Sequential Monte Carlo Filtering Estimation of Ebola Progression in West Africa
Applications
2016-01-29 v1 Populations and Evolution
Abstract
We use a multivariate formulation of sequential Monte Carlo filter that utilizes mechanistic models for Ebola virus propagation and available incidence data to simultaneously estimate the disease progression states and the model parameters. This method has the advantage of performing the inference online as the new data becomes available and estimates the evolution of basic reproductive ratio of the Ebola outbreak through time. Our analysis identifies a peak in the basic reproductive ratio close to the time when Ebola cases were reported in Europe and the USA.
Keywords
Cite
@article{arxiv.1601.07606,
title = {Sequential Monte Carlo Filtering Estimation of Ebola Progression in West Africa},
author = {Narges Montazeri Shahtori and Caterina Scoglio and Arash Pourhabib and Faryad Darabi Sahneh},
journal= {arXiv preprint arXiv:1601.07606},
year = {2016}
}
Comments
6 pages, 3 figures