Parameterizing Spatial Models of Infectious Disease Transmission that Incorporate Infection Time Uncertainty Using Sampling-Based Likelihood Approximations

A class of discrete-time models of infectious disease spread, referred to as individual-level models (ILMs), are typically fitted in a Bayesian Markov chain Monte Carlo (MCMC) framework. These models quantify probabilistic outcomes regarding the risk of infection of susceptible individuals due to va...

Descripción completa

Detalles Bibliográficos
Autores principales: Malik, Rajat, Deardon, Rob, Kwong, Grace P. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4701410/
https://www.ncbi.nlm.nih.gov/pubmed/26731666
http://dx.doi.org/10.1371/journal.pone.0146253

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4701410/
https://www.ncbi.nlm.nih.gov/pubmed/26731666
http://dx.doi.org/10.1371/journal.pone.0146253

Ejemplares similares