The 2013–2016 West African epidemic caused by the Ebola virus was of unprecedented magnitude, duration and impact. Here we reconstruct the dispersal, proliferation and decline of Ebola virus throughout the region by analysing 1,610 Ebola virus genomes, which represent over 5% of the known cases. We test the association of geography, climate and demography with viral movement among administrative regions, inferring a classic ‘gravity’ model, with intense dispersal between larger and closer populations. Despite attenuation of international dispersal after border closures, cross-border transmission had already sown the seeds for an international epidemic, rendering these measures ineffective at curbing the epidemic. We address why the epidemic did not spread into neighbouring countries, showing that these countries were susceptible to substantial outbreaks but at lower risk of introductions. Finally, we reveal that this large epidemic was a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help to inform interventions in future epidemics.
Access optionsAccess options
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
The authors acknowledge support from: European Union Seventh Framework 278433-PREDEMICS (P.L., A.R.) and ERC 260864 (P.L., A.R., M.A.S.) European Union Horizon 2020 643476-COMPARE (M.P.G.K., A.R.), 634650-VIROGENESIS (P.L., M.P.G.K.), 666100-EVIDENT and European Commission IFS/2011/272-372, EMLab (S.G.), National Institutes of Health R01 AI107034, R01 AI117011 and R01 HG006139 and National Science Foundation IIS 1251151 and DMS 1264153 (M.A.S.), NIH AI081982, AI082119, AI082805 AI088843, AI104216, AI104621, AI115754, HSN272200900049C, HHSN272201400048C (R.F.G.), NIH R35 GM119774-01 (T.B.) National Health & Medical Research Council (Australia) (E.C.H.). The Research Foundation - Flanders G0D5117N (G.B., P.L.), Work in Liberia was funded by the Defense Threat Reduction Agency, the Global Emerging Infections System and the Targeted Acquisition of Reference Materials Augmenting Capabilities (TARMAC) Initiative agencies from the US Department of Defense (G.Pa.), Bill and Melinda Gates Foundation OPP1106427, 1032350, OPP1134076, Wellcome Trust 106866/Z/15/Z, Clinton Health Access Initiative (A.J.T.), National Institute for Health Research Health Protection Research Unit in Emerging and Zoonotic Infections (J.A.H.), Key Research and Development Program from the Ministry of Science and Technology of China 2016YFC1200800 (D.L.), National Natural Science Foundation of China 81590760 and 81321063 (G.F.G.), Mahan Post-doctoral fellowship Fred Hutchinson Cancer Research Center (G.D.), National Institute of Allergy and Infectious Disease U19AI110818, 5R01AI114855-03, United States Agency for International Development OAA-G-15-00001 and the Bill and Melinda Gates Foundation OPP1123407 (P.C.S.), NIH 1U01HG007480-01 and the World Bank ACE019 (C.T.H.), PEW Biomedical Scholarship, NIH UL1TR001114, and NIAID contract HHSN272201400048C (K.G.A.). J.H.K., an employee of Tunnell Government Services, Inc., is a subcontractor under Battelle Memorial Institute’s prime contract with the NIAID (contract HHSN272200700016I). Colour-blind-friendly colour palettes were designed by C. Brewer, Pennsylvania State University (http://colorbrewer2.org). Matplotlib (http://matplotlib.org) was used extensively throughout this article for data visualisation. We acknowledge support from NVIDIA Corporation with the donation of parallel computing resources used for this research. Finally, we recognize the contributions made by our colleagues who died from Ebola virus disease whilst fighting the epidemic.
Extended data figures
Extended data tables
Map of the three most affected countries - Guinea, Liberia and Sierra Leone - is shown on the left. Colours indicate country - Guinea is green, Liberia is red and Sierra Leone is blue. Weekly incidence of EVD cases is indicated by shading of administrative divisions (darker shades correspond to more cases, on a logarithmic scale) within each country. Cases are linearly interpolated between successive reporting weeks. Inferred movements of Ebola virus are indicated with tapered projectiles, coloured by its origin country (Guinea in green, Sierra Leone in blue, Liberia in red) if lineage is crossing an international border and black otherwise. Red circles at population centroids of each administrative division indicate the number of lineages estimated to be present within the location. Phylogenetic tree in the upper right shows the relationships between sampled Ebola lineages, with branches coloured by location (lighter shades indicate locations further west within each country). Migrations inferred between any two locations in the tree are animated on the map on the left. Plot on the lower right shows the sum of weekly cases reported for each administrative division, for each individual country (Guinea in green, Sierra Leone in blue, Liberia in red). Weekly cases for individual administrative divisions are animated as changes in administrative division's colour on the map on the left.
About this article
Journal of Molecular Evolution (2019)