Vital Surveillances: The Spatiotemporal Epidemiology and Influencing Factor Analysis of Leptospirosis — Anhui Province, China, 2004–2023

Surveillance data of leptospirosis from January 2004 to December 2023 in Anhui Province, including both clinically diagnosed and laboratory-confirmed cases based on the Diagnostic Criteria for Leptospirosis (WS 2902008), were obtained from the CISDCP. The data included comprehensive demographic information such as age, gender, occupation, residential address, and date of illness onset for all leptospirosis patients. Demographic data for Anhui Province were obtained from the National Bureau of Statistics of China.

A descriptive analysis of county-level surveillance data was conducted to characterize the epidemiological features of leptospirosis. Spatiotemporal scanning analyses were performed using SaTScan (version 9.6, Information Management Services, Maryland, USA) based on spatial dynamic window scanning methodology. Relative risk (RR) and log-likelihood ratio (LLR) were calculated to quantify the elevated risk within scanning windows compared to areas outside these windows. The scanning window with the highest LLR value was designated as the primary cluster, while other windows with statistically significant LLRs were classified as secondary clusters. To investigate potential risk factors and their short-term effects on leptospirosis incidence, Spearman correlation analysis was conducted between local precipitation, temperature, normalized difference vegetation index (NDVI) and reported leptospirosis cases in two high-risk counties (Huaiyuan and Jingde) from 2004 to 2023 using SPSS (version 22.0, IBM Corp., Armonk, NY, USA). Monthly climatic data were obtained from the National Tibetan Plateau Data Center (https://data.tpdc.ac.cn/). Monthly NDVI data were sourced from the National Aeronautics and Space Administration (https://www.nasa.gov/). All statistical analyses were performed using SPSS, and circular heatmaps were generated using chiplot (https://www.chiplot.online/). Results were considered statistically significant when P values were less than 0.05.

From 2004 to 2023, a total of 458 cases from 45 counties were reported in Anhui, with an annual average incidence rate of 0.037 per 100,000 population (Figure 1). Overall, leptospirosis incidence remained low throughout the study period, with notable spikes occurring in 2007, 2008, 2010, 2016, and 2021. Annual incidence rates fluctuated between 0.01 and 0.09 per 100,000 population.

Figure 1. 

Annual distribution of leptospirosis cases in Anhui Province, China, 2004–2023.

Leptospirosis cases were documented across all age groups, with the highest prevalence observed among adults aged 40–59 years (n=222, 48.47%). Farmers constituted the predominant occupational category (n=405, 88.43%), followed by students (n=15, 3.28%). The male-to-female ratio was 2.14∶1. Leptospirosis cases were reported in every month except February, with August and September (n=349, 76.20%) representing the primary peak season annually, demonstrating distinct single-peak seasonal characteristics (Figure 2).

Figure 2. 

The monthly reported cases of leptospirosis in Anhui Province, China, 2004–2023，(A) Monthly distribution of leptospirosis cases each year; (B) Circular heatmap of the proportion of monthly leptospirosis cases each year.

Note: The order of the circles from the inside to the outside is represented 2004–2023.

Significant spatial heterogeneity was observed in the distribution of leptospirosis cases across counties in Anhui Province between 2004–2023, with Huaiyuan and Jingde emerging as the two highest-risk counties based on cumulative case numbers over the 20-year period (Supplementary Table S1). Multiple small-scale outbreaks occurred throughout this timeframe. Jingde County reported the highest incidence rates of 14.49, 8.98, and 15.26 per 100,000 population, accounting for 38.89%, 25.00%, and 46.81% of all Anhui cases in 2007, 2008, and 2010, respectively. Huaiyuan County subsequently emerged as a major hotspot, with incidence rates of 4.12 and 2.89 per 100,000 population, representing 85.11% and 72.97% of total provincial cases in 2016 and 2021, respectively. Spatiotemporal scan analysis revealed non-random distribution of leptospirosis across geographical areas and time periods, identifying one most likely cluster and one secondary cluster (Table 1). The most likely cluster was concentrated in the southern mountainous areas, encompassing 9 adjacent counties (Qimen, Yixian, Huangshan, Jingde, Jixi, Xiuning, Tunxi, Huizhou, and Shexian) from 2004–2012 (LLR=737.62, RR=88.06, P<0.001). The secondary cluster was localized to Huaiyuan in the northern Huaihe River Basin from 2016–2021 (LLR=330.76, RR=65.60, P<0.001).

