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.

The prevalence of schistosomiasis japonica has decreased significantly, and the responses changing from control to elimination in Jiangsu Province, P.R. China. How to estimate the change in prevalence of schistosomiasis using only serological data will be important and useful. We collected serum samples from 2011 to 2015 to build a serum bank from Dantu County of Jiangsu, China. Serum samples were detected by enzyme-linked immunosorbent assay (ELISA), the positive rate and optical density (OD) value were obtained. The Bayesian model including the prior information of sensitivity and specificity of ELISA was established, and the estimated infection rates were obtained for different years, genders and age groups. There was no significant difference in the mean OD between different years and genders, but there was a significant difference between the different age groups. There were statistically significant differences in the positive rate for different years and age groups, but no significant difference at different genders. The estimated infection rate for the five years was 1.288, 1.456, 1.032, 1.485 and 1.358%, respectively. There was no significant difference between different years and between genders, but a significant difference between different age groups. The risk of schistosomiasis transmission in this area still exists, and risk monitoring of schistosomiasis should be strengthened.

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.

Rapid diagnosis of urogenital schistosomiasis caused by Schistosoma haematobium requires an accurate and timely assay, especially for low-intensity S. haematobium infection cases and in non-endemic areas. The mitochondrial cytochrome c oxidase 1 (cox1) gene fragment of S. haematobium was selected as detection target as this short fragment, which can be rapidly sequenced and yet possess good diagnostic resolution. A pair of primers and a fluorescent probe were designed according to the principle of recombinase-aided amplification (RAA), which was subsequently optimized and applied as an S. haematobium-specific RAA assay. Its diagnostic performance was validated for sensitivity and specificity in comparison to microscopy-based egg counting after urine filtration. The RAA assay could detect as little as 10 copies/μL of S. haematobium recombinant plasmid, and no cross-reactions were observed with S. mansoni, S. japonicum, Ancylostoma duodenale, Clonorchis sinensis, Echinococcus granulosus, or Ascaris lumbricoides. This test can be conducted at 39 °C and the whole RAA reaction can be completed within 20 min. The validation of the RAA assay showed that it had 100 % consistency with urine-egg microscopy, as it does not require an elaborate reading tool, is simple to use, and should be useful for field diagnostics and point-of-care applications.

Schistosomiasis is serious parasitic disease with an estimated global prevalence of active infections of more than 190 million. Accurate methods for the assessment of schistosomiasis risk are crucial for schistosomiasis prevention and control in China. Traditional approaches to the identification of epidemiological risk factors include pathogen biology, immunology, imaging, and molecular biology techniques. Identification of schistosomiasis risk has been revolutionized by the advent of computer network communication technologies, including 3S, mathematical modeling, big data, and artificial intelligence (AI). In this review, we analyze the development of traditional and new technologies for risk identification of schistosomiasis transmission in China. New technologies allow for the integration of environmental and socio-economic factors for accurate prediction of the risk population and regions. The combination of traditional and new techniques provides a foundation for the development of more effective approaches to accelerate the process of schistosomiasis elimination.

Background:Bulinus globosus snail was the intermediate host of schistosome hematobium and hard to be found during the dry season. This study aimed to understand the vertical distribution of B. globosus in desiccated and re-hydrated soils and provide evidence on whether snails can drill into the soil for summer.Methods: Four laboratory/field experiments were designed to study the downward movement of the snails in desiccated soils or upward movement in re-watered soils. In Experiment 1, aquaria containing snails on the soil surface were placed in an outdoor environment to desiccate naturally. Then, snails were retrieved from different soil layers. In Experiment 2, snails on the soil surface were covered with an extra 5 cm layer of soil and 4 cm layer of water. The snail positions and survival rates were checked on the first, third, fifth, seventh, and ninth day. In Experiment 3, a seasonal ditch was selected in the field. After the soil in the ditch was naturally desiccated, 1cm, 1–3cm, 3–5cm, and 5–10 cm depth of soil layers were screened to retrieve snails. In Experiment 4, after the above ditch was naturally re-watered, snails were checked in the surface water once a week for 5 weeks.Results: At the end of Experiment 1, all the snails were only found at the soil surface. At the end of Experiment 2, snails were found neither within nor on top of the 4 cm layer of extra mud. At the end of Experiment 3, 96.92% of snails remained on the soil surface. Next, 2.77% of living snails were found in the mud crack within 1–5 cm depth. In Experiment 4, after the experimental field was naturally re-watered, no snails were found above the soil surface.Conclusion:B. globosus snails do not initially move downward into the soil during the dry season or upward to the soil surface after being re-watered.