Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas

被引：47

作者：

Aleta, Alberto ^{[1
]}

Martin-Corral, David ^{[2
,3
,4
]}

Bakker, Michiel A. ^{[5
]}

Piontti, Ana Pastore Y. ^{[6
]}

Ajelli, Marco ^{[6
,7
]}

Litvinova, Maria ^{[7
]}

Chinazzi, Matteo ^{[6
]}

Dean, Natalie E. ^{[8
]}

Halloran, M. Elizabeth ^{[9
,10
]}

Longini Jr, Ira M. ^{[8
]}

Pentland, Alex ^{[5
]}

Vespignani, Alessandro ^{[1
,6
]}

Moreno, Yamir ^{[1
,11
,12
]}

Moro, Esteban ^{[2
,3
,5
]}

机构：

[1] ISI Fdn, I-10126 Turin, Italy

[2] Univ Carlos III Madrid, Dept Matemat, Leganes 28911, Spain

[3] Univ Carlos III Madrid, Grp Interdisciplinar Sistemas Complejos, Leganes 28911, Spain

[4] Zensei Technol SL, Madrid 28010, Spain

[5] MIT, Inst Data Sci & Soc, Connect Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA

[6] Northeastern Univ, Lab Modeling Biol & Sociotech Syst, Boston, MA 02115 USA

[7] Indiana Univ, Dept Epidemiol & Biostat, Lab Computat Epidemiol & Publ Hlth, Sch Publ Hlth, Bloomington, IN 47405 USA

[8] Univ Florida, Coll Publ Hlth & Hlth Profess, Dept Biostat, Gainesville, FL 32611 USA

[9] Fred Hutchinson Canc Res Ctr, Vaccine & Infect Dis Div, Biostat Bioinformat & Epidemiol Program, Seattle, WA 98109 USA

[10] Univ Washington, Dept Biostat, Seattle, WA 98195 USA

[11] Univ Zaragoza, Inst Biocomputat & Phys Complex Syst, Zaragoza 50018, Spain

[12] Univ Zaragoza, Fac Sci, Dept Theoret Phys, Zaragoza 50009, Spain

来源：

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | 2022年 / 119卷 / 26期

关键词：

COVID-19; mobility; location; superspreading event; COVID-19;

D O I：

10.1073/pnas.2112182119

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页数：8

共 32 条

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