JMIR Public Health and Surveillance (Mar 2023)

Dining-Out Behavior as a Proxy for the Superspreading Potential of SARS-CoV-2 Infections: Modeling Analysis

  • Ka Chun Chong,
  • Kehang Li,
  • Zihao Guo,
  • Katherine Min Jia,
  • Eman Yee Man Leung,
  • Shi Zhao,
  • Chi Tim Hung,
  • Carrie Ho Kwan Yam,
  • Tsz Yu Chow,
  • Dong Dong,
  • Huwen Wang,
  • Yuchen Wei,
  • Eng Kiong Yeoh

DOI
https://doi.org/10.2196/44251
Journal volume & issue
Vol. 9
p. e44251

Abstract

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BackgroundWhile many studies evaluated the reliability of digital mobility metrics as a proxy of SARS-CoV-2 transmission potential, none examined the relationship between dining-out behavior and the superspreading potential of COVID-19. ObjectiveWe employed the mobility proxy of dining out in eateries to examine this association in Hong Kong with COVID-19 outbreaks highly characterized by superspreading events. MethodsWe retrieved the illness onset date and contact-tracing history of all laboratory-confirmed cases of COVID-19 from February 16, 2020, to April 30, 2021. We estimated the time-varying reproduction number (Rt) and dispersion parameter (k), a measure of superspreading potential, and related them to the mobility proxy of dining out in eateries. We compared the relative contribution to the superspreading potential with other common proxies derived by Google LLC and Apple Inc. ResultsA total of 6391 clusters involving 8375 cases were used in the estimation. A high correlation between dining-out mobility and superspreading potential was observed. Compared to other mobility proxies derived by Google and Apple, the mobility of dining-out behavior explained the highest variability of k (ΔR-sq=9.7%, 95% credible interval: 5.7% to 13.2%) and Rt (ΔR-sq=15.7%, 95% credible interval: 13.6% to 17.7%). ConclusionsWe demonstrated that there was a strong link between dining-out behaviors and the superspreading potential of COVID-19. The methodological innovation suggests a further development using digital mobility proxies of dining-out patterns to generate early warnings of superspreading events.