Epidemiologic and Environmental Risk Factors of Rift Valley Fever in Southern Africa from 2008 to 2011.

Margaret M Glancey,Assaf Anyamba,Kenneth J Linthicum

doi:10.1089/vbz.2015.1774

Abstract

Background: Rift Valley fever (RVF) outbreaks have been associated with periods of widespread and above-normal rainfall over several months. Knowledge on the environmental factors influencing disease transmission dynamics has provided the basis for developing models to predict RVF outbreaks in Africa. From 2008 to 2011, South Africa experienced the worst wave of RVF outbreaks in almost 40 years. We investigated rainfall-associated environmental factors in southern Africa preceding these outbreaks.Methods: RVF epizootic records obtained from the World Animal Health Information Database (WAHID), documenting livestock species affected, location, and time, were analyzed. Environmental variables including rainfall and satellite-derived normalized difference vegetation index (NDVI) data were collected and assessed in outbreak regions to understand the underlying drivers of the outbreaks.Results: The predominant domestic vertebrate species affected in 2008 and 2009 were cattle, when outbreaks were concentrated in the eastern provinces of South Africa. In 2010 and 2011, outbreaks occurred in the interior and southern provinces affecting over 16,000 sheep. The highest number of cases occurred between January and April but epidemics occurred in different regions every year, moving from the northeast of South Africa toward the southwest with each progressing year. The outbreaks showed a pattern of increased rainfall preceding epizootics ranging from 9 to 152 days; however, NDVI and rainfall were less correlated with the start of the outbreaks than has been observed in eastern Africa.Conclusions: Analyses of the multiyear RVF outbreaks of 2008 to 2011 in South Africa indicated that rainfall, NDVI, and other environmental and geographical factors, such as land use, drainage, and topography, play a role in disease emergence. Current and future investigations into these factors will be able to contribute to improving spatial accuracy of models to map risk areas, allowing adequate time for preparation and prevention before an outbreak occurs.

Highlights

Rift Valley fever (RVF) was first identified in 1931 in Kenya’s Great Rift Valley following a large epizootic among sheep (Daubney 1931)
Outbreaks have been reported across Africa and the Arabian Peninsula (Davies 1975, Swanepoel 1976, Meegan and Bailey 1989, Davies et al 1992, Arthur et al 1993, Madani et al 2003, Mohamed et al 2010, Shieh et al 2010, Hassan et al 2011). This disease was first recognized in South Africa in 1951, an epidemic that resulted in 500,000 abortions and 100,000 deaths among sheep (Gear et al 1951, Woods et al 2002)
Epidemic years were synchronized to the seasonal rainfall cycle preceding RVF outbreaks so that 2008 contained all outbreaks between October, 2007, and September, 2008; 2009 contained all outbreaks between October, 2008 and September, 2009, and so on

Summary

Introduction

Rift Valley fever (RVF) was first identified in 1931 in Kenya’s Great Rift Valley following a large epizootic among sheep (Daubney 1931). Outbreaks have been reported across Africa and the Arabian Peninsula (Davies 1975, Swanepoel 1976, Meegan and Bailey 1989, Davies et al 1992, Arthur et al 1993, Madani et al 2003, Mohamed et al 2010, Shieh et al 2010, Hassan et al 2011) This disease was first recognized in South Africa in 1951, an epidemic that resulted in 500,000 abortions and 100,000 deaths among sheep (Gear et al 1951, Woods et al 2002). Conclusions: Analyses of the multiyear RVF outbreaks of 2008 to 2011 in South Africa indicated that rainfall, NDVI, and other environmental and geographical factors, such as land use, drainage, and topography, play a role in disease emergence. Current and future investigations into these factors will be able to contribute to improving spatial accuracy of models to map risk areas, allowing adequate time for preparation and prevention before an outbreak occurs

Methods

Results

Discussion

Conclusion