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Association between Rift Valley fever virus seroprevalences in livestock and humans and their respective intra-cluster correlation coefficients, Tana River County, Kenya
Int Livestock Res Inst, Nairobi, Kenya.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Int Livestock Res Inst, Nairobi, Kenya; Swedish Univ Agr Sci, Uppsala, Sweden.ORCID iD: 0000-0002-1175-0398
Kenya Govt Med Res Ctr, Nairobi, Kenya.
Int Livestock Res Inst, Nairobi, Kenya.
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2019 (English)In: Epidemiology and Infection, ISSN 0950-2688, E-ISSN 1469-4409, Vol. 147, article id e67Article in journal (Refereed) Published
Abstract [en]

We implemented a cross-sectional study in Tana River County, Kenya, a Rift Valley fever (RVF)-endemic area, to quantify the strength of association between RVF virus (RVFv) seroprevalences in livestock and humans, and their respective intra-cluster correlation coefficients (ICCs). The study involved 1932 livestock from 152 households and 552 humans from 170 households. Serum samples were collected and screened for anti-RVFv immunoglobulin G (IgG) antibodies using inhibition IgG enzyme-linked immunosorbent assay (ELISA). Data collected were analysed using generalised linear mixed effects models, with herd/household and village being fitted as random variables. The overall RVFv seroprevalences in livestock and humans were 25.41% (95% confidence interval (CI) 23.49-27.42%) and 21.20% (17.86-24.85%), respectively. The presence of at least one seropositive animal in a household was associated with an increased odds of exposure in people of 2.23 (95% CI 1.03-4.84). The ICCs associated with RVF virus seroprevalence in livestock were 0.30 (95% CI 0.19-0.44) and 0.22 (95% CI 0.12-0.38) within and between herds, respectively. These findings suggest that there is a greater variability of RVF virus exposure between than within herds. We discuss ways of using these ICC estimates in observational surveys for RVF in endemic areas and postulate that the design of the sentinel herd surveillance should consider patterns of RVF clustering to enhance its effectiveness as an early warning system for RVF epidemics.

Place, publisher, year, edition, pages
2019. Vol. 147, article id e67
Keywords [en]
Hierarchical modelling, Rift Valley fever, intra-cluster correlation coefficients, risk factors, seroprevalence
National Category
Pathobiology
Identifiers
URN: urn:nbn:se:uu:diva-373034DOI: 10.1017/S0950268818003242ISI: 000455339100066PubMedID: 30516123OAI: oai:DiVA.org:uu-373034DiVA, id: diva2:1277477
Available from: 2019-01-10 Created: 2019-01-10 Last updated: 2019-02-06Bibliographically approved

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