Variability in transmission risk of SARS-CoV-2 in close contact settings: A contact tracing study in Shandong Province, China

Epidemics. 2022 Jun:39:100553. doi: 10.1016/j.epidem.2022.100553. Epub 2022 Mar 9.

Abstract

Background: Understanding the relative transmissibility of SARS-CoV-2 virus across different contact settings and the possibility of superspreading events is important for prioritizing disease control. Such assessment requires proper consideration of individual level exposure history, which is made possible by contact tracing.

Methods: The case-ascertained study in Shandong, China including 97 laboratory-confirmed index cases and 3158 close contacts. All close contacts were quarantined after their last exposure of index cases. Contacts were tested for COVID-19 regularly by PCR to identify both symptomatic and asymptomatic infections. We developed a Bayesian transmission model to the contact tracing data to account for different duration of exposure among individuals to transmission risk in different settings, and the heterogeneity of infectivity of cases.

Results: We estimate secondary attack rates (SAR) to be 39% (95% credible interval (CrI): 20-64%) in households, 30% (95% CrI: 11-67%) in healthcare facilities, 23% (95% CrI: 7-51%) at workplaces, and 4% (95% CrI: 1-17%) during air travel. Models allowing heterogeneity of infectivity of cases provided a better goodness-of-fit. We estimated that 64% (95% CrI: 55-72%) of cases did not generate secondary transmissions, and 20% (95% CrI: 15-26%) cases explained 80% of secondary transmissions.

Conclusions: Household, healthcare facilities and workplaces are efficient setting for transmission. Timely identification of potential superspreaders in most transmissible settings remains crucial for containing the pandemic.

Keywords: COVID-19; Close contact; Households; Superspreading; Transmission risk.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Bayes Theorem
  • COVID-19* / epidemiology
  • China / epidemiology
  • Contact Tracing
  • Humans
  • SARS-CoV-2*