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Estimating the time-varying reproduction number for COVID-19 in South Africa during the first four waves using multiple measures of incidence for public and private sectors across four waves
Jeremy Bingham; Stefano Tempia; Harry Moultrie; Cecile Viboud; Waasila Jassat; Cheryl Cohen; Juliet R.C. Pulliam.
Afiliação
  • Jeremy Bingham; Stellenbosch University
  • Stefano Tempia; National Institute for Communicable Diseases
  • Harry Moultrie; National Institute for Communicable Diseases
  • Cecile Viboud; NIH
  • Waasila Jassat; National Institute for Communicable Diseases
  • Cheryl Cohen; National Insitute for Communicable Diseases
  • Juliet R.C. Pulliam; Stellenbosch University
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22277932
ABSTRACT
ObjectivesWe aimed to quantify transmission trends in South Africa during the first four waves of the COVID-19 pandemic using estimates of the time-varying reproduction number (R) and to compare the robustness of R estimates based on three different data sources and using data from public and private sector service providers. MethodsWe estimated R from March 2020 through April 2022, nationally and by province, based on time series of rt-PCR-confirmed cases, hospitalizations, and hospital-associated deaths, using a method which models daily incidence as a weighted sum of past incidence. We also estimated R separately using public and private sector data. ResultsNationally, the maximum case-based R following the introduction of lockdown measures was 1.55 (CI 1.43-1.66), 1.56 (CI 1.47-1.64), 1.46 (CI 1.38-1.53) and 3.33 (CI 2.84-3.97) during the first (Wuhan-Hu), second (Beta), third (Delta), and fourth (Omicron) waves respectively. Estimates based on the three data sources (cases, hospitalisations, deaths) were generally similar during the first three waves but case-based estimates were higher during the fourth wave. Public and private sector R estimates were generally similar except during the initial lockdowns and in case-based estimates during the fourth wave. DiscussionAgreement between R estimates using different data sources during the first three waves suggests that data from any of these sources could be used in the early stages of a future pandemic. High R estimates for Omicron relative to earlier waves is interesting given a high level of exposure pre-Omicron. The agreement between public and private sector R estimates highlights the fact that clients of the public and private sectors did not experience two separate epidemics, except perhaps to a limited extent during the strictest lockdowns in the first wave.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo observacional Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo observacional Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
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