Vaccine models predict rules for updating vaccines against evolving pathogens such as SARS-CoV-2 and influenza in the context of pre-existing immunity.

Desikan, Rajat; Linderman, Susanne L; Davis, Carl; Zarnitsyna, Veronika I; Ahmed, Hasan; Antia, Rustom

Desikan, Rajat; Linderman, Susanne L; Davis, Carl; Zarnitsyna, Veronika I; Ahmed, Hasan; Antia, Rustom.

Afiliação

Desikan R; Clinical Pharmacology Modeling & Simulation, GlaxoSmithKline (GSK), Stevenage, Hertfordshire, United Kingdom.
Linderman SL; Department of Microbiology and Immunology, Emory University, Atlanta, GA, United States.
Davis C; Department of Microbiology and Immunology, Emory University, Atlanta, GA, United States.
Zarnitsyna VI; Department of Microbiology and Immunology, Emory University, Atlanta, GA, United States.
Ahmed H; Department of Biology, Emory University, Atlanta, GA, United States.
Antia R; Department of Biology, Emory University, Atlanta, GA, United States.

Front Immunol ; 13: 985478, 2022.

Article em En | MEDLINE | ID: mdl-36263031

Assuntos

COVID-19; Virus da Influenza A Subtipo H5N1; Vacinas contra Influenza; Influenza Humana; Humanos; SARS-CoV-2; Vacinas contra COVID-19; Influenza Humana/prevenção & controle; COVID-19/prevenção & controle

Palavras-chave

COVID-19; SARS-CoV-2; Vaccine; modeling; omicron; simulations; variants

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vacinas contra Influenza / Influenza Humana / Virus da Influenza A Subtipo H5N1 / COVID-19 Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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