Abstract:Objective To analyze the spatial autocorrelation and temporal-spatial clustering characteristics of scarlet fever in Songjiang District of Shanghai from 2014 to 2020, to explore the high incidence areas and aggregation time of scarlet fever in Songjiang District, and to provide a scientific basis for scarlet fever prevention and control. Methods Descriptive epidemiology, spatial autocorrelation analysis and temporal-spatial scanning clustering analysis were used to analyze the epidemic data of scarlet fever in Songjiang District of Shanghai from 2014 to 2020. Results Totally 3,328 cases of scarlet fever were reported cumulatively in Songjiang Districtof Shanghaifrom 2014 to 2020, with an average annual reported incidence rate of 25.03/100,000. The incidence of scarlet fever showed obvious seasonal distribution, with two peaks in April-June and November-January of the next year. The cases were concentrated in the group aged 4-10 years, accounting for 89.12% of the total number of cases. Students and kindergarten children were the high risk groups of scarlet fever. The global spatial autocorrelation analysis showed that the incidence of scarlet fever in Songjiang District was positivelyspatiallycorrelated, and P<0.05. Local autocorrelation analysis displayed that the distribution of scarlet fever mainly presented the patterns of high-high, low-low and low-high. Hotspot analysis revealed that the clustering areas were concentrated in Jiuting Town in the northeast of Songjiang District, but the cold spots were mainly concentrated in the southwest of Songjiang District. Spatio-temporal scanning results revealed that the high-risk aggregation areas from 2014 to 2020 were mainly the central urban area and the northeast area, and the aggregation period was mainly in April-June or November-December, which was basically consistent with the peak incidence. Conclusion The incidence of scarlet fever in Songjiang District in 2014-2020 showed significant seasonality and temporal-spatial aggregation. The central urban area and streets/towns in the northeast area are the key areas for scarlet fever prevention and control.
高桂玲, 王超, 吕锡宏, 孙中兴, 姚霞菁. 2014—2020年上海市松江区猩红热时空分布特征分析[J]. 实用预防医学, 2023, 30(1): 16-20.
GAO Gui-ling, WANG Chao, LYU Xi-hong, SUN Zhong-xing, YAO Xia-jing. Temporal and spatial distribution characteristics of scarlet fever in Songjiang District of Shanghai, 2014-2020. , 2023, 30(1): 16-20.