Objective To analyze the distribution characteristics,spatial and spatiotemporal clustering of scrub typhus in Shandong Province,China,and to identify high-risk areas,so as to provide scientific information for developing scrub typhus prevention and control strategies and measures.Methods Descriptive epidemiological methods,spatial autocorrelation analysis,and spatiotemporal clustering were used to analyze the spatiotemporal distribution characteristics of scrub typhus in Shandong Province from 2006 to 2021,and identified high-risk areas.ArcGIS 10.8 software was used to visualize the results.Results A total of 10 207 cases were reported in Shandong Province during 2006-2021,with a mean annual incidence rate of 0.64/100 000,and the incidence rate increased first and then decreased.Unimodal distributions were observed in the cases with respect to age(concentrated in 40-<80 years)and seasonality(peaking in October to November).By occupation,most of the patients were farmers.The global Moran's I index of the annual incidence rate of scrub typhus was 0.203-0.676(all P<0.05),indicating a positive spatial correlation at the district/county level.The local autocorrelation analysis results showed that high-high cluster areas mainly included Laiwu District and Gangcheng District of Jinan,Xintai City of Tai'an,Yishui County of Linyi,and Ju County and Wulian County of Rizhao.The spatial scan analysis results showed that the cases were spatially clustered,and the spatial clusters tended to expand from the central to the southern and eastern parts of Shandong Province from 2006 to 2021.The spatiotemporal scan analysis detected a spatiotemporal cluster area with a high incidence rate,which centered around Donggang District of Rizhao,with a radiation radius of 199.11 km,from October 2014 to November 2017(risk ratio=8.24,log-likelihood ratio=4 107.176,P<0.01).Conclusions From 2006 to 2021,the incidence of scrub typhus in Shandong Province first increased and then decreased,with significant spatiotemporal clustering,and high-incidence cluster areas had been expanding continuously.Effective measures should be taken for key populations in high-incidence regions and seasons.
Scrub typhusSpatiotemporal clusteringSpatial autocorrelationEpidemiological research
NETL
NSTL
万方数据