Based on the results of Spearman correlation analysis in Huaiyuan and Jingde, significantly positive correlations were observed between the numbers of reported case and average temperature, maximum temperature, and minimum temperature at lag periods of 0–3 and 6 months (P<0.05) (Table 2). Positive correlations were identified between leptospirosis and NDVI at lag periods of 0–1, 4, and 5 months in Huaiyuan, and at lag periods of 0–3, 5, and 6 months in Jingde, respectively (P<0.05) (Table 2). Similarly, positive correlations were observed between leptospirosis and rainfall at lag periods of 0–3 and 6 months in Huaiyuan, and at lag periods of 1–4 months in Jingde (P<0.05) (Table 2).

In this study, we analyzed the epidemiological characteristics and spatiotemporal patterns of leptospirosis in Anhui Province from 2004 to 2023, and explored potential climatic and environmental factors influencing disease transmission in high-risk regions. Throughout the 20-year study period, leptospirosis maintained a generally low incidence with significant spatial heterogeneity. Our findings suggest that temperature, rainfall, and NDVI may play substantial roles in driving increased leptospirosis incidence in Huaiyuan and Jingde Counties. This represents the first comprehensive analysis based on an extensive surveillance dataset to elucidate the predominant spatiotemporal patterns, identify key high-risk regions, and determine potential risk factors for leptospirosis in Anhui Province.

The significantly higher incidence among males compared to females in Anhui aligns with previous epidemiological studies (3-4). Middle-aged adults (40–59 years), males, and farmers — who constitute the primary local workforce — face elevated exposure risk to Leptospira-contaminated environments through activities such as rice harvesting, livestock management, fishing, and swimming (4,6). These findings underscore the necessity for enhanced health education targeting these vulnerable populations, particularly in rural communities. Our analysis revealed a distinct single-peak seasonal pattern of leptospirosis transmission, consistent with previous studies in Anhui (7). This peak coincides with the agricultural harvesting season and periods of high rainfall, further supporting the relationship between environmental conditions and disease transmission.

In this study, significant spatial heterogeneity was revealed. The high-incidence regions were predominantly concentrated in the southern mountainous areas and the northern Huaihe River Basin. Anhui, as a significant epidemic region, is traversed by both the Yangtze and Huaihe Rivers. The abundant rainfall, moist subtropical climate, and diverse host animal populations provide favorable environmental conditions for leptospirosis transmission. Notably, nine adjacent counties in the southern mountainous areas of Anhui formed the most likely high-risk cluster during 2004–2012, but the hotspots subsequently shifted to Huaiyuan in the northern Huaihe River Basin during 2016–2021. Rodents constituted the primary reservoir hosts in both high-risk regions of Huaiyuan and Jingde. The increased leptospirosis morbidity in Huaiyuan may be attributed to higher rodent densities and carrier rates, altered rodent species composition, and expanded rice cultivation areas (8-10). Three critical risk factors — rodent density exceeding 15%, rodent carrier rate exceeding 15%, and antibody levels against leptospirosis in the local population below 15% — precipitated the 2016 leptospirosis outbreak in Huaiyuan (7). Mechanized harvesting practices may have concurrently reduced human contact with contaminated environments in recent years (4). Consequently, more targeted control efforts are needed in these high-risk areas through enhanced epidemiological surveillance, promotion of protective equipment (rubber boots and gloves), and implementation of leptospirosis immunization when warranted.

Significant associations between leptospirosis, and climatic and environmental risk factors — including average humidity, precipitation, temperature, and difference water index — have been documented in previous research, though the reported lag effects vary considerably from weeks to months or even years (1,11). Our results demonstrate that the numbers of reported cases were significantly associated with temperature, rainfall, and NDVI in the two high-risk counties of Huaiyuan and Jingde. The strongest positive correlations were observed between leptospirosis and concurrent NDVI, with local temperature and rainfall showing strongest associations at a one-month lag in Huaiyuan. Compared to July measurements in 2015 and 2020, Huaiyuan experienced substantial rainfall increases of 47.06% and 19.83% in 2016 and 2021, respectively. The lagged effects of local precipitation likely constituted the primary risk factor for subsequent leptospirosis outbreaks in Huaiyuan, consistent with findings from Lezhi, China (12). Humid and warm conditions favor Leptospira survival, increase animal reservoir abundance, and facilitate environmental transmission of the pathogen. NDVI correlates with vegetation cover, livestock grazing patterns, animal reservoir abundance, and agricultural activities. Therefore, systematic monitoring and early-warning systems, coupled with locally-tailored intervention measures, are essential to reduce the burden of leptospiral infection in Huaiyuan.

In summary, our findings revealed significant spatial heterogeneity and distinct spatiotemporal clustering of leptospirosis in Anhui Province from 2004 to 2023. These results provide important insights for characterizing high-risk areas and strengthening ongoing surveillance and control efforts. However, this study has several limitations. Potential socioeconomic factors, host animal density, and Leptospira-carrying rates that may influence leptospirosis transmission were not included in the analysis. Additional risk factors should be explored in future investigations.