Zheng F, Sun Y Q, Zhang H X, Zhang H B, He B H, Jia Z Y, Li Q
School of Public Health, North China University of Science and Technology, Tangshan 063210, China.
Hebei Provincial Center for Disease Control and Prevention, Hebei Key Laboratory of Pathogens and Epidemiology of Infectious Diseases, Shijiazhuang 050021, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2024 Feb 10;45(2):213-219. doi: 10.3760/cma.j.cn112338-20230811-00064.
To analyze the spatial-temporal epidemiological characteristics of pertussis from 2013 to 2022 in Hebei Province and to provide a reference for improving prevention and control measures. Based on the data of pertussis reported in Hebei Province during 2013-2022 to analyze the popular characteristic, the ArcGIS 10.8 software was used to construct a ring map and to perform spatial autocorrelation analysis; the SaTScan 10.1 software was used for spatial-temporal scan statistics. There were 6 715 cases of the cumulative report in Hebei Province from 2013 to 2022 without death. The annual report incidence was 0.90/100 000. The overall incidence rate showed an upward trend from 2013 to 2019, and during 2020-2021, it showed a sharp decline, but in 2022, it showed a sharp increase. Summer and autumn are the peak seasons of the epidemic. The incidence was highest in age group <1 year (48.67%), and the lowest age group in age group ≥15 years (0.45%) and mainly scattered children (78.03%); the incidence about men is higher than women. Spatial autocorrelation analysis showed that the onset of pertussis has spatial clustering, and high-high clusters were found in Langfang, Baoding, and Cangzhou, the top three countries with reported incidence. The area covered by a low-low cluster was consistent with the distribution of the corresponding low-incidence areas in this study. Space-time scan detects five statistically significant areas, and three zones were concentrated in 2022. The incidence of pertussis in Hebei had obvious season, population, and area-specific differences. There was obvious spatiotemporal and clustering, so the control of key areas should target the characteristics of time and space.
分析2013年至2022年河北省百日咳的时空流行病学特征,为完善防控措施提供参考。基于2013—2022年河北省报告的百日咳数据,分析流行特征,运用ArcGIS 10.8软件绘制环形图并进行空间自相关分析;运用SaTScan 10.1软件进行时空扫描统计分析。2013年至2022年河北省累计报告6 715例,无死亡病例。年报告发病率为0.90/10万。总体发病率在2013年至2019年呈上升趋势,2020—2021年呈急剧下降,但2022年又急剧上升。夏秋季节是发病高峰。发病年龄以<1岁组最高(48.67%),≥15岁组最低(0.45%),以散居儿童为主(78.03%);男性发病率高于女性。空间自相关分析显示,百日咳发病存在空间聚集性,报告发病率前三位的廊坊、保定和沧州存在高高聚集区。低低聚集区覆盖范围与本研究中相应低发区分布一致。时空扫描检测到5个具有统计学意义的区域,其中3个区域集中在2022年。河北省百日咳发病具有明显的季节、人群和地区差异,存在明显的时空聚集性,应针对时空特征对重点地区进行防控。