Participatory probabilistic assessment of the risk to human health associated with cryptosporidiosis from urban dairying in Dagoretti, Nairobi, Kenya

dc.contributor.authorGrace, Delia
dc.contributor.authorMonda, Joseph
dc.contributor.authorKaranja, Nancy
dc.contributor.authorRandolph, Thomas F.
dc.contributor.authorKang’ethe, Erastus K.
dc.date.accessioned2012-09-07T17:07:19Z
dc.date.available2012-09-07T17:07:19Z
dc.date.copyright2012
dc.date.issued2012-08
dc.descriptionThis paper is part of a special supplement on assessing and managing urban zoonoses and food-borne disease in two African cities (Nairobi, Kenya and Ibadan, Nigeria).en
dc.description.abstractWe carried out a participatory risk assessment to estimate the risk (negative consequences and their likelihood) from zoonotic Cryptosporidium originating in dairy farms in urban Dagoretti, Nairobi to dairy farm households and their neighbours.We selected 20 households at high risk for Cryptosporidium from a larger sample of 300 dairy households in Dagoretti based on risk factors present. We then conducted a participatory mapping of the flow of the hazard from its origin (cattle) to human potential victims. This showed three main exposure pathways (food and water borne, occupational and recreational). This was used to develop a fault tree model which we parameterised using information from the study and literature. A stochastic simulation was used to estimate the probability of exposure to zoonotic cryptosporidiosis originating from urban dairying. Around 6 % of environmental samples were positive for Cryptosporidium. Probability of exposure to Cryptosporidium from dairy cattle ranged from 0.0055 for people with clinical acquired immunodeficiency syndrome in non-dairy households to 0.0102 for children under 5 years from dairy households. Most of the estimated health burden was born by children. Although dairy cattle are the source of Cryptosporidium, the model suggests consumption of vegetables is a greater source of risk than consumption of milk. In conclusion, by combining participatory methods with quantitative microbial risk assessment, we were able to rapidly, and with appropriate ‘imprecision’, investigate health risk to communities from Cryptosporidium and identify the most vulnerable groups and the most risky practices.en
dc.formatTexten
dc.format.extent1 digital file (10 p. : ill.)en
dc.format.mimetypeapplication/pdf
dc.identifier.citationGrace, D., Monda, J., Karanja, N., Randolph, T.F., & Kang’ethe, E.K. (2012). Participatory probabilistic assessment of the risk to human health associated with cryptosporidiosis from urban dairying in Dagoretti, Nairobi, Kenya. Tropical Animal Health and Production, SI.doi:10.1007/s11250-012-0204-3en
dc.identifier.issn0049-4747
dc.identifier.urihttp://hdl.handle.net/10625/50247
dc.language.isoen
dc.publisherSpringeren
dc.relation.journalTropical Animal Health and Production
dc.subjectURBAN DAIRYINGen
dc.subjectCRYPTOSPORIDIUMen
dc.subjectPARTICIPATORY RISK ASSESSMENTen
dc.subjectNAIROBIen
dc.subjectECOHEALTHen
dc.subjectKENYAen
dc.subjectURBAN DAIRY PRODUCTIONen
dc.subjectZOONOTIC DISEASESen
dc.subjectFOOD BORNE DISEASEen
dc.subjectVECTOR-BORNE DISEASESen
dc.titleParticipatory probabilistic assessment of the risk to human health associated with cryptosporidiosis from urban dairying in Dagoretti, Nairobi, Kenyaen
dc.typeJournal Article (peer-reviewed)en
idrc.copyright.holderSpringer Science+Business Media B.V.
idrc.dspace.accessIDRC Onlyen
idrc.noaccessDue to copyright restrictions the full text of this research output is not available in the IDRC Digital Library or by request from the IDRC Library. / Compte tenu des restrictions relatives au droit d'auteur, le texte intégral de cet extrant de recherche n'est pas accessible dans la Bibliothèque numérique du CRDI, et il n'est pas possible d'en faire la demande à la Bibliothéque du CRDI.en
idrc.project.componentnumber103075001
idrc.project.number103075
idrc.project.titleHealth Risk Analysis of Cryptosporidiosis and other Hazards in Urban Smallholder Dairy Production (Kenya)en
idrc.rims.adhocgroupIDRC SUPPORTEDen

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