Preplanned Studies: Epidemiological Transition and Spatial Expansion of Mountain-Type Zoonotic Visceral Leishmaniasis — China, 2010–2024

Introduction: Mountain-type zoonotic visceral leishmaniasis (MT-ZVL) has re-emerged in China with shifting demographic patterns and expanding geographical distribution. This study aimed to characterize its epidemiological and spatial-temporal dynamics to guide targeted control strategies.

Methods: Case data from 2010–2024 were analyzed using χ² tests and proportional analyses. Temporal trends were assessed by Joinpoint regression, projections by autoregressive integrated moving average (ARIMA) models, spatial clustering and directional tendency by Moran’s I and Standard Deviational Ellipse (SDE) analyses.

Results: A total of 2,260 cases were reported, showing a bimodal age distribution (<5 years and 60–75 years) with marked male predominance and a shifting occupational risk toward adults. Affected counties expanded from 19 to 69 and after a decline in 2010–2015, incidence increased and spread eastward during 2015–2024, with projections indicating continued growth by 2030 without strengthened control.

Conclusions: MT-ZVL in China shows expanding risk areas and changing occupational patterns, highlighting the need for strengthened surveillance and targeted control interventions in the regions.

Visceral leishmaniasis (VL), also known as kala-azar, is a neglected tropical disease that is fatal in over 95% of untreated cases (1). Mountain-type zoonotic visceral leishmaniasis (MT-ZVL) represents the predominant form of VL in China, accounting for more than 95% of reported cases. The disease is transmitted by P. chinensis, with dogs and certain wild animals serving as the primary reservoir hosts (2). Following large-scale control efforts initiated in the 1950s, MT-ZVL incidence declined substantially and was largely controlled by the 1960s. However, re-emergence and geographic expansion of MT-ZVL have been observed across multiple provinces in northern and central China over the past decade, raising concerns about the sustainability of previous control achievements (3–5). Recent surveillance data from China’s National Notifiable Diseases Reporting System (NNDRS) reveal shifts in the demographic and occupational profiles of MT-ZVL cases, with increasing involvement of farmers and older adults and a corresponding decline among young children. Concurrently, indigenous cases have been reported in an increasing number of counties, including areas previously not considered endemic, suggesting gradual expansion of transmission zones. These evolving patterns challenge traditional control approaches that focus primarily on historically endemic foci. This study characterizes the demographic features, occupational distribution, temporal trends, and geographic expansion of MT-ZVL transmission in China, providing evidence to inform targeted and adaptive public health interventions.

MT-ZVL surveillance data were obtained from the NNDRS from January 1, 2010, to December 31, 2024, covering 7 endemic provincial-level administrative divisions (PLADs): Beijing Municipality and 6 provinces (Shanxi, Shaanxi, Gansu, Sichuan, Henan, and Hebei). Population denominators were derived from China’s 6th (2010) and 7th (2020) National Population Censuses, with age-specific populations estimated using averaged census data to ensure temporal comparability. Incidence rates were calculated using the age and sex composition of each PLAD. Age- and sex-specific incidence rates were computed, and sex differences were assessed using χ² tests. Occupational categories were consolidated into standardized groups, and proportional distributions across these groups were analyzed to identify temporal shifts in case demographics. Temporal trends in MT-ZVL incidence were evaluated using Joinpoint regression analysis to identify significant inflection points and estimate annual percent changes (APC). Future incidence rates and projected case numbers for 2025–2030 were estimated using autoregressive integrated moving average (ARIMA) models. Spatial autocorrelation was assessed at the county level using Global Moran’s I statistic to evaluate overall clustering patterns. Standard Deviational Ellipse (SDE) analysis was applied to describe the spatial center, dispersion, and directional tendency of disease distribution. Data analysis was performed using R version 4.3.3 (R Foundation for Statistical Computing, Vienna, Austria), ArcGIS version 10.7 (Environmental Systems Research Institute, Redlands, CA, USA), and the Joinpoint Regression Program version 5.0.0 (Surveillance Research Program, National Cancer Institute, Bethesda, MD, USA).

Between 2010 and 2024, a total of 2,260 MT-ZVL cases were reported across the seven endemic provinces. The age-specific incidence demonstrated a bimodal distribution, with peak rates observed among children younger than 5 years and adults aged 60–75 years. Male predominance was statistically significant in infants <1 year (χ²=4.455, P=0.035) and adults aged 35–79 years (all P<0.01). The annual average number of cases per million population increased progressively with age after 30 years, reaching the highest levels in the 65–74-year age group, thereby identifying older adults as a primary high-risk population for MT-ZVL (Table 1). Throughout 2010–2024, MT-ZVL exhibited substantial temporal and seasonal variation. Following a steady decline from 2010 to 2014, both incidence and case numbers increased continuously from 2015 onward, reaching 226 indigenous cases in 2024, corresponding to an incidence rate of 0.608 per 1,000,000 population. Joinpoint regression analysis revealed a clear reversal in temporal trends around 2015. MT-ZVL incidence declined significantly during 2010–2015 [APC=–15.7%, 95% confidence interval (CI): –23.6 to –10.1, P<0.001], followed by a sustained and significant increase during 2015–2024 (APC=13.1%, 95% CI: 10.0 to 17.1, P<0.001). ARIMA projections indicate that without intensified control strategies, incidence will continue to rise, reaching 0.801 per 1,000,000 (95% CI: 0.081 to 1.520) by 2030, with an estimated 1,607 additional cases (95% CI: 660 to 2,554) expected between 2025 and 2030 (Figure 1A). The geographic distribution of MT-ZVL expanded substantially during this period, with the number of counties reporting local cases increasing from 19 in 2010 to 69 in 2024, highlighting progressive transmission spread and an expanding at-risk population (Figure 1B). Seasonal analysis revealed year-round case occurrence, with a pronounced peak from March to August and the highest monthly incidence in April, accounting for over 12% of the annual total (Figure 1C). Occupational analysis (Supplementary Table S1) demonstrated that farmers and scattered children were the primary affected groups, accounting for 40.1% and 30.9% of cases, respectively. Over time, the proportion of cases among scattered children declined markedly from 42.3% in 2010 to 14.6% in 2024, whereas the proportion among farmers increased from 23.6% to 54.4% (Figure 1D).

