Epidemiological and viral genomic sequence analysis of the 2014 ebola outbreak reveals clustered transmission. Academic Article

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.

authors

• Ndeffo, Martial

published proceedings

• Clin Infect Dis

altmetric score

• 100.4

author list (cited authors)

• Scarpino, S. V., Iamarino, A., Wells, C., Yamin, D., Ndeffo-Mbah, M., Wenzel, N. S., ... Townsend, J. P.

citation count

• 58

complete list of authors

• Scarpino, Samuel V||Iamarino, Atila||Wells, Chad||Yamin, Dan||Ndeffo-Mbah, Martial||Wenzel, Natasha S||Fox, Spencer J||Nyenswah, Tolbert||Altice, Frederick L||Galvani, Alison P||Meyers, Lauren Ancel||Townsend, Jeffrey P

publication date

• April 2015

publisher

• Oxford University Press (OUP)  Publisher

published in

• Clinical Infectious Diseases  Journal

keywords

• Cluster Analysis
• Clustering
• Disease Outbreaks
• Ebola
• Ebolavirus
• Epidemiology
• Genome Sequencing
• Genome, Viral
• Genotype
• Hemorrhagic Fever, Ebola
• Humans
• Sequence Analysis
• West Africa

PubMed Central ID

• 25516185

Digital Object Identifier (DOI)

• 10.1093/cid/ciu1131

start page

• 1079

end page

• 1082

volume

• 60

issue

• 7

URL

• http://dx.doi.org/10.1093/cid/ciu1131

user-defined tag

• 3 Good Health and Well-Being