Tracking [Image: see text] of COVID-19: A new real-time estimation using the Kalman filter

We develop a new method for estimating the effective reproduction number of an infectious disease ([Image: see text] ) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, [Image: see text] is linearly related to the growth rate of the number of infe...

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Detalles Bibliográficos
Autores principales: Arroyo-Marioli, Francisco, Bullano, Francisco, Kucinskas, Simas, Rondón-Moreno, Carlos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806155/
https://www.ncbi.nlm.nih.gov/pubmed/33439880
http://dx.doi.org/10.1371/journal.pone.0244474
Descripción
Sumario:We develop a new method for estimating the effective reproduction number of an infectious disease ([Image: see text] ) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, [Image: see text] is linearly related to the growth rate of the number of infected individuals. This time-varying growth rate is estimated using the Kalman filter from data on new cases. The method is easy to implement in standard statistical software, and it performs well even when the number of infected individuals is imperfectly measured, or the infection does not follow the SIR model. Our estimates of [Image: see text] for COVID-19 for 124 countries across the world are provided in an interactive online dashboard, and they are used to assess the effectiveness of non-pharmaceutical interventions in a sample of 14 European countries.

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