A simple, SIR-like but individual-based epidemic model: Application in comparison of COVID-19 in New York City and Wuhan

In this study, an individual-based epidemic model, considering latent-infectious-recovery periods, is presented. The analytic solution of the model in the form of recursive formulae with a time-dependent transmission coefficient is derived and implanted in Excel. The simulated epidemic curves from t...

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Detalles Bibliográficos
Autor principal: Liu, Xiaoping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759094/
https://www.ncbi.nlm.nih.gov/pubmed/33391987
http://dx.doi.org/10.1016/j.rinp.2020.103712
Descripción
Sumario:In this study, an individual-based epidemic model, considering latent-infectious-recovery periods, is presented. The analytic solution of the model in the form of recursive formulae with a time-dependent transmission coefficient is derived and implanted in Excel. The simulated epidemic curves from the model fit very well with the daily reported cases of COVID-19 in Wuhan, China and New York City (NYC), USA. These simulations show that the transmission rate of NYC’s COVID-19 is nearly 30% greater than the transmission rate of Wuhan’s COVID-19, and that the actual number of cumulative infected people in NYC is around 9 times the reported number of cumulative COVID-19 cases in NYC. Results from this study also provide important information about latent period, infectious period and lockdown efficiency.

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