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Quantifying the presymptomatic transmission of COVID-19 in the USA

  • Luyu Zhang
  • , Zhaohua Zhang
  • , Sen Pei
  • , Qing Gao
  • , Wei Chen*
  • *Corresponding author for this work
  • Beihang University
  • Columbia University
  • Zhongguancun Laboratory

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)861-883
Number of pages23
JournalMathematical Biosciences and Engineering
Volume21
Issue number1
DOIs
StatePublished - 2024

Keywords

  • covid-19
  • epidemiology
  • metapopulation model
  • nonlinear dynamics
  • presymptomatic transmission

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