Dudas, Gytis; Lemey, Philippe; Rambaut, Andrew. (2017). Virus genomes reveal factors that spread and sustained the Ebola epidemic, 2014-2015 [dataset]. University of Edinburgh. https://doi.org/10.7488/ds/1711.
Molecular epidemiological analysis output files and trees used in:
Dudas et al (2017) Nature.
# Abstract: # The 2013–2016 epidemic of Ebola virus disease was of unprecedented magnitude, duration and impact. Analysing 1610 Ebola virus genomes, representing over 5% of known cases, we reconstruct the dispersal, proliferation and decline of Ebola virus throughout the region. 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 set the seeds for an international epidemic, rendering these measures ineffective in curbing the epidemic. We address why the epidemic did not spread into neighbouring countries, showing they were susceptible to significant outbreaks but at lower risk of introductions. Finally, we reveal this large epidemic to be a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help inform interventions in future epidemics.
# Files: #
* "Makona_1610_joint_phylogeny_spatial_run1.tgz" - BEAST output files for joint discrete spatial GLM and phylogenetic reconstruction of 1610 EBOV genomes from Guinea, Sierra Leone and Liberia sampled over 2014-2015. Chain length 200M stets. Trees and log files plus MCC tree summary.
* "Makona_1610_joint_phylogeny_spatial_run2.tgz" - Second independent run of 200M steps.
* "Makona_1610_metadata_2016-06-23.csv" - metadata file for above genomes comprising sampling locations, sampling dates, responsible labs, accession numbers and references.
* "Location_Data_2016-05-27.csv" - data about each location used in the analysis including demographic, geographic, language and climatic variables.
* "Computed_Data_2016-08-26.csv" - outputs and estimates from the BEAST analysis used in summary analyses and figures.
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