Predictive factors and risk mapping for Rift Valley fever epidemics in Kenya

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cg.authorship.typesCGIAR and developing country instituteen
cg.contributor.affiliationMinistry of Agriculture, Livestock, and Fisheries, Kenyaen
cg.contributor.affiliationWashington State Universityen
cg.contributor.affiliationMinistry of Health, Kenyaen
cg.contributor.affiliationInternational Livestock Research Instituteen
cg.contributor.affiliationUniversity of Twenteen
cg.contributor.affiliationUnited States Centers for Disease Control and Preventionen
cg.contributor.crpAgriculture for Nutrition and Health
cg.coverage.countryKenya
cg.coverage.iso3166-alpha2KE
cg.coverage.regionAfrica
cg.coverage.regionEastern Africa
cg.creator.identifierBernard Bett: 0000-0001-9376-2941en
cg.howPublishedFormally Publisheden
cg.identifier.doihttps://doi.org/10.1371/journal.pone.0144570en
cg.isijournalISI Journalen
cg.issn1932-6203en
cg.issue1en
cg.journalPLOS ONEen
cg.reviewStatusPeer Reviewen
cg.subject.ilriANIMAL DISEASESen
cg.subject.ilriDISEASE CONTROLen
cg.subject.ilriENVIRONMENTen
cg.subject.ilriEPIDEMIOLOGYen
cg.subject.ilriLIVESTOCKen
cg.subject.ilriRVFen
cg.subject.ilriZOONOTIC DISEASESen
cg.volume11en
dc.contributor.authorMunyua, P.M.en
dc.contributor.authorMurithi, R.M.en
dc.contributor.authorIthondeka, P.M.en
dc.contributor.authorHightower, A.en
dc.contributor.authorThumbi, Samuel M.en
dc.contributor.authorAnyangu, S.A.en
dc.contributor.authorKiplimo, Jusper Ronohen
dc.contributor.authorBett, Bernard K.en
dc.contributor.authorVrieling, A.en
dc.contributor.authorBreiman, R.F.en
dc.contributor.authorNjenga, M.K.en
dc.date.accessioned2016-02-11T20:11:44Zen
dc.date.available2016-02-11T20:11:44Zen
dc.identifier.urihttps://hdl.handle.net/10568/71002
dc.titlePredictive factors and risk mapping for Rift Valley fever epidemics in Kenyaen
dcterms.abstractBackground To-date, Rift Valley fever (RVF) outbreaks have occurred in 38 of the 69 administrative districts in Kenya. Using surveillance records collected between 1951 and 2007, we determined the risk of exposure and outcome of an RVF outbreak, examined the ecological and climatic factors associated with the outbreaks, and used these data to develop an RVF risk map for Kenya. Methods Exposure to RVF was evaluated as the proportion of the total outbreak years that each district was involved in prior epizootics, whereas risk of outcome was assessed as severity of observed disease in humans and animals for each district. A probability-impact weighted score (1 to 9) of the combined exposure and outcome risks was used to classify a district as high (score ≥ 5) or medium (score ≥2 - <5) risk, a classification that was subsequently subjected to expert group analysis for final risk level determination at the division levels (total = 391 divisions). Divisions that never reported RVF disease (score < 2) were classified as low risk. Using data from the 2006/07 RVF outbreak, the predictive risk factors for an RVF outbreak were identified. The predictive probabilities from the model were further used to develop an RVF risk map for Kenya. Results The final output was a RVF risk map that classified 101 of 391 divisions (26%) located in 21 districts as high risk, and 100 of 391 divisions (26%) located in 35 districts as medium risk and 190 divisions (48%) as low risk, including all 97 divisions in Nyanza and Western provinces. The risk of RVF was positively associated with Normalized Difference Vegetation Index (NDVI), low altitude below 1000m and high precipitation in areas with solonertz, luvisols and vertisols soil types (p <0.05). Conclusion RVF risk map serves as an important tool for developing and deploying prevention and control measures against the disease.en
dcterms.accessRightsOpen Access
dcterms.audienceScientistsen
dcterms.available2016-01-25en
dcterms.bibliographicCitationMunyua, P.M., Murithi, R.M., Ithondeka, P., Hightower, A., Thumbi, S.M., Anyangu, S.A., Kiplimo, J., Bett, B., Vrieling, A., Breiman, R.F. and Njenga, M.K. 2016. Predictive factors and risk mapping for Rift Valley fever epidemics in Kenya. PLoS ONE 11(1): e0144570.en
dcterms.issued2016-01-25en
dcterms.languageen
dcterms.licenseCC0-1.0
dcterms.publisherPublic Library of Scienceen
dcterms.subjectswineen
dcterms.subjectzoonosesen
dcterms.typeJournal Article

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Learning the lessons of Rift Valley fever: Improved detection and mitigation of outbreaks