Spatiotemporal distribution of newly diagnosed echinococcosis patients in Sichuan Province, China, 2013-2024.

backgroundEchinococcosis is a zoonotic parasitic disease that significantly endangers public health and hinders socioeconomic development. Sichuan Province is a mixed endemic area of cystic echinococcosis (CE) and alveolar echinococcosis (AE), and it has one of the most severe epidemics of echinococcosis in China. In 2012, the national epidemiological sampling survey of echinococcosis revealed that the prevalence rate of echinococcosis among the population in Sichuan Province was 1.08%, significantly higher than the national average (0.24%). In this study, the spatiotemporal distribution characteristics of newly diagnosed patients with echinococcosis in Sichuan Province from 2013 to 2024 were analyzed, providing a reference for identifying key areas of echinococcosis and developing targeted prevention and control strategies.

methodsData on the number of individuals screened for echinococcosis and the number of newly diagnosed patients in endemic counties were obtained from the annual reports of the Sichuan Provincial Echinococcosis Control Program between 2013 and 2024. The detection rate of newly diagnosed echinococcosis patients was calculated for each year. County-level electronic maps of Sichuan Province were downloaded from the National Geographic Information Public Service Platform. The spatial distribution map of the detection rate of newly diagnosed patients with echinococcosis in Sichuan Province was created using ArcGIS software, and global and local spatial autocorrelation analyses were conducted. Spatiotemporal scanning analysis of the detection rate of newly diagnosed echinococcosis patients in Sichuan Province was conducted using SaTScan software.

resultsFrom 2013 to 2024, the total detection rate of newly diagnosed patients with echinococcosis in the endemic areas of Sichuan Province was 55.77/100,000, with the detection rates of CE and AE being 36.71/100,000 and 19.88/100,000, respectively. The total detection rate of newly diagnosed patients with echinococcosis, as well as that of CE and AE, demonstrated a decreasing trend year by year (χ2 = 1,054.785, 925.936, 196.018; P < 0.001). The detection rate of CE was higher than that of AE between 2013 and 2021; however, this trend was reversed between 2022 and 2024. In terms of spatial distribution, areas with higher detection rates were primarily concentrated in the northwestern part of Sichuan Province, whereas areas with lower detection rates were mainly distributed in the southeastern part of the province. The global spatial autocorrelation analysis results revealed that the total detection rate of newly diagnosed echinococcosis patients exhibited spatial clustering in 2013-2016, 2018, 2020, and 2024. The detection rate of newly diagnosed CE patients exhibited spatial clustering in 2013, 2014, and 2022. The detection rate of newly diagnosed patients with AE exhibited spatial clustering in 2013-2018, 2020, and 2023. Local spatial autocorrelation analyses revealed that the "high-high" clustering areas of the total detection rates, CE and AE detection rates were concentrated in the northwestern and northern parts of the endemic areas, while the "low-low" clustering areas were concentrated in the southeastern parts of the endemic areas. Spatiotemporal scanning analysis revealed that the most important clusters of newly total diagnosed echinococcosis and CE patients in Sichuan Province were mainly located in Shiqu, Seda, Baiyu, Ganzi, Dege, Xinlong, Luhuo, Aba, and Rangtang counties. The most important clusters of patients with AE were mainly in Shiqu, Seda, Baiyu, Ganzi, Dege, and Rangtang counties.

conclusionThe results demonstrated that the detection rate of newly diagnosed patients with echinococcosis in Sichuan Province decreased annually between 2013 and 2024, exhibiting significant spatial clustering. The western Sichuan Qinghai Tibet Plateau region is a "hot spot" for echinococcosis in the Sichuan Province population. It is recommended that relevant departments develop precise prevention and control strategies for the current areas of clustering.