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The CP‐ABM approach for modelling COVID‐19 infection dynamics and quantifying the effects of non‐pharmaceutical interventions

The motivation for this research is to develop an approach that reliably captures the disease dynamics of COVID-19 for an entire population in order to identify the key events driving change in the epidemic through accurate estimation of daily COVID-19 cases. This has been achieved through the new C...

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Detalles Bibliográficos
Autores principales: Novakovic, Aleksandar, Marshall, Adele H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107333/
https://www.ncbi.nlm.nih.gov/pubmed/35601479
http://dx.doi.org/10.1016/j.patcog.2022.108790
Descripción
Sumario:The motivation for this research is to develop an approach that reliably captures the disease dynamics of COVID-19 for an entire population in order to identify the key events driving change in the epidemic through accurate estimation of daily COVID-19 cases. This has been achieved through the new CP-ABM approach which uniquely incorporates Change Point detection into an Agent Based Model taking advantage of genetic algorithms for calibration and an efficient infection centric procedure for computational efficiency. The CP-ABM is applied to the Northern Ireland population where it successfully captures patterns in COVID-19 infection dynamics over both waves of the pandemic and quantifies the significant effects of non-pharmaceutical interventions (NPI) on a national level for lockdowns and mask wearing. To our knowledge, there is no other approach to date that has captured NPI effectiveness and infection spreading dynamics for both waves of the COVID-19 pandemic for an entire country population.