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Network models to evaluate vaccine strategies towards herd immunity in COVID-19.
Tetteh, Josephine N A; Nguyen, Van Kinh; Hernandez-Vargas, Esteban A.
Afiliação
  • Tetteh JNA; Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany; Institut für Mathematik, Goethe-Universität, Frankfurt am Main, Germany.
  • Nguyen VK; Imperial College London, London, United Kingdom.
  • Hernandez-Vargas EA; Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany; Instituto de Matemáticas, Universidad Nacional Autonoma de Mexico, Boulevard Juriquilla 3001, Santiago de Querétaro, Qro. 76230, Mexico. Electronic address: esteban@im.unam.mx.
J Theor Biol ; 531: 110894, 2021 12 21.
Article em En | MEDLINE | ID: mdl-34508758
Vaccination remains a critical element in the eventual solution to the COVID-19 public health crisis. Many vaccines are already being mass produced and supplied in many countries. However, the COVID-19 vaccination programme will be the biggest in history. Reaching herd immunity will require an unprecedented mass immunisation campaign that will take several months and millions of dollars. Using different network models, COVID-19 pandemic dynamics of different countries can be recapitulated such as in Italy. Stochastic computational simulations highlight that peak epidemic sizes in a population strongly depend on the network structure. Assuming a vaccine efficacy of at least 80% in a mass vaccination program, at least 70% of a given population should be vaccinated to obtain herd immunity, independently of the network structure. If the vaccine efficacy reports lower levels of efficacy in practice, then the coverage of vaccination would be needed to be even higher. Simulations suggest that the "Ring of Vaccination" strategy, vaccinating susceptible contact and contact of contacts, would prevent new waves of COVID -19 meanwhile a high percent of the population is vaccinated.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Vacinas / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: J Theor Biol Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Alemanha País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Vacinas / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: J Theor Biol Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Alemanha País de publicação: Reino Unido