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

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	American English
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 - 1 Apr 2015
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Ebola
West Africa
clustering
epidemiology
genome sequencing

All Science Journal Classification (ASJC) codes

Microbiology (medical)
Infectious Diseases

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10.1093/cid/ciu1131

Cite this

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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title = "Epidemiological and viral genomic sequence analysis of the 2014 Ebola outbreak reveals clustered transmission",

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.",

year = "2015",

month = apr,

day = "1",

doi = "10.1093/cid/ciu1131",

language = "American English",

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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.

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.

AB - 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.

KW - Ebola

KW - West Africa

KW - clustering

KW - epidemiology

KW - genome sequencing

UR - http://www.scopus.com/inward/record.url?scp=84926636820&partnerID=8YFLogxK

U2 - 10.1093/cid/ciu1131

DO - 10.1093/cid/ciu1131

M3 - Article

C2 - 25516185

SN - 1058-4838

VL - 60

SP - 1079

EP - 1082

JO - Clinical Infectious Diseases

JF - Clinical Infectious Diseases

IS - 7

ER -

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

Abstract

UN SDGs

Keywords

All Science Journal Classification (ASJC) codes

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