Characterization of partially observed epidemics through Bayesian inference: application to COVID-19

We demonstrate a Bayesian method for the “real-time” characterization and forecasting of partially observed COVID-19 epidemic. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The method is designed to help guide medical resource allocatio...

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Detalles Bibliográficos
Autores principales: Safta, Cosmin, Ray, Jaideep, Sargsyan, Khachik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538372/
https://www.ncbi.nlm.nih.gov/pubmed/33041410
http://dx.doi.org/10.1007/s00466-020-01897-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538372/
https://www.ncbi.nlm.nih.gov/pubmed/33041410
http://dx.doi.org/10.1007/s00466-020-01897-z

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