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Background Soil-transmitted helminth (STH) infections can cause a significant disease burden. It is estimated that 1.5 billion people worldwide are infected with STHs, primarily in tropical and subtropical regions. This study aimed to assess the distribution of the global burden and trend of STH infections from 1990 to 2021. Methods We retrieved data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 on the age-standardized rates (ASRs) of prevalence and disability-adjusted life-years (DALYs) of STH infections for all age groups in 204 countries and territories from 1990 to 2021. The ASRs of prevalence and DALYs by age, gender, and socio-demographic index (SDI) were calculated to quantify the spatial distribution and temporal trend. Spearman correlation analysis was used to examine the relationship between ASR and SDI. Results In 2021, there were an estimated 642.72 million cases and 1.38 million DALYs caused by STH infections worldwide. The age-standardized prevalence rate (ASPR) of STH infections was 8429.89 [95% uncertainty interval (UI): 7697.23, 9362.18 ] per 100,000 population globally. The ASPR of STH infections varied across 21 geographic regions in 2021, being mainly prevalent in most African and Latin American locations. The prevalence was higher in the groups of 5–19 years, especially the group of 5–9 years with the ASPR of 16,263 (95% UI: 14,877.06, 18,003.49) and ASR of DALYs of 40.69 (95% UI: 25.98, 60.91) per 100,000. The ASPR of STH infections showed an obvious decreasing trend worldwide (estimated annual percent change = − 4.03, 95% confidence interval: − 4.13, − 3.93) with variations in different species infections during the study years. At the regional level, the ASR of STH infections prevalence ( r  = − 0.8807, P  < 0.0001) and DALYs ( r  = − 0.9069, P  < 0.0001) were negatively correlated with SDI . Conclusions STH infections remain a public health problem in 2021, particularly in regions such as the middle parts of Africa and Americas, and in the 5–19 age populations. The reduction in the rate of prevalence and the loss of DALYs are negatively correlated with the increase in SDI. Enhancing political commitment, providing accurate preventive chemotherapy, and advancing techniques for surveillance and mapping systems are essential to achieve the target of ending STH infections as a public health problem by 2030. Graphical Abstract

This study aims to explore the spatiotemporal distribution of schistosomiasis in Jiangling County, and provide insights into the precise schistosomiasis control. The descriptive epidemiological method and Joinpoint regression model were used to analyze the changes in infection rates of humans, livestock, snails, average density of living snails and occurrence rate of frames with snails in Jiangling County from 2005 to 2021. Spatial epidemiology methods were used to detect the spatiotemporal clustering of schistosomiasis transmission risk in Jiangling county. The infection rates in humans, livestock, snails, average density of living snails and occurrence rate of frames with snails in Jiangling County decreased from 2005 to 2021 with statistically significant. The average density of living snails in Jiangling County was spatially clustered in each year, and the Moran's I varied from 0.10 to 0.26. The hot spots were mainly concentrated in some villages of Xionghe Town, Baimasi Town and Shagang Town. The mean center of the distribution of average density of living snails in Jiangling County first moved from northwest to southeast, and then returned from southeast to northwest after 2014. SDE azimuth fluctuated in the range of 111.68°-124.42°. Kernal density analysis showed that the high and medium-high risk areas of Jiangling County from 2005 to 2021 were mainly concentrated in the central and eastern of Jiangling County, and the medium-low and low risk areas were mainly distributed in the periphery of Jiangling County. The epidemic situation of schistosomiasis decreased significantly in Jiangling County from 2005 to 2021, but the schistosomiasis transmission risk still had spatial clustering in some areas. After transmission interruption, targeted transmission risk intervention strategies can be adopted according to different types of schistosomiasis risk areas.

