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BackgroundInfections caused by both Schistosoma mansoni and Schistosoma haematobium are endemic in Kenya, with over six million children at risk. A national school-based deworming programme was launched in 2012 with the goal of eliminating parasitic worms as a public health problem. This study used a model-based geostatistical (MBG) approach to design and analyse the impact of the programme and inform treatment strategy changes for schistosomiasis (SCH).MethodsA cross-sectional survey of 200 schools across 27 counties of Kenya was utilised. The study design, selection of the schools, and analysis followed the MBG approach, which incorporated historical data on treatment, morbidity, and environmental covariates.ResultsThe overall SCH prevalence was 5.0% (95% CI 4.9%–5.2%) and was estimated, with a high predictive probability of 0.999, to be between 1% and< 10%. The predictive probabilities at county level revealed county heterogeneity, with that of four counties estimated to be between 0% and< 1%, that of 20 counties estimated to be between 1% and< 10%, that of two counties estimated to be between 10% and< 20%, and that of one county estimated to be between 20% and< 50%.ConclusionSCH treatment requirements can now be confidently refined based on the World Health Organization’s guidelines. The four counties with prevalences of between 0% and< 1% may consider suspending treatment only in areas (i.e., sub-counties and wards) where the prevalence is< 1%.

Background: Kenya is endemic for soil-transmitted helminths (STH) with over 6 million children in 27 counties currently at-risk. A national school-based deworming programme (NSBDP) was launched in 2012 with a goal to eliminate parasitic worms as a public health problem. This study used model-based geostatistical (MBG) approach to design and analyse the impact of the NSBDP and inform treatment strategy changes. Methods: A cross-sectional study was used to survey 200 schools across 27 counties in Kenya. The study design, school selection and analysis followed the MBG approach which incorporated historical data on treatment, morbidity and environmental covariates to efficiently predict the helminths prevalence in Kenya. Results: Overall, the NSBDP geographic area prevalence for any STH was estimated to sit between 2 % and 0.999. Species-specific thresholds were between 2 % and 0.999. Conclusions: Based on the World Health Organization guidelines, STH treatment requirements can now be confidently refined. Ten counties may consider suspending treatment and implement appropriate surveillance system, while another 10 will require treatment once every two years, and the remaining seven will require treatment once every year.