Bayesian Spatio-Temporal Prediction and Counterfactual Generation: An Application in Non-Pharmaceutical Interventions in COVID-19

The spatio-temporal course of an epidemic (such as COVID-19) can be significantly affected by non-pharmaceutical interventions (NPIs) such as full or partial lockdowns. Bayesian Susceptible-Infected-Removed (SIR) models can be applied to the spatio-temporal spread of infectious diseases (STIFs) (suc...

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Detalles Bibliográficos
Autores principales: Lawson, Andrew, Rotejanaprasert, Chawarat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9965276/
https://www.ncbi.nlm.nih.gov/pubmed/36851538
http://dx.doi.org/10.3390/v15020325

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9965276/
https://www.ncbi.nlm.nih.gov/pubmed/36851538
http://dx.doi.org/10.3390/v15020325

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