Advancing schistosomiasis monitoring through optimised environmental DNA detection

Abstract

Schistosomiasis, caused by parasites of the genus Schistosoma, remains a major public health burden in sub-Saharan Africa, particularly where access to clean water, sanitation, and hygiene is limited. Effective control requires large-scale surveillance, but traditional methods such as malacological surveys, and stool or urine microscopy often lack sensitivity and scalability. This study evaluated environmental DNA-based detection of Schistosoma mansoni in water samples from Lake Albert and Lake Victoria, Uganda. Three filtration techniques (open membrane, Waterra eDNA capsule, and Sylphium eDNA Dual filter capsule), were compared for eDNA yield and detection sensitivity. Quantitative PCR (qPCR) targeting the cytochrome c oxidase subunit 1 (COI) mitochondrial gene was used to quantify S. mansoni eDNA, following in silico and in vitro primer optimisation. Conventional malacological surveys were conducted in parallel for validation. Statistical analyses further examined associations between eDNA yield, detectability, and environmental factors. The qPCR assay had a practical limit of detection (LOD) of 100 DNA copies per reaction and a theoretical LOD/limit of quantification of 83 copies. Schistosoma mansoni eDNA was detected in 26 % (15/58) of samples from Lake Albert and 24 % (27/113) from Lake Victoria. Waterra filters yielded the most eDNA, and Sylphium purification produced significantly greater yields than column-based extraction kits. Both filter type and eDNA yield significantly influenced S. mansoni detection: Waterra and Sylphium-single filters had the highest amplification probabilities (~40 %), while open membrane filters performed poorly (~3 %). eDNA yield was a strong predictor of detection, with the odds of positivity increasing by ~0.8 % per additional nanogram of eDNA. Among positive samples, Waterra filters produced the lowest mean Ct values, indicating greater recovery of amplifiable parasite DNA. Conversely, open membrane filters were the most affect by field contamination. Our findings highlight eDNA as a sensitive and scalable tool for surveillance of schistosomiasis and other water-borne parasitic diseases. While higher-capacity filters and two-phase extraction methods maximised eDNA yield, lower-yield methods still enabled detection in high-transmission settings. A comparative analysis of sampling effort, costs and contamination and infection risks is presented. Overall, our results support the adaptability of eDNA approaches across resource contexts and underscore the need for protocol standardisation, ecological validation, and field-deployable diagnostics such as LAMP.