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

Clin Infect Dis. 2015 Apr 1;60(7):1079-82. doi: 10.1093/cid/ciu1131. Epub 2014 Dec 15.

Authors

Affiliations

¹ Santa Fe Institute, New Mexico.
² Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut Department of Microbiology, Biomedical Sciences Institute, University of São Paulo, Brazil.
³ Yale Center for Infectious Disease Modeling and Analysis Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut.
⁴ Yale Center for Infectious Disease Modeling and Analysis.
⁵ Department of Integrative Biology, The University of Texas at Austin.
⁶ Ministry of Health and Social Welfare, Monrovia, Liberia.
⁷ Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut Section of Infectious Diseases, Yale University School of Medicine.
⁸ Yale Center for Infectious Disease Modeling and Analysis Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut Program in Computational Biology and Bioinformatics Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut.
⁹ Santa Fe Institute, New Mexico Department of Integrative Biology, The University of Texas at Austin.
¹⁰ Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut Program in Computational Biology and Bioinformatics Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut.

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.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Cluster Analysis
Disease Outbreaks*
Ebolavirus / classification*
Ebolavirus / genetics*
Ebolavirus / isolation & purification
Genome, Viral*
Genotype*
Hemorrhagic Fever, Ebola / transmission*
Hemorrhagic Fever, Ebola / virology*
Humans
Sequence Analysis

Abstract

Publication types

MeSH terms

Grants and funding