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Webinar: Biostatistics seminar – “Reconstruction of the Full Transmission Dynamics of COVID-19 in Wuhan”
September 16, 9:00 am to 10:00 am
“Reconstruction of the Full Transmission Dynamics of COVID-19 in Wuhan” will be presented by Chaolong Wang, PhD, Professor, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology.
As countries in the world review interventions for containing the pandemic of COVID-19, important lessons can be drawn from the study of the full transmission dynamics of its causative agent, SARS-CoV-2, in Wuhan (China), where vigorous non-pharmaceutical interventions have suppressed the local outbreak of this disease. Here, the investigators use a modelling approach to reconstruct the full-spectrum dynamics of COVID-19 in Wuhan between Jan. 1 and March 8, 2020, across five periods defined by events and interventions, based on 32,583 laboratory-confirmed cases.
Accounting for presymptomatic infectiousness, time-varying ascertainment rates, transmission rates and population movements, the project identifies two key features of the outbreak: high covertness and high transmissibility. The team estimates 87% (lower bound, 53%) of the infections before March 8, 2020 were unascertained (potentially including asymptomatic and mildly symptomatic individuals); and a basic reproduction number (R0) of 3.54 (95% credible interval 3.40 to 3.67) in the early outbreak, much higher than that of SARS and MERS.
The study sobserve that multipronged interventions had considerable positive effects on controlling the outbreak, decreasing the reproduction number to 0.28 (95% credible interval 0.23 to 0.33) and by projection reducing the total infections in Wuhan by 96.0% as of March 8, 2020. The project also explores the probability of resurgence following the lifting of all interventions after 14 consecutive days of no ascertained infections and estimates this probability at 0.32 and 0.06 based on models with 87% and 53% unascertained cases, respectively – highlighting the risk posed by substantial covert infections when changing control measures. These results have important implications when considering strategies of continuing surveillance and interventions to eventually contain outbreaks of COVID-19.
Participants may also join by calling 929-205-6099, meeting ID 322 043 373. If prompted, use passcode 167660.