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标题：Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas
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作者：Alberto Aleta ; David Martín-Corral ; Michiel A. Bakker 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2022
卷号：119
期号：26
DOI：10.1073/pnas.2112182119
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Significance The characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission risks across different settings remains unclear, including the roles of individual and setting heterogeneity. We integrate anonymized time-resolved mobility data with census and demographic data in the New York City, NY and Seattle, WA metropolitan areas to characterize the magnitude and heterogeneity of transmission events during the first COVID-19 wave. We simulate COVID-19 epidemic trajectories to study the impact of interventions, the part played by different settings in the infection spreading, and the role of superspreading events. Our results indicate that places are not dangerous on their own; instead, transmission risk is a combination of both the characteristics of the place/setting and the behavior of individuals who visit it. Detailed characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission across different settings can help design less disruptive interventions. We used real-time, privacy-enhanced mobility data in the New York City, NY and Seattle, WA metropolitan areas to build a detailed agent-based model of SARS-CoV-2 infection to estimate the where, when, and magnitude of transmission events during the pandemic’s first wave. We estimate that only 18% of individuals produce most infections (80%), with about 10% of events that can be considered superspreading events (SSEs). Although mass gatherings present an important risk for SSEs, we estimate that the bulk of transmission occurred in smaller events in settings like workplaces, grocery stores, or food venues. The places most important for transmission change during the pandemic and are different across cities, signaling the large underlying behavioral component underneath them. Our modeling complements case studies and epidemiological data and indicates that real-time tracking of transmission events could help evaluate and define targeted mitigation policies.
关键词：enCOVID-19mobilitylocationsuperspreading event