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Objective: To understand the epidemiological distribution characteristics of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in Yangquan City, Shanxi Province, China, from 2006 to 2021, to explore the influencing factors leading to the re-emergence of the epidemic, and to provide a basis for the formulation of targeted control strategies. Methods: Case information spanning from 2006 to 2021 in Yangquan City was collected for a retrospective case-control study conducted from June to September 2022. A 1:3 matched ratio was employed. A questionnaire was utilized to gather data on basic information, demographic characteristics, awareness of MT-ZVL knowledge, residence, and dog breeding and living habits. The study employed a multifactorial conditional stepwise logistic regression model to analyze the influencing factors. Results: A total of 508 subjects was analyzed. Risk factors for MT-ZVL included the use of soil/stone/concrete as building materials (OR = 3.932), presence of nearby empty/stone stack houses (OR = 2.515), dog breeding (OR = 4.215), presence of stray dogs (OR = 2.767), and neighbor's dog breeding (OR = 1.953). Protective factors comprised knowledge of MT-ZVL (OR = 0.113) and using mosquito repellents (OR = 0.388). The findings indicate significant associations between environmental and behavioral factors and MT-ZVL incidence in Yangquan City, Shanxi Province, China, from 2006 to 2021. These results underscore the importance of public awareness campaigns and targeted interventions aimed at reducing exposure to risk factors and promoting protective measures to mitigate the re-emergence of MT-ZVL outbreaks. Conclusion: House building materials, presence of neighboring empty houses, breeding domestic dogs and distribution of stray dogs surrounding the home are risk factors for MT-ZVL. Awareness of MT-ZVL and implementation of preventive measures during outdoor activities in summer and autumn are protective and may reduce the risk of MT-ZVL. Author summary: In recent years, a rapid reemergence of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) has been seen in the extension region of the Loess Plateau that had previously achieved elimination in China. In this study, we investigate the epidemiological characteristics of MT-ZVL and identify the factors associated with the rapid rise in MT-ZVL epidemics using a case-control design. A questionnaire was used to collect basic information, demographic characteristics, awareness of MT-ZVL knowledge, residence, and dog breeding and living habits. A multifactorial conditional stepwise logistic regression model was used to analyze the influencing factors. The study revealed that there has been a rising trend in the MT-ZVL endemic areas. House building materials, presence of neighboring empty houses, breeding domestic dogs and distribution of stray dogs surrounding the home are risk factors for MT-ZVL. Awareness of MT-ZVL and implementation of preventive measures during outdoor activities in summer and autumn are protective and may reduce the risk of MT-ZVL. We believe that our study makes a significant contribution to the literature to develop strategy for control the ongoing local transmission of MT-ZVL in hill districts. By analyzing the epidemiological characteristics and influencing factors of MT-ZVL, this research provides a basis for further optimizing the targeted control strategies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

With global warming and socioeconomic developments, there is a tendency toward the emergence and spread of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in China. Timely identification of the transmission risk and spread of MT-ZVL is, therefore, of great significance for effectively interrupting the spread of MT-ZVL and eliminating the disease. In this study, 26 environmental variables—namely, climatic, geographical, and 2 socioeconomic indicators were collected from regions where MT-ZVL patients were detected during the period from 2019 to 2021, to create 10 ecological niche models. The performance of these ecological niche models was evaluated using the area under the receiver-operating characteristic curve (AUC) and true skill statistic (TSS), and ensemble models were created to predict the transmission risk of MT-ZVL in China. All ten ecological niche models were effective at predicting the transmission risk of MT-ZVL in China, and there were significant differences in the mean AUC (H = 33.311, p < 0.05) and TSS values among these ten models (H = 26.344, p < 0.05). The random forest, maximum entropy, generalized boosted, and multivariate adaptive regression splines showed high performance at predicting the transmission risk of MT-ZVL (AUC > 0.95, TSS > 0.85). Ensemble models predicted a transmission risk of MT-ZVL in the provinces of Shanxi, Shaanxi, Henan, Gansu, Sichuan, and Hebei, which was centered in Shanxi Province and presented high spatial clustering characteristics. Multiple ensemble ecological niche models created based on climatic and environmental variables are effective at predicting the transmission risk of MT-ZVL in China. This risk is centered in Shanxi Province and tends towards gradual radiation dispersion to surrounding regions. Our results provide insights into MT-ZVL surveillance in regions at high risk of MT-ZVL. [ABSTRACT FROM AUTHOR]

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. Author summary: Leishmania parasite. It was defined as a neglected tropical disease (NTD) by the World Health Organization (WHO) since 2010. The eradication of VL had almost been achieved in the country since 1960s'last century but the parts of western China. Although the numbers of annual reported cases of VL declined, the mountain-type zoonotic visceral leishmaniasis (MT-ZVL) continued to increase in recent years. In this study, the epidemiological characters and spatio⁃temporal distribution of MT-ZVL were investigated in China between the years 2015 and 2019. A total of 529 cases of MT-ZVL were reported in six provinces and predominantly in Gansu (55.0%), Shanxi (21.7%), Shaanxi (12.5%) and Sichuan (8.9%) provinces. Significant differences in the Moran's I statistic were observed, indicating spatial autocorrelation in the spatial distribution of MT-ZVL. Spatio⁃temporal hotspot analysis revealed clustering of infection cases in the Shaanxi-Shanxi border areas and eastern of Shanxi province, as well as in the south of Gansu province and the north of the Sichuan province. Therefore, the reinforcement of VL control in conventionally high-risk areas, attention to areas where VL re-emergence is likely, timely survey of vectors, assessment of transmission risk, and targeted interventions are strongly recommended to reduce risk of MT-ZVL infection. [ABSTRACT FROM AUTHOR]