Modelling COVID-19 in the North American region with a metapopulation network and Kalman filter

Background: Understanding the dynamics of infectious disease spread and predicting clinical outcomes are critical for managing large-scale epidemics and pandemics, such as COVID-19. Effective modeling of disease transmission in interconnected populations helps inform public health responses and inte...

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Autori principali:	Matteo Perini, Teresa K. Yamana, Marta Galanti, Jiyeon Suh, Roselyn Kaondera-Shava, Jeffrey Shaman
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2025-03-01
Serie:	Epidemics
Soggetti:	COVID-19 Metapopulation model North America Transmission dynamics Bayesian inference
Accesso online:	http://www.sciencedirect.com/science/article/pii/S1755436525000064
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