scholarly journals Rift Valley fever in the Horn of Africa: challenges and opportunities

2012 ◽  
Vol 3 (2) ◽  
pp. 24 ◽  
Author(s):  
Nicole Butcher ◽  
Melissa Tan ◽  
Mohamud Sheikh
Author(s):  
R. Swanepoel ◽  
J. T. Paweska

Rift Valley fever (RVF) is an acute disease of domestic ruminants in mainland Africa and Madagascar, caused by a mosquito borne virus and characterized by necrotic hepatitis and a haemorrhagic state. Large outbreaks of the disease in sheep, cattle and goats occur at irregular intervals of several years when exceptionally heavy rains favour the breeding of the mosquito vectors, and are distinguished by heavy mortality among newborn animals and abortion in pregnant animals. Humans become infected from contact with tissues of infected animals or from mosquito bite, and usually develop mild to moderately severe febrile illness, but severe complications, which occur in a small proportion of patients, include ocular sequelae, encephalitis and fatal haemorrhagic disease. Despite the occurrence of low case fatality rates, substantial numbers of humans may succumb to the disease during large outbreaks. Modified live and inactivated vaccines are available for use in livestock, and an inactivated vaccine was used on a limited scale in humans with occupational exposure to infection. The literature on the disease has been the subject of several extensive reviews from which the information presented here is drawn, except where indicated otherwise (Henning 1956; Weiss 1957; Easterday 1965; Peters and Meegan 1981; Shimshony and Barzilai 1983; Meegan and Bailey 1989; Swanepoel and Coetzer 2004; Flick and Bouloy 2005). In September 2000, the disease appeared in south-west Saudi Arabia and adjacent Yemen, and the outbreak lasted until early 2001 (Al Hazmi et al. 2003; Madani et al. 2003; Abdo-Salem et al. 2006). The virus was probably introduced with infected livestock from the Horn of Africa, and it remains to be determined whether it has become endemic on the Arabian Peninsula.


2012 ◽  
Vol 13 (5) ◽  
Author(s):  
Robert D. Fyumagwa ◽  
Mangi J Ezekiel ◽  
Athanas Nyaki ◽  
Maulid L Mdaki ◽  
Zablon B. Katale ◽  
...  

2010 ◽  
Vol 43 (2) ◽  
pp. 471-480 ◽  
Author(s):  
Shaif Abdo-Salem ◽  
Agnès Waret-Szkuta ◽  
François Roger ◽  
Marie-Marie Olive ◽  
Khalid Saeed ◽  
...  

2006 ◽  
Vol 19 (9) ◽  
pp. 1673-1687 ◽  
Author(s):  
Matayo Indeje ◽  
M. Neil Ward ◽  
Laban J. Ogallo ◽  
Glyn Davies ◽  
Maxx Dilley ◽  
...  

Abstract In this paper the progress made in producing predictions of the Normalized Difference Vegetation Index (NDVI) over Kenya in the Greater Horn of Africa (GHA) for the October–December (OND) season is discussed. Several studies have identified a statistically significant relationship between rainfall and NDVI in the region. Predictability of seasonal rainfall by global climate models (GCMs) during the OND season over the GHA has also been established as being among the best in the world. Information was extracted from GCM seasonal prediction output using statistical transformations. The extracted information was then used in the prediction of NDVI. NDVI is a key variable for management of various climate-sensitive problems. For example, it has been shown to have the potential to predict environmental conditions associated with Rift Valley Fever (RVF) viral activity and this is referred to throughout the paper as a motivation for the study. RVF affects humans and livestock and is particularly economically important in the GHA. The establishment of predictability for NDVI in this paper is therefore part of a methodology that could ultimately generate information useful for managing RVF in livestock in the GHA. It has been shown that NDVI can be predicted skillfully over the GHA with a 2–3-month lead time. Such information is crucial for tailoring forecast information to support RVF monitoring and prediction over the region, as well as many other potential applications (e.g., livestock forage estimation). More generally, the Famine Early Warning System (FEWS), a project of the U.S. Agency for International Development (USAID) and the National Aeronautics and Space Administration (NASA) and other specialized technical centers routinely use NDVI images to monitor environmental conditions worldwide. The high predictability for NDVI established in this paper could therefore supplement the routine monitoring of environmental conditions for a wide range of applications.


1950 ◽  
Vol 5 (5) ◽  
pp. 243-247
Author(s):  
Minoru MATSUMOTO ◽  
Saburo IWASA ◽  
Motosige ENDO

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