An ensemble n-sub-epidemic modeling framework for short-term forecasting epidemic trajectories: Application to the COVID-19 pandemic in the USA.

Chowell, Gerardo; Dahal, Sushma; Tariq, Amna; Roosa, Kimberlyn; Hyman, James M; Luo, Ruiyan

Chowell, Gerardo; Dahal, Sushma; Tariq, Amna; Roosa, Kimberlyn; Hyman, James M; Luo, Ruiyan.

Afiliação

Chowell G; Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.
Dahal S; Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.
Tariq A; Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.
Roosa K; Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.
Hyman JM; National Institute for Mathematical and Biological Synthesis (NIMBioS), University of Tennessee, Knoxville, Tennessee, United States of America.
Luo R; Department of Mathematics, Center for Computational Science, Tulane University, New Orleans, Louisiana, United States of America.

PLoS Comput Biol ; 18(10): e1010602, 2022 10.

Article em En | MEDLINE | ID: mdl-36201534

Assuntos

COVID-19; Humanos; Estados Unidos/epidemiologia; COVID-19/epidemiologia; Pandemias; Previsões; Modelos Estatísticos; Tempo

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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