RVF risk map for Kenya generated from predicted probabilities by administrative divisions based on Centre Merged Analysis of Precipitation (CMAP).

<p>RVF risk map for Kenya generated from predicted probabilities by administrative divisions based on Centre Merged Analysis of Precipitation (CMAP).</p

Rift Valley Fever risk map for Kenya, 2012 based on the semi-quantitative risk assessment for likelihood of RVF epizootic and expert opinion.

<p>Rift Valley Fever risk map for Kenya, 2012 based on the semi-quantitative risk assessment for likelihood of RVF epizootic and expert opinion.</p

Graphical interpretation of the effects of rainfall and soil type on the risk of RVF outbreak.

<p>Graphical interpretation of the effects of rainfall and soil type on the risk of RVF outbreak.</p

Mean monthly actual rainfall (light shaded bars and left x-axis) recorded in the participating counties and number of suspect and probable Rift Valley Fever (RVF) herds (dark shaded bars and right x-axis) reported in Kenya, November 2015 –February 2016.

<p>Mean monthly actual rainfall (light shaded bars and left x-axis) recorded in the participating counties and number of suspect and probable Rift Valley Fever (RVF) herds (dark shaded bars and right x-axis) reported in Kenya, November 2015 –February 2016.</p

Weekly number of abortions, bleeding, and death syndrome reports (top graph) and number of total reports (bottom graph) submitted to the Rift Valley Fever Alert Centre in Kenya, November 16, 2015 –February 29, 2016.

<p>The total number of reports includes both syndromic and healthy reports.</p

Number of livestock species observed with abortion, bleeding, or death^*.

<p>Number of livestock species observed with abortion, bleeding, or death^{<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0006353#t001fn001" target="_blank">*</a>}.</p

Time-series plots of the weekly reporting for each syndrome by whether flooding and/or mosquito swarms were observed by farmers in their area.

<p>Time-series plots of the weekly reporting for each syndrome by whether flooding and/or mosquito swarms were observed by farmers in their area.</p

Schematic summary of the study design showing the species, the numbers and the physiological status of the study animals.

<p>The study was carried out in three sites (Kabete, Kiboko and Ngong)—all government farms with similar farm management conditions. We used 404 animals in the study, including 85 cattle, 168 sheep, and 151 goats. Of these, 194 were vaccinated with RVF Clone 13 vaccine whereas 210 were injected with placebo. The study animals were divided into 3 groups; Group A included non-pregnant animals, Group B included animal in 1^st half of the pregnancy, and Group C animals in 2^nd half of pregnancy.</p

Administrative Law -- Power of Board of Education to Abolish Fraternities

<p>Left panel (bottom) shows proportion of cattle with IgG antibodies following vaccination 14 to 366 days post-vaccination. The right panel (bottom) shows proportion of cattle that produced anti-RVF IgM antibodies over the 1 year period. The top panel on the left and right are the placebo-treated animals.</p

Map of Kenya showing selected Rift Valley Fever (RVF) high-risk counties in grey.

<p>A high-risk county was based on ecological and climatic factors associated with previous RVF outbreaks in Kenya, as defined by Munyua et al. [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0006353#pntd.0006353.ref019" target="_blank">19</a>]. The high-risk counties were selected for participation in the enhanced surveillance for RVF.</p