| Literature DB >> 25516185 |
Samuel V Scarpino1, Atila Iamarino2, Chad Wells3, Dan Yamin3, Martial Ndeffo-Mbah3, Natasha S Wenzel4, Spencer J Fox5, Tolbert Nyenswah6, Frederick L Altice7, Alison P Galvani8, Lauren Ancel Meyers9, Jeffrey P Townsend10.
Abstract
Using Ebolavirus genomic and epidemiological data, we conducted the first joint analysis in which both data types were used to fit dynamic transmission models for an ongoing outbreak. Our results indicate that transmission is clustered, highlighting a potential bias in medical demand forecasts, and provide the first empirical estimate of underreporting.Entities:
Keywords: Ebola; West Africa; clustering; epidemiology; genome sequencing
Mesh:
Year: 2014 PMID: 25516185 PMCID: PMC4375398 DOI: 10.1093/cid/ciu1131
Source DB: PubMed Journal: Clin Infect Dis ISSN: 1058-4838 Impact factor: 9.079