Purpose Mosquito-borne diseases (MBDs) pose a significant threat in the Asia-Pacific region, encompassing both the Western Pacific and South-East Asia. This study is aimed at improving the understanding of the evolution of incidence patterns of MBDs within the Asia-Pacific region and supporting the development of effective health policies. Methods Case numbers, incidence, and age-standardized incidence rate (ASIR) of MBDs were obtained from the Global Burden of Disease Study 2021. Furthermore, an Age-Period-Cohort model was applied to characterize overall temporal trends in MBDs incidence and to assess the independent effects of age, period, and birth cohort. Decomposition analysis was used to quantify the extent to epidemiological changes, population growth, and aging contributed to the observed trends. Additional stratified analyses were performed by regions and country. Results From 1992 to 2021, the ASIR of MBDs in the Asia-Pacific region displayed regional heterogeneity. Overall, the net drift of ASIR indicated an annual increase of 1.07% per year in the Western Pacific region, rising from 292.26 to 380.84 per 100,000 population. In contrast, the South-East Asia region experienced an annual decrease of 1.88% per year, with ASIR declining from 3,779.81 to 1,856.84 per 100,000 population. Meanwhile, driven by population growth and epidemiological changes, dengue gradually replaced malaria as the predominant MBD in both regions. Dengue cases increased from 1,082,887 to 3,839,091 in the Western Pacific region and from 14,326,313 to 32,627,815 in the South-East Asia region, far exceeding the corresponding malaria cases (2,387,112 and 5,784,641). Age-Period-Cohort analysis further revealed distinct epidemiological patterns: South-East Asia exhibited favorable period and cohort effects, while the Western Pacific showed an unfavorable trend. Conclusion The intensifying threat of MBDs in the Western Pacific region underscores the need for highly responsive and adaptive public health strategies, supported by ongoing regional collaboration.

Abstract Antibiotic-resistant (AR) bacterial wound infections (WIs) impose major burdens on healthcare systems, exacerbated by ineffective therapies and stalled antibiotic development. Phage therapy and phage-derived enzymes have gained traction as potent alternatives, leveraging targeted bactericidal mechanisms to combat AR pathogens. In this review, we summarised the antimicrobial mechanisms of both phage therapy and phage-derived enzymes as antimicrobial therapy, and outlined recent advances in their use for in vitro, in vivo and clinical applications for WI management. In addition, we also highlights recent advancements in their development, driven by genetic engineering, chemical modifications, and artificial intelligence. Finally, we identified the potential barriers and challenges they may encounter in clinical practice and the corresponding strategies to address these issues. The entire review gives us a comprehensive understanding of the latest advances in phages and their derivative enzyme therapies for treating WIs, in the hope that research in this field will continue to improve and innovate, accelerating the transition from the laboratory to application at the bedside and ultimately improving the efficacy of treatment for AR bacterial WIs.

Background Visceral leishmaniasis (VL) is one of the most important neglected tropical diseases. Although VL was controlled in several regions of China during the last century, the mountain-type zoonotic visceral leishmaniasis (MT-ZVL) has reemerged in the hilly areas of China in recent decades. The purpose of this study was to construct an indicator framework for assessing the risk of the MT-ZVL in China, and to provide guidance for preventing disease. Methods Based on a literature review and expert interview, a 3-level indicator framework was initially established in November 2021, and 28 experts were selected to perform two rounds of consultation using the Delphi method. The comprehensive weight of the tertiary indicators was determined by the Delphi and the entropy weight methods. Results Two rounds of Delphi consultation were conducted. Four primary indicators, 11 secondary indicators, and 35 tertiary indicators were identified. The Delphi-entropy weight method was performed to calculate the comprehensive weight of the tertiary indicators. The normalized weights of the primary indicators were 0.268, 0.261, 0.242, and 0.229, respectively, for biological factors, interventions, environmental factors, and social factors. The normalized weights of the top four secondary indicators were 0.122, 0.120, 0.098, and 0.096, respectively, for climatic features, geographical features, sandflies, and dogs. Among the tertiary indicators, the top four normalized comprehensive weights were the population density of sandflies (0.076), topography (0.057), the population density of dogs, including tethering (0.056), and use of bed nets or other protective measures (0.056). Conclusions An indicator framework of transmission risk assessment for MT-ZVL was established using the Delphi-entropy weight method. The framework provides a practical tool to evaluate transmission risk in endemic areas.

