Abstract
The 2014 West African Ebola Outbreak is the largest Ebola virus disease (EVD) epidemic ever recorded, not only in number of cases but also in geographical extent. Unlike previous EVD outbreaks, the large number of cases observed in major cities with international airports raised the concern about the possibility of exportation of the infection in countries around the world. Starting in July 2014, we used the Global Epidemic and Mobility model to provide a real-time assessment of the potential international spread of the EVD epidemic. We modeled the unfolding of the outbreak in the most affected countries, considered different scenarios reflecting changes in the disease dynamic, and provided estimates for the probability of observing imported cases around the world for 220 countries. The model went through successive calibrations as more surveillance data were available, providing projections extending from a few weeks to several months. The results show that along the entire course of the epidemic the probability of observing cases outside of Africa was small, but not negligible, from September to November 2014. The inflection point of the epidemic occurred in late September and early October 2014 with a consistent longitudinal decrease in new cases, thus averting the status quo epidemic growth that could have seen hundreds of exported cases at the global scale in the following months.
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Acknowledgments
We acknowledge funding from DTRA-1-0910039 and MIDAS-National Institute of General Medical Sciences U54-GM111274. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. MFCG acknowledges CNPq-Brazil fellowship 314164/2014-6. We thank Nicole Samay for her invaluable help in the editing and preparation of the figures of the manuscript.
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Pastore-Piontti, A. et al. (2016). Real-Time Assessment of the International Spreading Risk Associated with the 2014 West African Ebola Outbreak. In: Chowell, G., Hyman, J. (eds) Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases. Springer, Cham. https://doi.org/10.1007/978-3-319-40413-4_4
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DOI: https://doi.org/10.1007/978-3-319-40413-4_4
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