Expanding mountain-type zoonotic visceral leishmaniasis in China: a multi-source data-driven investigation

Mountain-type zoonotic visceral leishmaniasis (MT-ZVL) is undergoing rapid re-emergence in central China and demonstrates significant potential for further dissemination. The aim of this study was to provide information on optimal control strategies by estimating the disease's current distribution and potential for spread into new areas.

We used a three-pronged approach: (1) active field surveillance in 57 potential-risk counties in 2022 to investigate the distribution of the Phlebotomus chinensis (P. chinensis) vector and canine infections based on serological positivity; (2) study of annual surveillance reports of P. chinensis distribution and canine infection in 42 counties in Henan, Shanxi and Beijing (2023-2024); and (3) passive surveillance via China's National Notifiable Disease Surveillance System (NNDSS) revealing 1137 human MT-ZVL cases for the 2019-2024 period. We constructed a database based on an innovative active/passive surveillance approach and applied the optimized ecological niche model based on incorporating environmental, biological (the P. chinensis vector and infectious canines) and socioeconomic covariates to predict the relative risk of transmission at the 1 × 1 km resolution across central China. Model performance was validated using 239 unique, geolocated human case occurrences (2022-2024). This allowed us to map the MT-ZVL risk and quantify the populations at-risk within stratified risk tiers.

The field surveillance across 20 of 57 potential MT-ZVL risk counties captured 7552 P. chinensis specimens (mean density: 13.7 sandflies/trap/night), with a high peak in Jiexiu County, Shanxi Province (499.8). In 14 counties with confirmed P. chinensis presence, canine infections were recorded in 9 counties giving a mean seroprevalence of 2.7% (44/1648), with the highest proportion at 16.2% (21/130) seen in Yuzhou County, Henan Province. Annual surveillance reports confirmed P. chinensis presence in 24 of 42 monitored counties, with seropositive canines in two counties. The final training dataset included the recorded findings of 270 P. chinensis sandflies, 224 infected canines and 213 human case records. Extreme gradient boosting demonstrated superior predictive performance for human MT-ZVL infection risk, significantly outperforming benchmark models, with the area under the curve (AUC) of 0.950 (95% CI: 0.921-0.979) in internal validation and 0.913 (95% CI: 0.886-0.940) in external validation. Model performance was further validated by 88.3% of indigenous cases occurring within predicted high-risk zones. These high-risk zones were concentrated in hilly terrain along the Taihang, Lvliang and Qinling Mountains-primarily in central-southern Shanxi, Hebei-Shanxi border regions, eastern Shaanxi and north-western Henan. This study identified 117 high-risk or very high-risk counties with a combined population of 19.24 million. Medium-risk areas were found to encompass surrounding regions across Shanxi, Shaanxi, Henan, eastern Gansu, central-western Hebei and western/northern Beijing (87 counties; 12.07 million residents), while low-risk zones covered 87 counties in eastern Gansu, northern Sichuan, north-western Henan and central Hebei mountains (15.35 million residents). The optimized multi-source data-driven model exhibited robust predictive performance, identifying 291 at-risk counties threatening about 46.67 million residents.

This study demonstrated MT-ZVL to be a significant public health threat with rapid expansion across central China. Key findings revealed unabated endemic transmission, with the presence of P. chinensis and infectious canines in non-endemic areas signifying new emerging foci. By the identification of specific regions at risk for MT-ZVL, an evidence base warranting heightened public health vigilance against potential transmission has been established. Surveillance for MT-ZVL in central China and targeted interventions are strongly recommended.

This work was supported by the National Natural Science Foundation of China (No. 32161143036, No. 82473688), National Key Research and Development Program (2021YFC2300800, 2024YFC2310902), the Three-Year Initiative Plan for Strengthening Public Health System Construction in Shanghai (2023-2025) (No. GWVI-11.1-12).