Schistosomiasis japonica represents a significant public health concern in South Asia. There is an urgent need to optimize existing schistosomiasis diagnostic techniques. This study aims to develop models for the different stages of liver fibrosis caused by Schistosoma infection utilizing ultrasound radiomics and machine learning techniques. From 2018 to 2022, we retrospectively collected data on 1,531 patients and 5,671 B-mode ultrasound images from the Second People's Hospital of Duchang City, Jiangxi Province, China. The datasets were screened based on inclusion and exclusion criteria suitable for radiomics models. Liver fibrosis due to Schistosoma infection (LFSI) was categorized into four stages: grade 0, grade 1, grade 2, and grade 3. The data were divided into six binary classification problems, such as group 1 (grade 0 vs. grade 1) and group 2 (grade 0 vs. grade 2). Key radiomic features were extracted using Pyradiomics, the Mann-Whitney U test, and the Least Absolute Shrinkage and Selection Operator (LASSO). Machine learning models were constructed using Support Vector Machine (SVM), and the contribution of different features in the model was described by applying Shapley Additive Explanations (SHAP). This study ultimately included 1,388 patients and their corresponding images. A total of 851 radiomics features were extracted for each binary classification problems. Following feature selection, 18 to 76 features were retained from each groups. The area under the receiver operating characteristic curve (AUC) for the validation cohorts was 0.834 (95% CI: 0.779-0.885) for the LFSI grade 0 vs. LFSI grade 1, 0.771 (95% CI: 0.713-0.835) for LFSI grade 1 vs. LFSI grade 2, and 0.830 (95% CI: 0.762-0.885) for LFSI grade 2 vs. LFSI grade 3. Machine learning models based on ultrasound radiomics are feasible for classifying different stages of liver fibrosis caused by Schistosoma infection.

Background Colpodella species are classified within the domain Eukaryota, specifically under the order Colpodellida, family Colpodellaceae, and genus Colpodella , which are close relative of the phylum Apicomplexa. These organisms are unicellular, predatory flagellates. In recent years, their frequent detection in animal tissues, vector insect samples, and particularly in human has garnered significant attention as an emerging zoonotic threat. This review is to scope the biological characteristics and epidemiological features of Colpodella species. Methods The PubMed, Web of Science, and China National Knowledge Infrastructure databases were searched to identify studies in English or Chinese published before 4 February 2025. We searched for Colpodella -related nucleotide sequences released in the GenBank before 31 December, 2024. The literature and sequences were selected based on predefined inclusion criteria. We extracted the characteristics of Colpodella spp. from included articles and performed a phylogenetic analysis based on the included sequences. Results Thirty-seven records and 83 sequences were included in the study, respectively. Colpodella spp. currently comprise only two formally named species, alongside at least 11 species uncultured or unnamed in GenBank. Their life cycle includes trophozoite and cyst stages, with nutrient acquisition mediated by myzocytosis. These organisms display structural and protein similarities in their apical complexes to apicomplexan protozoa, yet with distinct differences. They are currently found in a wide range of hosts, including humans, livestock, pets, wildlife and vectors, across multiple continents, including Europe, Asia, Africa, and the Americas. Phylogenetic analyses reveal that Colpodella spp. exhibit significant genetic diversity and can be divided into seven clades, each characterized by distinct host ranges and regional distributions, and three clades posed pathogenic potential and significant risk of human infection. Conclusions This study systematically elucidates the broad host/vector range, genetic diversity and public health implications of Colpodella species based on comprehensive integrated genomic and epidemiological analyses. We recommend establishing active surveillance networks using clade-specific molecular markers for hosts and vectors in high-risk regions, incorporating Colpodella screening into routine diagnostics for fever cases of unknown origin with anaemia, prioritizing studies on isolation and cultivation, biological characteristics, and clade-specific in vitro invasion assays to elucidate the pathogenic mechanisms. Graphical Abstract

Precision interventions have been proposed in transmission-interrupted areas to further reduce the potential transmission risk of schistosomiasis. This study aimed to evaluate the effects of different interventions modes for potential transmission risk control. Three groups of schistosomiasis-endemic villages were selected in Jiangling county, Hubei province. After baseline surveys in 2020, three intervention models were employed in 2021 and 2022. In Model 1, Oncomelania hupensis snail control in key settings and an integrated strategy with an emphasis on the infectious sources managing was employed. In Model 2, an integrated health education-led strategy with an emphasis on infectious source management was employed. In Model 3, only the integrated strategy with an emphasis on infectious source management was employed. The effects of the different intervention models were examined with multiple indicators after 2 years of intervention using the entropy-weighted technique for order of preference by similarity to ideal solution (TOPSIS), rank-sum ratio (RSR) and fuzzy combination model of entropy-weighted TOPSIS and RSR. Entropy-weighted TOPSIS modeling showed that the Ci values of Model 2 were 0.4434, 0.2759, and 0.3069 in the three pilot villages, Ci values were larger, with top comprehensive ranking. The results of the RSR method showed that the RSR values of Model 2 were 0.75, 0.708, and 0.736 in the three pilot villages, with top comprehensive ranking. The results from the fuzzy combination model of entropy-weighted TOPSIS and RSR showed that implementation of Model 2 resulted in the highest comprehensive ranking among the three models in the three pilot villages under Ci: RSR = 0.1: 0.9, Ci: RSR = 0.5: 0.5 and Ci: RSR = 0.9: 0.1. The integrated health education-led strategy with an emphasis on infectious source management was the optimal model to manage the risk of transmission of schistosomiasis during the post-transmission interruption phase.

