Your browser doesn't support javascript.
Accounting for Imported Cases in Estimating the Time-Varying Reproductive Number of Coronavirus Disease 2019 in Hong Kong.
Tsang, Tim K; Wu, Peng; Lau, Eric H Y; Cowling, Benjamin J.
  • Tsang TK; World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Wu P; Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China.
  • Lau EHY; World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Cowling BJ; Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, China.
J Infect Dis ; 224(5): 783-787, 2021 09 01.
Article in English | MEDLINE | ID: covidwho-1393268
ABSTRACT
Estimating the time-varying reproductive number, Rt, is critical for monitoring transmissibility of an infectious disease. The impact of imported cases on the estimation is rarely explored. We developed a model to estimate separately the Rt for local cases and imported cases, accounting for imperfect contact tracing of cases. We applied this framework to data on coronavirus disease 2019 outbreaks in Hong Kong. The estimated Rt for local cases rose above 1 in late March 2020, which was undetected by other commonly used methods. When imported cases account for a considerable proportion of all cases, their impact on estimating Rt is critical.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: J Infect Dis Year: 2021 Document Type: Article Affiliation country: Infdis

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: J Infect Dis Year: 2021 Document Type: Article Affiliation country: Infdis