title: Spatial and temporal dynamics of superspreading events in the 2014-2015 West Africa Ebola epidemic.
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.
authors.affiliation: Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544; msylau@princeton.edu.
authors.forename: Max S Y
authors.initials: MS
authors.lastname: Lau
authors.affiliation: Department of Integrative Biology, Oregon State University, Corvallis, OR 97331.|Department of Mathematics, Oregon State University, Corvallis, OR 97331.
authors.forename: Benjamin Douglas
authors.initials: BD
authors.lastname: Dalziel
authors.affiliation: Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Funk
authors.affiliation: International Federation of Red Cross and Red Crescent Societies, CH-1211 Geneva 19, Switzerland.
authors.forename: Amanda
authors.initials: A
authors.lastname: McClelland
authors.affiliation: Epicentre, CH-1211 Geneva 6, Switzerland.
authors.forename: Amanda
authors.initials: A
authors.lastname: Tiffany
authors.affiliation: Medical Research Council Centre for Outbreak Analysis and Modelling, Department Infectious Disease Epidemiology, Imperial College London, London SW7 2AZ, United Kingdom.
authors.forename: Steven
authors.initials: S
authors.lastname: Riley
authors.affiliation: Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544.
authors.forename: C Jessica E
authors.initials: CJ
authors.lastname: Metcalf
authors.affiliation: Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544.|Fogarty International Center, National Institutes of Health, Bethesda, MD 20892.
authors.forename: Bryan T
authors.initials: BT
authors.lastname: Grenfell
mesh_terms: D000293:Adolescent; D000328:Adult; D000354:Africa, Western / Q000453:epidemiology; D000367:Age Factors; D000368:Aged; D001499:Bayes Theorem; D003710:Demography / Q000706:statistics & numerical data*; D018563:Disease Notification / Q000706:statistics & numerical data; D029043:Ebolavirus / Q000472:pathogenicity / Q000502:physiology; D058872:Epidemics; D062665:Epidemiological Monitoring; D005260:Female; D019142:Hemorrhagic Fever, Ebola / Q000453:epidemiology* / Q000635:transmission* / Q000821:virology; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D062211:Spatio-Temporal Analysis
keywords: Bayesian inference; Ebola; offspring distribution; superspreading