Imperial College London
Alternate

Steven Riley

Faculty of Medicine, School of Public Health

Professor of Infectious Disease Dynamics
 
 
 
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Contact

 

+44 (0)20 7594 2452s.riley

 
 
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Location

 

UG8Medical SchoolSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Lau:2017:10.1073/pnas.1614595114,
author = {Lau, MSY and Dalziel, BD and Funk, S and McClelland, A and Tiffany, A and Riley, S and Metcalf, CJE and Grenfell, BT},
doi = {10.1073/pnas.1614595114},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
pages = {2337--2342},
title = {Spatial and temporal dynamics of superspreading events in the 2014-2015 West Africa Ebola epidemic},
url = {http://dx.doi.org/10.1073/pnas.1614595114},
volume = {114},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The unprecedented scale of the Ebola outbreak in WesternAfrica (2014–2015) has prompted an explosion of efforts tounderstand the transmission dynamics of the virus and to analyzethe performance of possible containment strategies. Modelshave focused primarily on the reproductive numbers of thedisease that represent the average number of secondary infectionsproduced by a random infectious individual. However,these population-level estimates may conflate important systematicvariation in the number of cases generated by infectedindividuals, particularly found in spatially localized transmissionand superspreading events. Although superspreading featuresprominently in first-hand narratives of Ebola transmission, itsdynamics have not been systematically characterized, hinderingrefinements of future epidemic predictions and explorations oftargeted interventions. We used Bayesian model inference to integrateindividual-level spatial information with other epidemiologicaldata of community-based (undetected within clinical-caresystems) cases and to explicitly infer distribution of the cases generatedby each infected individual. Our results show that superspreadersplay a key role in sustaining onward transmission ofthe epidemic, and they are responsible for a significant proportion(∼61%) of the infections. Our results also suggest age as akey demographic predictor for superspreading. We also show thatcommunity-based cases may have progressed more rapidly thanthose notified within clinical-care systems, and most transmissionevents occurred in a relatively short distance (with median valueof 2.51 km). Our results stress the importance of characterizingsuperspreading of Ebola, enhance our current understanding ofits spatiotemporal dynamics, and highlight the potential importanceof targeted control measures.
AU  - Lau,MSY
AU  - Dalziel,BD
AU  - Funk,S
AU  - McClelland,A
AU  - Tiffany,A
AU  - Riley,S
AU  - Metcalf,CJE
AU  - Grenfell,BT
DO  - 10.1073/pnas.1614595114
EP  - 2342
PY  - 2017///
SN  - 0027-8424
SP  - 2337
TI  - Spatial and temporal dynamics of superspreading events in the 2014-2015 West Africa Ebola epidemic
T2  - Proceedings of the National Academy of Sciences of the United States of America
UR  - http://dx.doi.org/10.1073/pnas.1614595114
UR  - http://hdl.handle.net/10044/1/52855
VL  - 114
ER  -
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