With several decades of concerted control efforts, visceral leishmaniasis(VL) eradication had almost been achieved in China. However, VL cases continue to be detected in parts of western China recent years. Using data of reported cases, this study aimed to investigate the epidemiology and spatio⁃temporal distribution, of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in China between the years 2015 and 2019. Epidemiological data pertaining to patients with visceral leishmaniasis (VL) were collected in Gansu, Shaanxi, Sichuan, Shanxi, Henan and Hebei provinces between the years 2015 and 2019. Joinpoint regression analysis was performed to determine changes in the epidemic trend of MT-ZVL within the time period during which data was collected. Spatial autocorrelation of infection was examined using the Global Moran’s I statistic wand hotspot analysis was carried out using the Getis-Ord Gi* statistic. Spatio-temporal clustering analysis was conducted using the retrospective space-time permutation flexible spatial scanning statistics. A total of 529 cases of MT-ZVL were detected in the six provinces from which data were collected during the study time period, predominantly in Gansu (55.0%), Shanxi (21.7%), Shaanxi (12.5%) and Sichuan (8.9%) provinces. A decline in VL incidence in China was observed during the study period, whereas an increase in MT-ZVL incidence was observed in the six provinces from which data was obtained ( t = 4.87, P < 0.05), with highest incidence in Shanxi province ( t = 16.91, P < 0.05). Significant differences in the Moran’s I statistic were observed during study time period ( P < 0.05), indicating spatial autocorrelation in the spatial distribution of MT-ZVL. Hotspot and spatial autocorrelation analysis revealed clustering of infection cases in the Shaanxi-Shanxi border areas and in east of Shanxi province, where transmission increased rapidly over the study duration, as well as in well know high transmission areas in the south of Gansu province and the north of the Sichuan province. It indicates resurgence of MT-ZVL transmission over the latter three years of the study. Spatial clustering of infection was observed in localized areas, as well as sporadic outbreaks of infection.

Background The One Health (OH) concept has been promoted widely around the globe. OH framework is expected to be applied as an integrated approach to support addressing zoonotic diseases as a significant global health issue and to improve the efficiency and effectiveness of zoonosis prevention and control. This review is intended to overview the social impact of the implementation of OH on zoonosis prevention and control. Methods A scoping review of studies in the past 10 years was performed to overview the integration feature of OH in zoonosis prevention and control and the social impacts of OH. PubMed and Web of Science were searched for studies published in English between January 2011 and June 2021. The included studies were selected based on predefined criteria. Results Thirty-two studies were included in this review, and most of them adopted qualitative and semi-qualitative methods. More than 50% of the studies focused on zoonosis prevention and control. Most studies were conducted in low- and middle-income countries in Africa and Asia. Applying OH approach in diseases control integrates policymakers, stakeholders, and academics from various backgrounds. The impact of OH on economic is estimated that it may alleviate the burden of diseases and poverty in the long term, even though more financial support might be needed at the initial stage of OH implementation. OH implementation considers social and ecological factors related to zoonosis transmission and provides comprehensive strategies to assess and address related risks in different communities according to regions and customs. Conclusions Based on reviewed literature, although there seems to be a lack of guidelines for assessing and visualizing the outcomes of OH implementation, which may limit the large-scale adoption of it, evidence on the contributions of implementing OH concepts on zoonosis prevention and control indicates long-term benefits to society, including a better integration of politics, stakeholders and academics to improve their cooperation, a potential to address economic issues caused by zoonosis, and a comprehensive consideration on social determinants of health during zoonosis prevention and control.