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. 2025 Jul 28;19(7):e0013233.
doi: 10.1371/journal.pntd.0013233. eCollection 2025 Jul.

Precision mapping of schistosomiasis and soil-transmitted helminthiasis among school-age children: Targeting interventions in western Kenya

Affiliations

Precision mapping of schistosomiasis and soil-transmitted helminthiasis among school-age children: Targeting interventions in western Kenya

Stella Kepha et al. PLoS Negl Trop Dis. .

Abstract

Background: Mapping of schistosomiasis (SCH) and soil-transmitted helminthiasis (STH) is a critical step in understanding where at-risk populations live in order to effectively plan and target available resources and to achieve maximum impact on disease burden. A precision mapping protocol was developed and implemented in Kakamega, Bungoma, Trans Nzoia and Vihiga Counties in western Kenya by applying the current World Health Organization (WHO) mapping guideline at a lower administrative level (Ward).

Methods: Cross-sectional surveys were conducted among school-age children (SAC) in 5 primary schools purposefully selected in each mapping unit (Ward). In each school, stool and urine samples were collected from 60 randomly selected children (ages 8-14 years). The prevalence and intensity of infection of Schistosoma mansoni and STH were determined using the Kato-Katz technique and urine filtration for S. haematobium. Water Sanitation and Hygiene (WASH) status were also recorded.

Results: Of the 46,464 children sampled, 3.2% (95% CI: 3.0-3.3) were infected with at least one Schistosoma species, with S. mansoni being the most predominant at 3.2% (95% CI: 2.9 - 3.3). 7.6% (95% CI: 7.3 - 7.8) of children were infected with at least one STH species, with A. lumbricoides being the most common (6.5%), and hookworm the least common (0.7%). The prevalence of S. mansoni was highest in Bungoma County (4.5%) and lowest in Trans Nzoia county (0.5%); STH prevalence was highest in Vihiga County (10.7%) and lowest in Trans Nzoia County (4.8%). SCH and STH infections were mainly of light intensity (2.2% and 5.6%, respectively). Based on sub-County-level data and prevalence threshold of ≥2% for MDA, 49 and 144 Wards required treatment for SCH and STH, respectively, whereas based on the Ward-level data, only 40 and 138 Wards required treatment for SCH and STH, respectively.

Conclusions: Use of Ward relative to sub-county prevalence revealed considerable spatial heterogeneity for SCH and STH and resulted in 14.5% and 0.8% reduction in the number of people treated for SCH and STH, respectively, underscoring the critical role of precision mapping in improved targeting of interventions.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Four counties in western Kenya where the study was conducted https://www.gadm.org/download_country.html.
Fig 2
Fig 2. Data flow diagram showing recruitment rates and loss to follow-up at various stages of sampling.
Fig 3
Fig 3. Prevalence distribution of S. mansoni by County, sub-County, Ward and site level, https://www.gadm.org/download_country.html.
Fig 4
Fig 4. Prevalence distribution of S. haematobium by County, sub-County, Ward and site level. https://www.gadm.org/download_country.html.
Fig 5
Fig 5. Prevalence distribution of Any STH by County, sub-County, Ward and site level, https://www.gadm.org/download_country.html.
Fig 6
Fig 6. Prevalence distribution of A. lumbricoides by County, sub-County, Ward and site level, https://www.gadm.org/download_country.html.
Fig 7
Fig 7. Prevalence distribution of Hookworm by County, sub-County, Ward and site level, https://www.gadm.org/download_country.html.
Fig 8
Fig 8. Prevalence distribution of T. trichiura by County, sub-County, Ward and site level, https://www.gadm.org/download_country.html.

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