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. 2025 Dec 5;19(12):e0013746.
doi: 10.1371/journal.pntd.0013746. eCollection 2025 Dec.

The epidemiology and spatial distribution of Taenia solium taeniosis and cysticercosis in Kenya: The case of Busia County

Affiliations

The epidemiology and spatial distribution of Taenia solium taeniosis and cysticercosis in Kenya: The case of Busia County

Yewubdar Gulelat Zemedhun et al. PLoS Negl Trop Dis. .

Erratum in

Abstract

Background: Taenia solium is responsible for a substantial global disease burden in pig-raising and pork-consuming regions of the developing world. The study assessed the reported spatial pattern of Taenia solium taeniosis and cysticercosis (TSTC) in Kenya, with the focus on risk mapping of TSTC in Busia County.

Methodology: The study employed a mixed approach, incorporating routinely collected data and open-source resources. A literature review and collection of pig population data were used to map the TSTC and pig population distribution at the national level. In Busia County, the retrospective study retrieved reports on porcine cysticercosis and epilepsy (as a proxy indicator of neurocysticercosis) from hospitals and meat inspection records. The cross-sectional study assessed risk behaviors associated with TSTC in Busia County. The TSTC reports and proportions of porcine cysticercosis and epilepsy (as a proxy indicator of neurocysticercosis) were aggregated at the county and sub-county levels and visualized using QGIS. In addition, the World Health Organization's (WHO's) T. solium mapping tool was employed for risk mapping T. solium in Busia County.

Results: The pig population data showed a linear growth trend, with a higher population reported in Central and Western Kenya. A systematic search of the literature yielded a total of fourteen research reports, with the reported cases ranging from 1.8% to 49.9% for porcine cysticercosis, 1.6% to 31.1% for human cysticercosis, and 0.18% to 19.9% for T. solium taeniosis, respectively. The retrospective data showed cases of porcine cysticercosis and epilepsy (as a proxy indicator of neurocysticercosis) in all sub-counties of Busia. The WHO risk mapping tool categorized Bunyala, Teso South, Nambale, and Butula sub-counties as high-risk areas. The questionnaire survey highlighted semi-confinement as the predominant pig husbandry practice (61.1%), with 32% of pigs having access to sewage, and there was poor community awareness about TSTC in Busia County.

Conclusion: The study indicated the presence of TSTC transmission in Western Kenya and identified Busia County as a high-risk area based on multiple layers of evidence. This mixed approach utilized readily available data to generate new evidence that could support sustainable One Health strategies for interrupting the T. solium transmission cycle.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Map showing the distribution of pig population in key pig-keeping counties of Kenya and porcine cysticercosis reports.
Fig 2
Fig 2. Map illustrating the spatial distribution of the reported TSTC cases in Kenya based on the literature review.
The map was produced using the free and open-source QGIS software. The shapefile was obtained from Humanitarian Data Exchange Kenya Subnational Administrative Boundaries data set (https://data.humdata.org/dataset/geoboundaries-admin-boundaries-for-kenya) and provided by the geoBoundaries under CC BY 4.0 license https://www.geoboundaries.org/index.html#citation [42].
Fig 3
Fig 3. The map showing the distribution of porcine cysticercosis and epilepsy in Busia sub-counties from retrospective hospital and meat inspection records.
The map was produced using the free and open-source QGIS software. The shapefile was obtained from Humanitarian Data Exchange Kenya Subnational Administrative Boundaries data set (https://data.humdata.org/dataset/geoboundaries-admin-boundaries-for-kenya) and provided by the geoBoundaries under CC BY 4.0 license https://www.geoboundaries.org/index.html#citation [42].
Fig 4
Fig 4. Map showing the risk of T. solium transmission in Busia County using the WHO mapping tool.
The map was produced using the free and open-source QGIS software. The shapefile was obtained from Humanitarian Data Exchange Kenya Subnational Administrative Boundaries data set (https://data.humdata.org/dataset/geoboundaries-admin-boundaries-for-kenya) and provided by the geoBoundaries under CC BY 4.0 license https://www.geoboundaries.org/index.html#citation [42].

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