Geostatistical Model-Based Estimates of Schistosomiasis Prevalence among Individuals Aged ≤20 Years in West Africa

Abstract

Background

Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps.

Methodology

We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging.

Principal Findings

Our models revealed that 50.8 million individuals aged ≤20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection.

Conclusion/Significance

We present the first empirical estimates for S. mansoni and S. haematobium prevalence at high spatial resolution throughout West Africa. Our prediction maps allow prioritizing of interventions in a spatially explicit manner, and will be useful for monitoring and evaluation of schistosomiasis control programs.

Author Summary

Schistosomiasis is a parasitic disease caused by a blood fluke that mainly occurs in Africa. Current prevalence estimates of schistosomiasis are based on historical data, and hence might be outdated due to control programs, improved sanitation, and water resources development and management (e.g., construction of large dams and irrigation systems). To help planning, coordination, and evaluation of control activities, reliable schistosomiasis prevalence estimates are needed. We analyzed compiled survey data from 1980 onwards for West Africa, including Cameroon, focusing on individuals aged ≤20 years. Bayesian geostatistical models were implemented based on environmental and climatic predictors to take into account potential spatial clustering within the data. We created the first smooth data-driven prevalence maps for Schistosoma mansoni and S. haematobium at high spatial resolution throughout West Africa. We found that an estimated 50.8 million West Africans aged ≤20 years are infected with schistosome blood flukes. Country prevalence estimates ranged between 0.5% (in The Gambia) and 37.1% (in Liberia) for S. mansoni and between 17.6% (in The Gambia) and 51.6% (in Sierra Leone) for S. haematobium. Our results allow prioritization of areas where interventions are needed, and to monitor and evaluate the impact of control activities.