A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2.

Hill, Edward M; Atkins, Benjamin D; Keeling, Matt J; Dyson, Louise; Tildesley, Michael J

Hill, Edward M; Atkins, Benjamin D; Keeling, Matt J; Dyson, Louise; Tildesley, Michael J.

Afiliação

Hill EM; The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom.
Atkins BD; Joint UNIversities Pandemic and Epidemiological Research, https://maths.org/juniper/.
Keeling MJ; The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom.
Dyson L; Joint UNIversities Pandemic and Epidemiological Research, https://maths.org/juniper/.
Tildesley MJ; The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom.

PLoS Comput Biol ; 17(6): e1009058, 2021 06.

Article em En | MEDLINE | ID: mdl-34133427

Assuntos

COVID-19/prevenção & controle; Busca de Comunicante; Modelos Biológicos; Local de Trabalho; COVID-19/epidemiologia; COVID-19/transmissão; Fidelidade a Diretrizes/estatística & dados numéricos; Humanos; Pandemias; Saúde Pública; SARS-CoV-2; Trabalho/estatística & dados numéricos

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Busca de Comunicante / Local de Trabalho / COVID-19 / Modelos Biológicos Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google