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Modeling the Impact of Vaccination on COVID-19 and Its Delta and Omicron Variants.
Wang, Jianbo; Chan, Yin-Chi; Niu, Ruiwu; Wong, Eric W M; van Wyk, Michaël Antonie.
Afiliación
  • Wang J; Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China.
  • Chan YC; School of Computer Science, Southwest Petroleum University, Chengdu 610500, China.
  • Niu R; Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China.
  • Wong EWM; Institute for Manufacturing, University of Cambridge, Cambridge CB3 0FS, UK.
  • van Wyk MA; College of Mathematics and Statistics, Shenzhen University, Shenzhen 518060, China.
Viruses ; 14(7)2022 07 06.
Article en En | MEDLINE | ID: mdl-35891462
Vaccination is an important means to fight against the spread of the SARS-CoV-2 virus and its variants. In this work, we propose a general susceptible-vaccinated-exposed-infected-hospitalized-removed (SVEIHR) model and derive its basic and effective reproduction numbers. We set Hong Kong as an example and calculate conditions of herd immunity for multiple vaccines and disease variants. The model shows how the number of confirmed COVID-19 cases in Hong Kong during the second and third waves of the COVID-19 pandemic would have been reduced if vaccination were available then. We then investigate the relationships between various model parameters and the cumulative number of hospitalized COVID-19 cases in Hong Kong for the ancestral, Delta, and Omicron strains. Numerical results demonstrate that the static herd immunity threshold corresponds to one percent of the population requiring hospitalization or isolation at some point in time. We also demonstrate that when the vaccination rate is high, the initial proportion of vaccinated individuals can be lowered while still maintaining the same proportion of cumulative hospitalized/isolated individuals.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans Idioma: En Revista: Viruses Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans Idioma: En Revista: Viruses Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza