Quantifying the presymptomatic transmission of COVID-19 in the USA

Author:

Zhang Luyu1,Zhang Zhaohua1,Pei Sen2,Gao Qing34,Chen Wei456

Affiliation:

1. LMIB and School of Mathematical Sciences, Beihang University, Beijing 100191, China

2. Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA

3. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China

4. Zhongguancun Laboratory, Beijing 100194, China

5. Institute of Artificial Intelligence, Beihang University, Beijing 100191, China

6. Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China

Abstract

<abstract><p>The emergence of many presymptomatic hidden transmission events significantly complicated the intervention and control of the spread of COVID-19 in the USA during the year 2020. To analyze the role that presymptomatic infections play in the spread of this disease, we developed a state-level metapopulation model to simulate COVID-19 transmission in the USA in 2020 during which period the number of confirmed cases was more than in any other country. We estimated that the transmission rate (i.e., the number of new infections per unit time generated by an infected individual) of presymptomatic infections was approximately 59.9% the transmission rate of reported infections. We further estimated that {at any point in time the} average proportion of infected individuals in the presymptomatic stage was consistently over 50% of all infected individuals. Presymptomatic transmission was consistently contributing over 52% to daily new infections, as well as consistently contributing over 50% to the effective reproduction number from February to December. Finally, non-pharmaceutical intervention targeting presymptomatic infections was very effective in reducing the number of reported cases. These results reveal the significant contribution that presymptomatic transmission made to COVID-19 transmission in the USA during 2020, as well as pave the way for the design of effective disease control and mitigation strategies.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

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