Efficient Real-Time Monitoring of an Emerging Influenza Pandemic: How Feasible?

Birrell, Paul J; Wernisch, Lorenz; Tom, Brian D M; Held, Leonhard; Roberts, Gareth O; Pebody, Richard G; De Angelis, Daniela

Birrell, Paul J; Wernisch, Lorenz; Tom, Brian D M; Held, Leonhard; Roberts, Gareth O; Pebody, Richard G; De Angelis, Daniela.

Afiliação

Birrell PJ; MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge.
Wernisch L; MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge.
Tom BDM; MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge.
Held L; Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich.
Roberts GO; CRiSM, Department of Statistics, University of Warwick.
Pebody RG; Health Protection Directorate, Public Health England.
De Angelis D; MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge.

Ann Appl Stat ; 14(1): 74-93, 2020 Mar.

Article em En | MEDLINE | ID: mdl-34992706

Palavras-chave

SEIR transmission model; Sequential Monte Carlo; pandemic influenza; real-time inference; resample-move

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Ann Appl Stat Ano de publicação: 2020 Tipo de documento: Article

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