Efficient Bayesian inference of fully stochastic epidemiological models with applications to COVID-19

Epidemiological forecasts are beset by uncertainties about the underlying epidemiological processes, and the surveillance process through which data are acquired. We present a Bayesian inference methodology that quantifies these uncertainties, for epidemics that are modelled by (possibly) non-statio...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Yuting I., Turk, Günther, Rohrbach, Paul B., Pietzonka, Patrick, Kappler, Julian, Singh, Rajesh, Dolezal, Jakub, Ekeh, Timothy, Kikuchi, Lukas, Peterson, Joseph D., Bolitho, Austen, Kobayashi, Hideki, Cates, Michael E., Adhikari, R., Jack, Robert L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Mathematics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355677/
https://www.ncbi.nlm.nih.gov/pubmed/34430050
http://dx.doi.org/10.1098/rsos.211065

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355677/
https://www.ncbi.nlm.nih.gov/pubmed/34430050
http://dx.doi.org/10.1098/rsos.211065

Ejemplares similares