Cargando…
Analysis of the COVID-19 pandemic using a compartmental model with time-varying parameters fitted by a genetic algorithm
Analyzing the COVID-19 pandemic is a critical factor in developing effective policies to deal with similar challenges in the future. However, many parameters (e.g., the actual number of infected people, the effectiveness of vaccination) are still subject to considerable debate because they are unobs...
Autores principales: | Zelenkov, Yuri, Reshettsov, Ivan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072952/ https://www.ncbi.nlm.nih.gov/pubmed/37033691 http://dx.doi.org/10.1016/j.eswa.2023.120034 |
Ejemplares similares
-
An Estimation Algorithm for General Linear Single Particle Tracking Models with Time-Varying Parameters
por: Godoy, Boris I., et al.
Publicado: (2021) -
Using a genetic algorithm to fit parameters of a COVID-19 SEIR model for US states
por: Yarsky, P.
Publicado: (2021) -
NC-COVID: A Time-Varying Compartmental Model for Estimating SARS-CoV-2 Infection Dynamics in North Carolina, US
por: Delamater, Paul L., et al.
Publicado: (2022) -
Estimation of parameters for a humidity-dependent compartmental model of the COVID-19 outbreak
por: Farkas, Csaba, et al.
Publicado: (2021) -
A fractional-order compartmental model for the spread of the COVID-19 pandemic
por: Biala, T.A., et al.
Publicado: (2021)