Spatially explicit Schistosoma infection risk in eastern Africa using Bayesian geostatistical modelling

Area of Science:

• Epidemiology
• Parasitology
• Geographic Information Systems (GIS)

Background:

• Schistosomiasis is a major parasitic disease in tropical and subtropical regions.
• Current prevalence data are outdated due to population and environmental changes.
• Accurate risk assessments are crucial for effective schistosomiasis control interventions.

Purpose of the Study:

• To generate updated, high-resolution prevalence maps for Schistosoma mansoni and Schistosoma haematobium in eastern Africa.
• To estimate the current number of infected individuals across 13 eastern African countries.
• To inform and guide future schistosomiasis control and monitoring strategies.

Main Methods:

• Analysis of georeferenced survey data from an open-access neglected tropical diseases database.
• Application of Bayesian geostatistical models incorporating climatic and environmental factors.
• Utilized alignment factors to combine data from different age groups and estimate prevalence in specific age strata and entire communities.

Main Results:

• An estimated 122 million individuals in eastern Africa are infected with S. mansoni, S. haematobium, or both.
• Prevalence estimates varied significantly by country, ranging from 12.9% to 34.5% for S. mansoni and 11.9% to 40.9% for S. haematobium.
• Identified higher-than-expected infection risks in Burundi, Eritrea, Ethiopia, Kenya, Rwanda, Somalia, and Sudan, and lower-than-expected risks in Mozambique and Tanzania.

Conclusions:

• This study provides the most current, spatially explicit estimates of schistosomiasis prevalence in eastern Africa.
• The findings highlight the need for revised intervention strategies and resource allocation.
• These empirical risk estimates serve as a vital benchmark for future schistosomiasis control program evaluations.