Epidemiological and viral genomic sequence analysis of the 2014 Ebola outbreak reveals clustered transmission

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

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.

Original languageEnglish
Pages (from-to)1079-1082
Number of pages4
JournalClinical Infectious Diseases
Volume60
Issue number7
DOIs
StatePublished - 1 Apr 2015
Externally publishedYes

Funding

FundersFunder number
Fundacao de Amparo a Pesquisa de Sao Paulo13/15144-8
National Science Foundation1514673
National Science Foundation
National Institutes of Health5 U01 GM105627, U01GM087719, K24 DA017072
National Institutes of Health
National Center for Advancing Translational SciencesUL1TR000142
National Center for Advancing Translational Sciences
Santa Fe Institute
Notsew Orm Sands Foundation

    Keywords

    • Ebola
    • West Africa
    • clustering
    • epidemiology
    • genome sequencing

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