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Modeling the positive testing rate of COVID-19 in South Africa using a semi-parametric smoother for binomial data.
Owokotomo, Olajumoke Evangelina; Manda, Samuel; Cleasen, Jürgen; Kasim, Adetayo; Sengupta, Rudradev; Shome, Rahul; Subhra Paria, Soumya; Reddy, Tarylee; Shkedy, Ziv.
Afiliación
  • Owokotomo OE; Center for Statistics, Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium.
  • Manda S; Department of Statistics, University of Pretoria, Pretoria, South Africa.
  • Cleasen J; Center for Statistics, Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium.
  • Kasim A; Department of Anthropology, Durham Research Methods Centre, Durham University, Durham, United Kingdom.
  • Sengupta R; The Janssen Pharmaceutical, Companies of Johnson & Johnson, Beerse, Belgium.
  • Shome R; Department of Computer Science, Rice University, Houston, TX, United States.
  • Subhra Paria S; School of Mathematics and Statistics, The Open University, Milton Keynes, United Kingdom.
  • Reddy T; Biostatistics Research Unit, South African Medical Research Council, Capetown, South Africa.
  • Shkedy Z; Center for Statistics, Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium.
Front Public Health ; 11: 979230, 2023.
Article en En | MEDLINE | ID: mdl-36908419
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans País/Región como asunto: Africa Idioma: En Revista: Front Public Health Año: 2023 Tipo del documento: Article País de afiliación: Bélgica Pais de publicación: Suiza
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans País/Región como asunto: Africa Idioma: En Revista: Front Public Health Año: 2023 Tipo del documento: Article País de afiliación: Bélgica Pais de publicación: Suiza