Spatiotemporal analysis of schistosomiasis and soil-transmitted helminth distribution in three highly endemic provinces in Angola

Abstract

A school-based preventive chemotherapy (PC) program has operated since 2013 for soil-transmitted helminths (STHs) and 2014 for schistosomiasis in Huambo, Uige and Zaire provinces, Angola. This program was informed by a prevalence survey in 2014 and evaluated in 2021, demonstrating limited impact in reducing provincial-level prevalence. This geospatial analysis aims to provide granular estimates of the geographic distribution of schistosomiasis and STHs to target control strategies. Methods Parasitological data on schistosomiasis and STHs were obtained from school-based prevalence surveys conducted in 2014 and 2021. These data were supplemented with open access environmental and climatic data to develop risk prediction maps for each parasite at each time point. Variables for the final risk prediction models were selected through non-spatial multivariable regression analyses and residual spatial autocorrelation was investigated using semivariograms. Risk prediction maps were then developed using either non-spatial or spatial (using the Matérn covariance) geostatistical models depending on the presence of residual spatial autocorrelation. Results The 2014 survey included 17,093 schoolchildren (575 schools) for schistosomiasis and 3,649 schoolchildren (121 schools) for STHs, and the 2021 survey included 17,880 schoolchildren (599 schools) for schistosomiasis and 6,461 schoolchildren (214 schools) for STHs. Our analyses indicated that in Huambo province, there are small areas of high schistosomiasis risk in the north and south, and a centrally located STH hotspot, with no discernible change in predicted risk for either infection over time. In Uige, there has been a reduction in schistosomiasis hotspots in the southwest corner but an overall increase in predicted risk throughout the province, whilst there is a concerning trend for expanding areas of high predicted STH risk throughout. In Zaire, there are increasing areas of higher risk for schistosomiasis and STHs, with co-endemic hotspots. Conclusion These risk prediction maps importantly identify higher risk areas for schistosomiasis and STHs within large geographic regions that should be prioritised for control with tailored decisions for future PC delivery.