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

doi:10.1093/cid/ciu1131

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

Research output: Contribution to journal › Article › peer-review

41 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 language	English (US)
Pages (from-to)	1079-1082
Number of pages	4
Journal	Clinical Infectious Diseases
Volume	60
Issue number	7
DOIs	https://doi.org/10.1093/cid/ciu1131
State	Published - Apr 1 2015
Externally published	Yes

Keywords

Ebola
West Africa
clustering
epidemiology
genome sequencing

ASJC Scopus subject areas

Microbiology (medical)
Infectious Diseases

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10.1093/cid/ciu1131

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Scarpino, S. V., Iamarino, A., Wells, C., Yamin, D., Ndeffo-Mbah, M., Wenzel, N. S., Fox, S. J., Nyenswah, T., Altice, F. L., Galvani, A. P., Meyers, L. A., & Townsend, J. P. (2015). Epidemiological and viral genomic sequence analysis of the 2014 Ebola outbreak reveals clustered transmission. Clinical Infectious Diseases, 60(7), 1079-1082. https://doi.org/10.1093/cid/ciu1131

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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.",

keywords = "Ebola, West Africa, clustering, epidemiology, genome sequencing",

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

note = "Publisher Copyright: {\textcopyright} The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.",

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doi = "10.1093/cid/ciu1131",

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T1 - Epidemiological and viral genomic sequence analysis of the 2014 Ebola outbreak reveals clustered transmission

AU - Scarpino, Samuel V.

AU - Iamarino, Atila

AU - Wells, Chad

AU - Yamin, Dan

AU - Ndeffo-Mbah, Martial

AU - Wenzel, Natasha S.

AU - Fox, Spencer J.

AU - Nyenswah, Tolbert

AU - Altice, Frederick L.

AU - Galvani, Alison P.

AU - Meyers, Lauren Ancel

AU - Townsend, Jeffrey P.

N1 - Publisher Copyright: © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.

PY - 2015/4/1

Y1 - 2015/4/1

N2 - 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.

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KW - West Africa

KW - clustering

KW - epidemiology

KW - genome sequencing

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

Abstract

Keywords

ASJC Scopus subject areas

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