scholarly journals Rift Valley Fever Outbreaks in Mauritania and Related Environmental Conditions

2014 ◽  
Vol 11 (1) ◽  
pp. 903-918 ◽  
Author(s):  
Cyril Caminade ◽  
Jacques Ndione ◽  
Mawlouth Diallo ◽  
Dave MacLeod ◽  
Ousmane Faye ◽  
...  
Keyword(s):  
Environmental Conditions ◽  
Rift Valley ◽  
Rift Valley Fever ◽  
Valley Fever

Predictability of the Normalized Difference Vegetation Index in Kenya and Potential Applications as an Indicator of Rift Valley Fever Outbreaks in the Greater Horn of Africa

2006 ◽  
Vol 19 (9) ◽  
pp. 1673-1687 ◽  
Author(s):  
Matayo Indeje ◽  
M. Neil Ward ◽  
Laban J. Ogallo ◽  
Glyn Davies ◽  
Maxx Dilley ◽  
...  
Keyword(s):  
Environmental Conditions ◽  
Rift Valley ◽  
Rift Valley Fever ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Horn Of Africa ◽  
Valley Fever ◽  
Wide Range ◽  
Potential Applications ◽  
Greater Horn Of Africa

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.

Complement fixation reaction of Rift Valley fever virus

1950 ◽  
Vol 5 (5) ◽  
pp. 243-247
Author(s):  
Minoru MATSUMOTO ◽  
Saburo IWASA ◽  
Motosige ENDO
Keyword(s):  
Rift Valley ◽  
Rift Valley Fever ◽  
Complement Fixation ◽  
Rift Valley Fever Virus ◽  
Fever Virus ◽  
Valley Fever ◽  
Fixation Reaction

scholarly journals The Use of Nanotrap Particles in the Enhanced Detection of Rift Valley Fever Virus Nucleoprotein

PLoS ONE ◽  
2015 ◽  
Vol 10 (5) ◽  
pp. e0128215 ◽  
Author(s):  
Nazly Shafagati ◽  
Lindsay Lundberg ◽  
Alan Baer ◽  
Alexis Patanarut ◽  
Katherine Fite ◽  
...  
Keyword(s):  
Rift Valley ◽  
Rift Valley Fever ◽  
Rift Valley Fever Virus ◽  
Fever Virus ◽  
Valley Fever
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