Figure 1. 

Temporal-spatial trends, seasonal patterns, and occupational distribution of MT-ZVL cases in endemic PLADs of China, 2010–2024, with incidence projections to 2030. (A) Time-trend analysis of incidence with observed, fitted, and predicted values of MT-ZVL. (B) Annual number of new indigenous cases and counties reporting cases of MT-ZVL. (C) Monthly distribution of MT-ZVL cases. (D) Heat map of the occupational distribution of MT-ZVL cases.

Note: “Observed” indicates the reported annual incidence (cases per million population) from the NNDRS; “Fitted” indicates the Joinpoint regression-based fitted trend; “Predicted” indicates the ARIMA model-based projected incidence for 2025–2030. Incidence was calculated as the number of reported cases per million population. In panel B, bars represent the number of newly reported cases, and the line represents the number of counties reporting at least one MT-ZVL case each year. In panel C, bars represent the monthly number of new cases, and the line represents the percentage of cases occurring in each month. In panel D, cell values show the proportion (%) of cases in each occupational category by year, calculated as (number of cases in a given occupation / total number of cases in that year) × 100; color intensity represents the absolute number of cases. Occupational codes (O01–O18) correspond to the standardized occupational classification used in NNDRS.

Abbreviation: MT-ZVL=mountain-type zoonotic visceral leishmaniasis; PLADs=provincial-level administrative divisions; CI=confidence interval; NNDRS=National Notifiable Diseases Reporting System.

Spatial autocorrelation analysis revealed significant clustering of MT-ZVL incidence in most years, particularly after 2020, with consistently positive Moran’s I values (Supplementary Table S2), indicating intensifying geographic aggregation. The SDE analysis demonstrated a significant northeastward shift of the mean center from (104.86°, 33.39°) to (111.89°, 36.40°) and the area enlarged from core regions in Gansu and Sichuan to Shaanxi, Shanxi, Henan, and Hebei. Directional anisotropy peaked in 2015–2019 (Ratio=7.32), indicating a pronounced corridor expansion, and declined in 2020–2024 (Ratio=3.42), suggesting a transition toward areal diffusion. The consistently stable orientation (62.82°–66.13°) reflected a persistent southwest–northeast expansion trajectory (Table 2).

This nationwide analysis demonstrates that the epidemiology of MT-ZVL in China has undergone a substantial transition over the past 15 years. The most notable findings include a shift in high-risk populations from scattered children to farmers and older adults, a clear reversal in incidence trends after 2015, and persistent spatial clustering with geographic expansion into previously unaffected areas. Together, these patterns reflect evolving transmission dynamics and mounting challenges for disease control. Historically, MT-ZVL in China disproportionately affected young children, likely due to peri-domestic exposure to P. chinensis. Our findings indicate a declining proportion of cases among scattered children and a growing burden among farmers, who now represent the primary high-risk group. This shift may be driven by sustained occupational exposure to P. chinensis habitats linked to agricultural activities, livestock shelters, and rural living environments (6). The increasing incidence among older adults further suggests cumulative exposure and potential age-related susceptibility. Similar occupational risk patterns have been reported in other endemic regions globally, where rural and agricultural populations bear the highest disease burden (7). However, the underlying causes of this epidemiological shift remain unclear; further studies are therefore needed to clarify the determinants of these changes and to inform more targeted control interventions. The observed resurgence of MT-ZVL after 2015 suggests that earlier control gains have not been fully sustained (4,8). Multiple factors may contribute to this resurgence, including reduced intensity of vector and reservoir control, ecological changes, rural land-use transformation, and increased human mobility (8–9). The pronounced seasonal peak from spring to summer aligns with P. chinensis activity and highlights the importance of timely, preseason interventions for vector control (10). Forecasting results underscore the likelihood of continued resurgence in the absence of strengthened, targeted control measures.

Spatial analyses revealed persistent clustering of MT-ZVL incidence that has intensified in recent years. Although some years exhibited weaker spatial dependence, this pattern likely reflects low overall incidence or sporadic case distribution rather than a genuine absence of clustering. The northeastward expansion indicates that MT-ZVL transmission is no longer confined to traditional endemic foci (3). These findings underscore the urgent need to extend surveillance and control efforts to newly affected areas and to allocate resources strategically based on spatiotemporal risk patterns.

Based on these findings, several public health actions are warranted. Control strategies should prioritize farmers and older adults through targeted health education, personal protective measures, and improved access to early diagnosis and treatment. Integrated approaches that combine sustained vector surveillance, dog reservoir management, and rapid response to emerging hotspots are essential to interrupt transmission cycles. This study has several limitations, including potential underreporting in surveillance data, broad occupational classifications, and the absence of analyses of environmental and socioeconomic drivers. Furthermore, the role of other reservoir hosts, such as wild animals, was not assessed and may be underestimated. Nevertheless, the extended 15-year study period and nationwide coverage provide robust evidence to inform future public health practice and policy development.

The staff at Centers for Disease Control and Prevention and Institutes of Parasitic Diseases at all administrative levels throughout China for their invaluable assistance with data collection.