A Bayesian Monte Carlo approach for predicting the spread of infectious diseases

In this paper, a simple yet interpretable, probabilistic model is proposed for the prediction of reported case counts of infectious diseases. A spatio-temporal kernel is derived from training data to capture the typical interaction effects of reported infections across time and space, which provides...

Descripción completa

Detalles Bibliográficos
Autores principales: Stojanović, Olivera, Leugering, Johannes, Pipa, Gordon, Ghozzi, Stéphane, Ullrich, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6919583/
https://www.ncbi.nlm.nih.gov/pubmed/31851680
http://dx.doi.org/10.1371/journal.pone.0225838

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6919583/
https://www.ncbi.nlm.nih.gov/pubmed/31851680
http://dx.doi.org/10.1371/journal.pone.0225838

Ejemplares similares