Schistosomiasis is a serious and neglected global tropical disease, affecting upwards of 230 million people, with more than 95% of infections concentrated in Africa. For many years, the main schistosomiasis control strategy in Africa focused on mass drug administration (MDA). The aim of this study was to compare the difference between MDA alone and alongside another intervention, namely snail control, by exploring effective measures for eliminating schistosomiasis. Retrospective data of human prevalence on Schistosoma haematobium and major control measures were collected from the China-Zanzibar-WHO Cooperation Project for Schistosomiasis Elimination (CZW) and the Zanzibar Elimination of Schistosomiasis Transmission (ZEST) project since 2012. The optimal order polynomial regression fitting model and joinpoint regression model (JRM) were used to analyze trends in schistosomiasis prevalence and the consistency of change points with strengthening of the control measures. In Unguja Island, the main control measure was MDA, and prevalence decreased to a nadir in 2019, and then rebounded. The R² value of the optimal fitting model was 0.6641. There was a single JRM changepoint in 2019, the annual percent change (APC) was −19.3% (p < 0.05) from 2012 to 2019, and the APC was 59.7% (p > 0.05) from 2019 to 2021. In Pemba Island, the main control measures until 2016 was MDA, while integrated measures of MDA and snail control were implemented from 2017, the prevalence continuously decreased, and the R² value was 0.8673. There was also a single JRM changepoint in 2017, the APC was −22.2% (p < 0.05) from 2012 to 2017, and was maintained at −8.6% (p > 0.05) from 2017 to 2021. Our data indicate that, while it is challenging to eliminate schistosomiasis by MDA alone, integrated measures, including both MDA and snail control, can prevent reinfection and help to eliminate the diseases in Africa.

Schistosomiasis remains a major public health concern in Africa, despite global efforts to eliminate the disease by 2030. This study estimates the burden, trends, and inequalities of schistosomiasis in Africa from 1990 to 2021, and projects future prevalence to inform the WHO’s elimination strategies. Data from the Global Burden of Disease Study (GBD 2021) were used to calculate annual average percentage change (AAPC) and annual percentage change (APC), with spatial global autocorrelation analysis performed to examine temporal and spatial trends. Five modeling algorithms were constructed to predict disease burden in Africa from 2022 to 2041. The age-standardized prevalences rate (ASPR) of schistosomiasis in Africa decreased from 18,495.51 per 100,000 in 1990 to 9,461.76 per 100,000 in 2021. The total number of cases, disability-adjusted life-years (DALYs), and mortality accounted for 84.25%, 87.92% and 87.28% of the global totals, respectively. ARIMA modeling predicts that by 2030, the ASPR will reach 3.99%. Despite progress, the burden remains significant, and intensified efforts are needed, particularly in high-burden regions like West Africa, to meet the WHO’s 2030 elimination targets.

Background: As the unique intermediate host of Schistosoma japonicum, the geographical distribution of Oncomelania hupensis (O. hupensis) is an important index in the schistosomiasis surveillance system. This study comprehensively analyzed the pattern of snail distribution along the Yangtze River in Jiangsu Province and identified the dynamic determinants of the distribution of O. hupensis. Methods: Snail data from 2017 to 2021 in three cities (Nanjing, Zhenjiang, and Yangzhou) along the Yangtze River were obtained from the annual cross-sectional survey produced by the Jiangsu Institute of Parasitic Diseases. Spatial autocorrelation and hot-spot analysis were implemented to detect the spatio–temporal dynamics of O. hupensis distribution. Furthermore, 12 factors were used as independent variables to construct an ordinary least squares (OLS) model, a geographically weighted regression (GWR) model, and a geographically and temporally weighted regression (GTWR) model to identify the determinants of the distribution of O. hupensis. The adjusted coefficients of determination (adjusted R², AICc, RSS) were used to evaluate the performance of the models. Results: In general, the distribution of O. hupensis had significant spatial aggregation in the past five years, and the density of O. hupensis increased eastwards in the Jiangsu section of the lower reaches of the Yangtze River. Relatively speaking, the distribution of O. hupensis wase spatially clustered from 2017 to 2021, that is, it was found that the border between Yangzhou and Zhenjiang was the high density agglomeration area of O. hupensis snails. According to the GTWR model, the density of O. hupensis was related to the normalized difference vegetation index, wetness, dryness, land surface temperature, elevation, slope, and distance to nearest river, which had a good explanatory power for the snail data in Yangzhou City (adjusted R² = 0.7039, AICc = 29.10, RSS = 6.81). Conclusions: The distribution of O. hupensis and the environmental factors in the Jiangsu section of the lower reaches of the Yangtze River had significant spatial aggregation. In different areas, the determinants affecting the distribution of O. hupensis were different, which could provide a scientific basis for precise prevention and control of O. hupensis. A GTWR model was prepared and used to identify the dynamic determinants for the distribution of O. hupensis and contribute to the national programs of control of schistosomiasis and other snail-borne diseases.

Schistosomiasis remains a major global public health challenge. Bulinus serves as an intermediate host for Schistosoma, including S. haematobium, S. intercalatum, and S. guineensis. Emerging evidence suggests that temperature fluctuations associated with global climate change are key factors influencing the survival and distribution of Bulinus. The ecological shifts in intermediate host snails may significantly influence schistosomiasis transmission dynamics, thereby exacerbating threats to human health. However, the physiological effects of temperature stress on the survival of B. globosus at the molecular level, including gene expression and underlying mechanisms, remain unclear. Our experimental study found that extreme temperature stress significantly reduced the survival rates of Bulinus globosus (B. globosus). De novo transcriptome sequencing revealed key genes associated with lipid metabolism, carbohydrate metabolism, homeostasis regulation, and the antioxidant system. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis identified significant enrichment of differentially expressed genes (DEGs) in heat shock protein pathways, propanoate metabolism, and N-acylethanolamine metabolism pathways. Overall, this work provides the first transcriptomic characterization of the thermal stress response in B. globosus, extending genomic resources for annotation and stress-related gene discovery. These findings establish a solid foundation for developing control strategies to mitigate climate-driven risks of schistosomiasis transmission.