Parameter identifiability and optimal control of an SARS-CoV-2 model early in the pandemic.

Tuncer, Necibe; Timsina, Archana; Nuno, Miriam; Chowell, Gerardo; Martcheva, Maia

Tuncer, Necibe; Timsina, Archana; Nuno, Miriam; Chowell, Gerardo; Martcheva, Maia.

Afiliación

Tuncer N; Department of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL, USA.
Timsina A; Department of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL, USA.
Nuno M; Department of Biostatistics, University of California, Davis, CA, USA.
Chowell G; Department of Population Health Sciences, Georgia State University, Atlanta, GA, USA.
Martcheva M; Department of Mathematics, University of Florida, Gainesville, FL, USA.

J Biol Dyn ; 16(1): 412-438, 2022 12.

Article en En | MEDLINE | ID: mdl-35635313

Asunto(s)

COVID-19; SARS-CoV-2; COVID-19/epidemiología; Humanos; Modelos Biológicos; Método de Montecarlo; Pandemias/prevención & control

Palabras clave

Coronavirus disease 2019 (COVID-19); Practical and structural identifiability; Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2); asymptomatic transmission; basic reproductive number; epidemic model; isolation; mass-action incidence; outbreak

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: SARS-CoV-2 / COVID-19 Tipo de estudio: Health_economic_evaluation / Prognostic_studies Límite: Humans Idioma: En Revista: J Biol Dyn Asunto de la revista: BIOLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

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