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Insights into COVID-19 epidemiology and control from temporal changes in serial interval distributions in Hong Kong
Sheikh Taslim Ali; Dongxuan Chen; Wey Wen Lim; Amy Yeung; Dillon C. Adam; Yiu Chung Lau; Eric H. Y. Lau; Jessica Y. Wong; Jingyi Xiao; Faith Ho; Huizhi Gao; Lin Wang; Xiao-Ke Xu; Zhanwei Du; Peng Wu; Gabriel M. Leung; Benjamin J. Cowling.
Afiliación
  • Sheikh Taslim Ali; The University of Hong Kong
  • Dongxuan Chen; The University of Hong Kong
  • Wey Wen Lim; The University of Hong Kong
  • Amy Yeung; The University of Hong Kong
  • Dillon C. Adam; The University of Hong Kong
  • Yiu Chung Lau; The University of Hong Kong
  • Eric H. Y. Lau; The University of Hong Kong
  • Jessica Y. Wong; The University of Hong Kong
  • Jingyi Xiao; The University of Hong Kong
  • Faith Ho; The University of Hong Kong
  • Huizhi Gao; The University of Hong Kong
  • Lin Wang; The University of Cambridge
  • Xiao-Ke Xu; Dalian Minzu University
  • Zhanwei Du; The University of Hong Kong
  • Peng Wu; The University of Hong Kong
  • Gabriel M. Leung; The University of Hong Kong
  • Benjamin J. Cowling; The University of Hong Kong
Preprint en En | PREPRINT-MEDRXIV | ID: ppmedrxiv-22279351
ABSTRACT
The serial interval distribution is used to approximate the generation time distribution, an essential parameter to predict the effective reproductive number "Rt", a measure of transmissibility. However, serial interval distributions may change as an epidemic progresses rather than remaining constant. Here we show that serial intervals in Hong Kong varied over time, closely associated with the temporal variation in COVID-19 case profiles and public health and social measures that were implemented in response to surges in community transmission. Quantification of the variation over time in serial intervals led to improved estimation of Rt, and provided additional insights into the impact of public health measures on transmission of infections. One-Sentence SummaryReal-time estimates of serial interval distributions can improve assessment of COVID-19 transmission dynamics and control.
Licencia
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Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Observational_studies / Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Preprint
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Observational_studies / Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Preprint