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Tracking and predicting the African COVID-19 pandemic.
Ssentongo, Paddy; Fronterre, Claudio; Geronimo, Andrew; Greybush, Steven J; Mbabazi, Pamela K; Muvawala, Joseph; Nahalamba, Sarah B; Omadi, Philip O; Opar, Bernard T; Sinnar, Shamim A; Wang, Yan; Whalen, Andrew J; Held, Leonhard; Jewell, Chris; Muwanguzi, Abraham J B; Greatrex, Helen; Norton, Michael M; Diggle, Peter; Schiff, Steven J.
Afiliación
  • Ssentongo P; Center for Neural Engineering, Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA United States of America.
  • Fronterre C; Department of Public Health Sciences, The Pennsylvania State University College of Medicine, Hershey, PA, United States of America.
  • Geronimo A; Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom.
  • Greybush SJ; Department of Neurosurgery, The Pennsylvania State University College of Medicine, Hershey, PA, United States of America.
  • Mbabazi PK; Department of Meteorology and Atmospheric Science, and Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA, United States of America.
  • Muvawala J; National Planning Authority, Kampala, Uganda.
  • Nahalamba SB; National Planning Authority, Kampala, Uganda.
  • Omadi PO; National Planning Authority, Kampala, Uganda.
  • Opar BT; National Planning Authority, Kampala, Uganda.
  • Sinnar SA; Ministry of Health, Kampala, Uganda.
  • Wang Y; Center for Neural Engineering, Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA United States of America.
  • Whalen AJ; Department of Meteorology and Atmospheric Science, and Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA, United States of America.
  • Held L; Center for Neural Engineering, Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA United States of America.
  • Jewell C; Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA United States of America.
  • Muwanguzi AJB; Epidemiology, Biostatistics and Prevention Institute (EBPI) University of Zurich, Zurich, Switzerland.
  • Greatrex H; Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, United Kingdom.
  • Norton MM; National Planning Authority, Kampala, Uganda.
  • Diggle P; Department of Geography, Department of Statistics, and Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA United States of America.
  • Schiff SJ; Center for Neural Engineering, Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA United States of America.
medRxiv ; 2020 Nov 16.
Article en En | MEDLINE | ID: mdl-33236036
The ongoing coronavirus disease 2019 (COVID-19) pandemic is heterogeneous throughout Africa and threatening millions of lives. Surveillance and short-term modeling forecasts are critical to provide timely information for decisions on control strategies. We use a model that explains the evolution of the COVID-19 pandemic over time in the entire African continent, parameterized by socioeconomic and geoeconomic variations and the lagged effects of social policy and meteorological history. We observed the effect of the human development index, containment policies, testing capacity, specific humidity, temperature and landlocked status of countries on the local within-country and external between-country transmission. One week forecasts of case numbers from the model were driven by the quality of the reported data. Seeking equitable behavioral and social interventions, balanced with coordinated country-specific strategies in infection suppression, should be a continental priority to control the COVID-19 pandemic in Africa.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: MedRxiv Año: 2020 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: MedRxiv Año: 2020 Tipo del documento: Article