fundamental model named exposure risk with the virion-laden droplets, which forecasted the disease spreading between individuals accurately. Thirdly, 120 indoor scenarios were built and simulated, based on which the value of independent and dependent variables can be measured. Besides, the Pearson correlation analysis and linear regression analysis were employed to examine the relations between obstacle factors and epidemic transmissions. Finally, several design guidelines were provided for policymakers to mitigate the disease spreading: minimizing the size of obstacles; increasing the obstacle quantity and adopting the uniform obstacle placement by lifting the smallest size of the walkable convex space. 


National Natural Science Foundation of China (Grant No. 72101276)

Shenzhen Science and Technology Innovation Committee (Grant No. GXWD 20200830165201001)

Fundamental Research Funds for the Central Universities (Grant No. 22qntd1710)


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School of Intelligent System Engineering, Sun Yat-Sen University, Shenzhen, Guangdong

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