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Throughout sub-Saharan Africa, most countries endemic for schistosomiasis (SCH) have successfully scaled-up treatment with praziquantel through schools or in the community. Surveys are now needed to evaluate the impact of the interventions, to ensure that resources are being directed to the areas of greatest need.
Photo Credit: The END Fund/Viviane Rakotoarivony
Countries: Ghana, Côte d’Ivoire, Mali and Togo
Implementing partners: London School of Hygiene and Tropical Medicine, Kenya Medical Research Institute, Swiss Tropical Public Health Institute and the Task Force for Global Health, with funding from the United States Agency for International Development and the Bill and Melinda Gates Foundation
Timescale: 2021 – present
Throughout sub-Saharan Africa, most countries endemic for schistosomiasis (SCH) have successfully scaled-up treatment with praziquantel through schools or in the community. Surveys are now needed to evaluate the impact of the interventions, to ensure that resources are being directed to the areas of greatest need. But given the highly focal nature of SCH, it is important to determine the optimal sampling approach to assess disease prevalence and enable treatment decisions at a more focal level.
The World Health Organization set up a technical working group, with Unlimit Health as a key member, to evaluate multiple sampling strategies. This group determined the critical need for a precise understanding of the underlying prevalence of SCH in different settings in which the sampling strategies could be compared. Consequently, the Schistosomiasis Oversampling Study (SOS) was developed as a large multi-country evaluation, conducted in Ghana, Côte d’Ivoire, Mali and Togo, selected for their different transmission settings.
The aim of SOS is to provide a detailed epidemiological understanding of the distribution of two SCH species: S. haematobium and S. mansoni in school-age children after multiple rounds of treatment.
The prevalence data can be used in geostatistical models to create prevalence surfaces, which can then be used to evaluate different sampling strategies and ultimately to select an approach that is optimal for SCH programme decision making by ministries of health. However, the optimal sampling design needs to ensure it is both feasible for country programs to implement and result in sufficiently accurate treatment classifications.
Initial results from these study sites suggest that a ‘one size fits all’ approach for programmatic decisions may be hard to find.
Geostatistical modelling was used to create fine-scale SCH prevalence surfaces using country data and simulated optimal sampling strategies for SCH impact assessments, which would enable sub-implementation unit decision making. The outcomes were shared with Programme Managers in SSA and international experts during a meeting at the Bill and Melinda Gates Foundation office in Seattle, USA highlighting the key finding and further critical analyses that were required under the SOS project.