Spatial and Temporal Dynamics of Superspreading Events in the 2014-2015 West Africa Ebola Epidemic

Hdl Handle:
http://hdl.handle.net/10144/618809
Title:
Spatial and Temporal Dynamics of Superspreading Events in the 2014-2015 West Africa Ebola Epidemic
Authors:
Lau, MSY; Dalziel, BD; Funk, S; McClelland, A; Tiffany, A; Riley, S; Metcalf, CJE; Grenfell, BT
Journal:
Proceedings of the National Academy of Sciences of the United States of America
Abstract:
The unprecedented scale of the Ebola outbreak in Western Africa (2014-2015) has prompted an explosion of efforts to understand the transmission dynamics of the virus and to analyze the performance of possible containment strategies. Models have focused primarily on the reproductive numbers of the disease that represent the average number of secondary infections produced by a random infectious individual. However, these population-level estimates may conflate important systematic variation in the number of cases generated by infected individuals, particularly found in spatially localized transmission and superspreading events. Although superspreading features prominently in first-hand narratives of Ebola transmission, its dynamics have not been systematically characterized, hindering refinements of future epidemic predictions and explorations of targeted interventions. We used Bayesian model inference to integrate individual-level spatial information with other epidemiological data of community-based (undetected within clinical-care systems) cases and to explicitly infer distribution of the cases generated by each infected individual. Our results show that superspreaders play a key role in sustaining onward transmission of the epidemic, and they are responsible for a significant proportion ([Formula: see text]61%) of the infections. Our results also suggest age as a key demographic predictor for superspreading. We also show that community-based cases may have progressed more rapidly than those notified within clinical-care systems, and most transmission events occurred in a relatively short distance (with median value of 2.51 km). Our results stress the importance of characterizing superspreading of Ebola, enhance our current understanding of its spatiotemporal dynamics, and highlight the potential importance of targeted control measures.
Publisher:
National Academy of Sciences
Issue Date:
13-Feb-2017
URI:
http://hdl.handle.net/10144/618809
DOI:
10.1073/pnas.1614595114
PubMed ID:
28193880
Language:
en
ISSN:
1091-6490
Appears in Collections:
Other Diseases

Full metadata record

DC FieldValue Language
dc.contributor.authorLau, MSYen
dc.contributor.authorDalziel, BDen
dc.contributor.authorFunk, Sen
dc.contributor.authorMcClelland, Aen
dc.contributor.authorTiffany, Aen
dc.contributor.authorRiley, Sen
dc.contributor.authorMetcalf, CJEen
dc.contributor.authorGrenfell, BTen
dc.date.accessioned2017-02-28T21:19:40Z-
dc.date.available2017-02-28T21:19:40Z-
dc.date.issued2017-02-13-
dc.identifier.citationSpatial and Temporal Dynamics of Superspreading Events in the 2014-2015 West Africa Ebola Epidemic. 2017 Proc. Natl. Acad. Sci. U.S.A.en
dc.identifier.issn1091-6490-
dc.identifier.pmid28193880-
dc.identifier.doi10.1073/pnas.1614595114-
dc.identifier.urihttp://hdl.handle.net/10144/618809-
dc.description.abstractThe unprecedented scale of the Ebola outbreak in Western Africa (2014-2015) has prompted an explosion of efforts to understand the transmission dynamics of the virus and to analyze the performance of possible containment strategies. Models have focused primarily on the reproductive numbers of the disease that represent the average number of secondary infections produced by a random infectious individual. However, these population-level estimates may conflate important systematic variation in the number of cases generated by infected individuals, particularly found in spatially localized transmission and superspreading events. Although superspreading features prominently in first-hand narratives of Ebola transmission, its dynamics have not been systematically characterized, hindering refinements of future epidemic predictions and explorations of targeted interventions. We used Bayesian model inference to integrate individual-level spatial information with other epidemiological data of community-based (undetected within clinical-care systems) cases and to explicitly infer distribution of the cases generated by each infected individual. Our results show that superspreaders play a key role in sustaining onward transmission of the epidemic, and they are responsible for a significant proportion ([Formula: see text]61%) of the infections. Our results also suggest age as a key demographic predictor for superspreading. We also show that community-based cases may have progressed more rapidly than those notified within clinical-care systems, and most transmission events occurred in a relatively short distance (with median value of 2.51 km). Our results stress the importance of characterizing superspreading of Ebola, enhance our current understanding of its spatiotemporal dynamics, and highlight the potential importance of targeted control measures.en
dc.language.isoenen
dc.publisherNational Academy of Sciencesen
dc.rightsArchived with thanks to Proceedings of the National Academy of Sciences of the United States of Americaen
dc.titleSpatial and Temporal Dynamics of Superspreading Events in the 2014-2015 West Africa Ebola Epidemicen
dc.identifier.journalProceedings of the National Academy of Sciences of the United States of Americaen

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