The underlying numerical data for Table 1.

Background
Scrub typhus, an overlooked vector-borne disease in mainland China, has shown shifting epidemiological patterns in recent decades, yet comprehensive assessments of its spatiotemporal trends and disease burden—including premature mortality quantified by years of potential life lost (YPLL)—remain limited. This study aimed to characterize the epidemiological trends, spatiotemporal patterns, and disease burden of scrub typhus in mainland China, with a focus on estimating YPLL.
Methods
Nationwide scrub typhus case data were extracted from the China Information System for Disease Control and Prevention (CISDCP). Time-series analysis, spatial autocorrelation analysis, and spatiotemporal clustering analysis (SaTScan) were performed, and years of potential life lost (YPLL) were calculated to explore the epidemiological characteristics and spatiotemporal patterns of the scrub typhus in China. Negative binomial regression analysis was used to explore the association between scrub typhus and environmental variables.
Results
There were 283273 cases and 103 deaths reported. 2006–2023, the average yearly incidence was 1.14 cases per 100,000 people. From 0.10 per 100,000 population in 2006 to 2.37 per 100,000 population in 2023, the annual incidence rose dramatically. In 2023, there were 1,150 impacted counties, up from 226 in 2006. Yunnan (84795), Guangdong (70 013), Guangxi (30147), Anhui (20492) and Jiangsu (16760) were the top five provinces in terms of reported cases, accounting for 78.44% of all scrub typhus cases. The disease, which was endemic in southern China from 2006 to 2009, has spread to every province, particularly in northernmost and western of China. October has the highest seasonal index (2.53), followed by July and August. The majority of affected groups were women (52.90%), farmers (76.11%), and those between the ages of 40 and 59 (39.98%). The percentage of cases involving those 60 and older rose from 22.83% in 2006 to 37.90% in 2023. Spatial autocorrelation analyses showed a significant positive spatial correlation for scrub typhus incidence in all years except 2006–2011, showing a clustering distribution. The LISA cluster maps showed “high-high” clusters expanding in southern China, and “low-low” clusters were growing in northern areas. The results of negative binomial regression model revealed significant positive effects of temperature with a 1-month lag (IRR = 1.17, p < 0.001), rainfall with a 2-month lag (IRR = 1.008, p = 0.002), NDVI (IRR = 1.07, p = 0.008), and incidence in neighboring provinces (IRR = 1.05, p = 0.013) on scrub typhus risk. YPLL analysis highlighted substantial mortality impacts, particularly the age groups among males that most contributed to the losses were 40–49 years and 0–4 years (28.32% and 27.99%, respectively), while the highest frequencies of YPLL among females were observed between 50 and 59 years old (40.97%) and 60–69 years old (21.27%).
Conclusions
Based on results, we recommend prioritizing surveillance and resource allocation to high-risk areas including Guangdong, Yunnan, Guangxi, and Fujian provinces, as well as emerging northern regions (e.g., Anhui, Shandong) exhibiting rapid geographic expansion. Health interventions should target farmers (particularly females) and adults aged ≥60 years in rural areas. Meanwhile, efforts should accelerate vaccine development for high-risk occupational groups. Vector control and prevention campaigns should be intensified during critical pre-peak windows: the outbreak peaked in October.