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Using Reverse Genetics to Manipulate the NSs Gene of the Rift Valley Fever Virus MP-12 Strain to Improve Vaccine Safety and Efficacy
Published on: November 1, 2011
Informing Rift Valley Fever preparedness by mapping seasonally varying environmental suitability
Austin N Hardcastle1, Joshua C P Osborne1, Rebecca E Ramshaw1
1Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Background:
Rift Valley Fever (RVF) poses a threat to human and animal health throughout much of Africa and the Middle East and has been recognized as a global health security priority and a key preparedness target.
Methods:
We combined RVF occurrence data from a systematic literature review with animal notification data from an online database. Using boosted regression trees, we made monthly environmental suitability predictions from January 1995 to December 2016 at a 5 × 5-km resolution throughout regions of Africa, Europe, and the Middle East. We calculated the average number of months per year suitable for transmission, the mean suitability for each calendar month, and the "spillover potential," a measure incorporating suitability with human and livestock populations.
Results:
Several countries where cases have not yet been reported are suitable for RVF. Areas across the region of interest are suitable for transmission at different times of the year, and some areas are suitable for multiple seasons each year. Spillover potential results show areas within countries where high populations of humans and livestock are at risk for much of the year.
Conclusions:
The widespread environmental suitability of RVF highlights the need for increased preparedness, even in countries that have not previously experienced cases. These maps can aid in prioritizing long-term RVF preparedness activities and determining optimal times for recurring preparedness activities. Given an outbreak, our results can highlight areas often at risk for subsequent transmission that month, enabling decision-makers to target responses effectively.
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