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Pharmaceutical and non-pharmaceutical interventions for controlling the COVID-19 pandemic.
Molla, Jeta; Farhang-Sardroodi, Suzan; Moyles, Iain R; Heffernan, Jane M.
Afiliação
  • Molla J; Department of Mathematics and Statistics, York University, Toronto, Ontario, Canada.
  • Farhang-Sardroodi S; Centre for Disease Modelling (CDM), Mathematics Statistics, York University, Toronto, Ontario, Canada.
  • Moyles IR; Modelling Infection and Immunity Lab, Mathematics Statistics, York University, Toronto, Ontario, Canada.
  • Heffernan JM; Centre for Disease Modelling (CDM), Mathematics Statistics, York University, Toronto, Ontario, Canada.
R Soc Open Sci ; 10(12): 230621, 2023 Dec.
Article em En | MEDLINE | ID: mdl-38126062
ABSTRACT
Disease spread can be affected by pharmaceutical interventions (such as vaccination) and non-pharmaceutical interventions (such as physical distancing, mask-wearing and contact tracing). Understanding the relationship between disease dynamics and human behaviour is a significant factor to controlling infections. In this work, we propose a compartmental epidemiological model for studying how the infection dynamics of COVID-19 evolves for people with different levels of social distancing, natural immunity and vaccine-induced immunity. Our model recreates the transmission dynamics of COVID-19 in Ontario up to December 2021. Our results indicate that people change their behaviour based on the disease dynamics and mitigation measures. Specifically, they adopt more protective behaviour when mandated social distancing measures are in effect, typically concurrent with a high number of infections. They reduce protective behaviour when vaccination coverage is high or when mandated contact reduction measures are relaxed, typically concurrent with a reduction of infections. We demonstrate that waning of infection and vaccine-induced immunity are important for reproducing disease transmission in autumn 2021.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article