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Characterizing key attributes of COVID-19 transmission dynamics in China's original outbreak: Model-based estimations

journal contribution
submitted on 2023-10-01, 06:43 and posted on 2023-10-15, 12:05 authored by Houssein H. Ayoub, Hiam Chemaitelly, Ghina R. Mumtaz, Shaheen Seedat, Susanne F. Awad, Monia Makhoul, Laith J. Abu-Raddad

A novel coronavirus strain, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in China. This study aims to characterize key attributes of SARS-CoV-2 epidemiology as the infection emerged in China. An age-stratified mathematical model was constructed to describe transmission dynamics and estimate age-specific differences in biological susceptibility to infection, age-assortativeness in transmission mixing, and transition in rate of infectious contacts (and reproduction number R0) following introduction of mass interventions. The model estimated the infectious contact rate in early epidemic at 0.59 contacts/day (95% uncertainty interval-UI = 0.48–0.71). Relative to those 60–69 years, susceptibility was 0.06 in those ≤19 years, 0.34 in 20–29 years, 0.57 in 30–39 years, 0.69 in 40–49 years, 0.79 in 50–59 years, 0.94 in 70–79 years, and 0.88 in ≥80 years. Assortativeness in transmission mixing by age was limited at 0.004 (95% UI = 0.002–0.008). R0 rapidly declined from 2.1 (95% UI = 1.8–2.4) to 0.06 (95% UI = 0.05–0.07) following interventions' onset. Age appears to be a principal factor in explaining the transmission patterns in China. The biological susceptibility to infection seems limited among children but high among those >50 years. There was no evidence for differential contact mixing by age.

Other Information

Published in: Global Epidemiology
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.gloepi.2020.100042

Funding

Open Access funding provided by the Qatar National Library

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2020

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Qatar University
  • College of Arts and Sciences - QU
  • Weill Cornell Medicine - Qatar

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