One of the strategies for the control and elimination of schistosomiasis is the control of its snail vectors in an endemic area, as is done in other tropical diseases like malaria. However, the strategy currently practiced for the control of the disease in Nigeria is the annual mass administration of preventive chemotherapy (Praziquantel) among school-age children while neglecting the control of its snail intermediate host and other control components. The neglect of malacology and vector control will slow the elimination targets and timeline of 2030 set by the WHO. In this study, we investigated the abundance and seasonal variations in the snail vectors of schistosomiasis and the relationship between the disease among humans and infected snail vectors. A total of 21,282 snails were collected from 13 sites across the six area councils of the Federal Capital Territory (FCT). Of the collected snails, 1451 (6.8%) belong to three species: Biomphelaria pfeifferi (0.5%), Bulinus truncatus (2.1%) and Bulinus globosus (4.2%), which are known to be vectors of Schistosoma mansoni, Schistosoma haematobium and Schistosoma bovis, respectively. These three species were all shedding cercariae both at the time of collection and afterwards, when they were induced to shed cercariae. The association between the reported prevalence of the disease and the percentage of snails shedding cercaria were heterogenous across different communities. While Takushara, with a disease prevalence of 46%, had 60% of the cercaria shedding snails, Kwaita sabo pukafa and Guduji, with disease prevalences of 56% and 26% respectively, had no cercaria shedding snails. Similarly, Dagiri rafin shahu and Gwako 1, with disease prevalences of 60% and 38%, had cercaria shedding snails of less than 1%. Nonetheless, the presence of Bulinus and Biomphelaria species in these communities indicates a potential risk of infection for humans and other animals who may come in contact with the water. Consequently, integrated multisectoral control and elimination measures that combine malacological monitoring with behavioral, environmental, and historical epidemiological assessments with a deliberate health orientation of the people through sensitization and health education is advocated to reduce exposure to the disease risk factors and contribute towards elimination of the disease.

Introduction: Schistosomiasis is a public health concern and there is a need for reliable field-compatible diagnostic methods in endemic settings. The AiDx Assist, an artificial intelligence (AI)-based automated microscope, has shown promising results for the detection of Schistosoma haematobium eggs in urine. It has been further developed to detect Schistosoma mansoni eggs in stool.

Methods: In this study, we evaluated the performance of the AiDx Assist for the detection of S. mansoni eggs in stool samples and further validated the performance of the AiDx Assist for the detection of S. haematobium eggs in urine samples. Additionally, the potential of the AiDx Assist for the detection of other helminths in stool samples was explored. In total, 405 participants from an area endemic for both S. mansoni and S. haematobium provided stool and urine samples which were subjected to AiDx Assist (semi- and fully automated), while conventional microscopy was used as the diagnostic reference.

Results: Only samples with complete test results were included in the final analysis, resulting in 375 stool and 398 urine samples, of which 38.4% and 65.3% showed Schistosoma eggs by conventional microscopy. The collected images of the stool samples were retrospectively examined for other helminth eggs via manual analysis. For the detection of S. mansoni eggs, the sensitivity of the semi-automated AiDx Assist (86.8%) was significantly higher compared to the fully automated AiDx Assist (56.9%) while the specificity was comparable, with 81.4% and 86.8%, respectively. Retrospectively, eggs of Ascaris lumbricoides and Trichuris trichiura were visualized. For the examination of urine samples, a comparable sensitivity in the detection of S. haematobium eggs was found between the semi-and the fully automated modes of the AiDx Assist, showing 94.6% and 91.9%, respectively. Furthermore, the specificity was comparable, with 90.6%and 91.3% respectively.

Discussion: The AiDx Assist met the World Health Organization Target Product Profile criteria in terms of diagnostic accuracy for the detection of S. haematobium eggs in urine samples and performed modestly in the detection of S. mansoni eggs in stool samples. With some further improvements, it has the potential to become a valuable diagnostic tool for screening multiple helminth parasites in stool and urine samples.