Why is it difficult to accurately predict the COVID-19 epidemic?

Roda, Weston C; Varughese, Marie B; Han, Donglin; Li, Michael Y

Roda, Weston C; Varughese, Marie B; Han, Donglin; Li, Michael Y.

Afiliación

Roda WC; Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, T6G 2G1 Canada.
Varughese MB; Analytics and Performance Reporting Branch, Alberta Health, Edmonton, Alberta, T5J 2N3, Canada.
Han D; Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, T6G 2G1 Canada.
Li MY; Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, T6G 2G1 Canada.

Infect Dis Model ; 5: 271-281, 2020.

Article en En | MEDLINE | ID: mdl-32289100

Palabras clave

Bayesian inference; COVID-19 epidemic in Wuhan; Model selection; Nonidentifiability; Peak time of epidemic; Quarantine; SIR and SEIR models

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Infect Dis Model Año: 2020 Tipo del documento: Article Pais de publicación: China

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