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arXiv 2011.11381cs.AIcs.MAphysics.soc-ph

Elementary Effects Analysis of factors controlling COVID-19 infections in computational simulation reveals the importance of Social Distancing and Mask Usage

University of Warwick(华威大学);The Chinese University of Hong Kong(香港中文大学);University of Birmingham(伯明翰大学)

Kelvin K. F. Li, Stephen A. Jarvis, Fayyaz Minhas

英文摘要:

COVID-19 was declared a pandemic by the World Health Organization (WHO) on March 11th, 2020. With half of the world's countries in lockdown as of April due to this pandemic, monitoring and understanding the spread of the virus and infection rates and how these factors relate to behavioural and societal parameters is crucial for effective policy making. This paper aims to investigate the effectiveness of masks, social distancing, lockdown and self-isolation for reducing the spread of SARS-CoV-2 infections. Our findings based on agent-based simulation modelling show that whilst requiring a lockdown is widely believed to be the most efficient method to quickly reduce infection numbers, the practice of social distancing and the usage of surgical masks can potentially be more effective than requiring a lockdown. Our multivariate analysis of simulation results using the Morris Elementary Effects Method suggests that if a sufficient proportion of the population wore surgical masks and followed social distancing regulations, then SARS-CoV-2 infections can be controlled without requiring a lockdown.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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