Abstract
Genetic analyses have provided important insights into Ebola virus spread during the recent West African outbreak, but their implications for specific intervention scenarios remain unclear. Here, we address this issue using a collection of phylodynamic approaches. We show that long-distance dispersal events were not crucial for epidemic expansion and that preventing viral lineage movement to any given administrative area would, in most cases, have had little impact. However, major urban areas were critical in attracting and disseminating the virus: preventing viral lineage movement to all three capitals simultaneously would have contained epidemic size to one-third. We also show that announcements of border closures were followed by a significant but transient effect on international virus dispersal. By quantifying the hypothetical impact of different intervention strategies, as well as the impact of barriers on dispersal frequency, our study illustrates how phylodynamic analyses can help to address specific epidemiological and outbreak control questions.
Highlights
Genetic analyses have provided important insights into Ebola virus spread during the recent West African outbreak, but their implications for specific intervention scenarios remain unclear
We quantify important parameters of spatial spread and demonstrate how a posterior predictive simulation procedure can be used to evaluate potential barriers to transmission, the impact of border closures. These new evolutionary approaches deepen our understanding of the public health implications of Ebola virus (EBOV) epidemic dynamics and the extent to which viral spread could be curbed by particular intervention strategies
To understand the implications of EBOV metapopulation dynamics during the 2013–2016 epidemic, we first investigate the impact of hypothetical intervention strategies on epidemic size and
Summary
Genetic analyses have provided important insights into Ebola virus spread during the recent West African outbreak, but their implications for specific intervention scenarios remain unclear. Ebola viral genomes were reported across numerous studies focusing on different time periods and/or geographic areas, the collated genetic data cover the entire epidemic exceptionally well, and sampling intensity correlates strongly with the infection burden in different locations throughout the course of the outbreak[27] This data set motivated a detailed phylogeographic study that identified the patterns and drivers of spatial spread[27]. We quantify important parameters of spatial spread and demonstrate how a posterior predictive simulation procedure can be used to evaluate potential barriers to transmission, the impact of border closures These new evolutionary approaches deepen our understanding of the public health implications of EBOV epidemic dynamics and the extent to which viral spread could be curbed by particular intervention strategies
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
