Informing Rift Valley Fever preparedness by mapping seasonally varying environmental suitability

Abstract

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.

Keywords: Environmental suitability; Mapping; Outbreak; Preparedness; Rift Valley Fever; Spillover potential.

Figure 1

Rift Valley Fever detections used for modelling. Caption: Data from the EMPRES-i database and our literature extraction are shown. These occurrence data represent cases in humans (blue), mammals (red), and vectors (green) that were detected either by PCR or by a serological test on a symptomatic subject. They were used as input into the environmental suitability model.

Figure 2

Average number of suitable months per year. Caption: The average number of suitable months per year across years 1995-2016 is shown for each 5 × 5-km pixel. A pixel was considered suitable in a month-year combination if its predicted suitability value was above an optimized threshold for that month-year. Places in darker purple were suitable for more months per year, on average.

Figure 3

Mean monthly suitability predictions. Caption: Mean RVF suitability is shown throughout the year for January (A), April (B), July (C), and October (D). The pixel values in each monthly map represent the average suitability in that month across the years 1995-2016. Places in purple were more suitable, on average, than places in green. Maps for all 12 months are shown in Appendix Figures 31-42.

Figure 4

Monthly spillover value. Caption: These maps show districts’ average spillover potential during January (A), April (B), July (C), and October (D). Values in these maps represent average spillover values in that month across all years of analysis. Districts in dark purple represent districts with the highest spillover potential. Maps for all 12 months are provided in Appendix Figures 67-78.

Figure 5

Average number of months per year in the highest spillover category. Caption: Each district is colored by how many months per year, on average, it was in the top spillover quintile of districts at risk of RVF. Districts in darker purple were in the top quintile most often. Districts in grey were never in the top quintile.