南方医科大学学报

南方医科大学学报 ›› 2023, Vol. 43 ›› Issue (4): 644-648.doi: 10.12122/j.issn.1673-4254.2023.04.19

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2016~2020年中国猩红热发病的空间聚集性分析

张佳豪，杨若男，贺舒凝，袁 萍   

  1. 四川大学华西公共卫生学院//华西第四医院流行病与卫生统计学系，四川 成都 610041
  • 出版日期:2023-04-20 发布日期:2023-05-16

Spatial clustering analysis of scarlet fever incidence in China from 2016 to 2020

ZHANG Jiahao, YANG Ruonan, HE Shuning, YUAN Ping   

  1. Department of Epidemiology and Health Statistics/West China Fourth Hospital and West China School of Public Health, Sichuan University, Chengdu 610041, China
  • Online:2023-04-20 Published:2023-05-16

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摘要： 目的 探讨我国2016~2020年猩红热的发病率趋势以及空间聚集特征，为合理制定区域性疾病防控策略与措施提供依据。方法 通过《中国卫生健康统计年鉴》和中国疾病预防控制中心牵头负责的公共卫生科学数据中心获取2016～2020年我国31个省份及直辖市（不包括港澳台）的猩红热发病率数据，应用ArcGIS绘制了我国猩红热发病的三维空间趋势图，判断猩红热发病的地区变化趋势，采用GeoDa空间自相关分析探索我国近年来猩红热的空间聚集情况。结果 2016~2020年全国31个省份（直辖市、自治区）累积报告猩红热病例310816例，年平均发病率为4.48/10万。报告发病率从2016年的4.32/10万下降到2020年的1.18/10万（Z=103.47，P<0.001）。2016~2019年，我国猩红热发病存在较为明显的地区聚集特征（Moran's I>0，P<0.05），2020年我国猩红热发病呈随机分布（Moran's I>0，P=0.16），东西部地区呈“U”型分布，中间低两边高，由南向北逐渐升高。内蒙古、河北以及甘肃等北部地区为我国猩红热发病的高-高（H-H）聚集区域。结论 我国猩红热发病仍有较高的发病率，且发病存在较为明显的空间聚集性，应针对猩红热发病呈现H-H聚集的北部地区，适当地增加卫生资源配置和相应的健康宣传教育力度，制定区域化的猩红热防控政策，防止猩红热热点区域的扩大。

关键词: 猩红热；流行趋势；空间流行病学；自相关分析

Abstract: Objective To investigate the incidence trend and spatial clustering characteristics of scarlet fever in China from 2016 to 2020 to provide evidence for development of regional disease prevention and control strategies. Methods The incidence data of scarlet fever in 31 provinces and municipalities in mainland China from 2016 to 2020 were obtained from the Chinese Health Statistics Yearbook and the Public Health Science Data Center led by the Chinese Center for Disease Control and Prevention. The three-dimensional spatial trend map of scarlet fever incidence in China was drawn using ArcGIS to determine the regional trend of scarlet fever incidence. GeoDa spatial autocorrelation analysis was used to explore the spatial aggregation of scarlet fever in China in recent years. Results From 2016 to 2020, a total of 310 816 cases of scarlet fever were reported in 31 provinces, municipalities directly under the central government and autonomous regions, with an average annual incidence of 4.48/100 000. The reported incidence decreased from 4.32/100 000 in 2016 to 1.18/100 000 in 2020 (Z=103.47, P<0.001). The incidence of scarlet fever in China showed an obvious regional clustering from 2016 to 2019 (Moran's I>0, P<0.05), but was randomly distributed in 2020 (Moran's I>0, P=0.16). The incidence of scarlet fever showed a U-shaped distribution in eastern and western regions of China, and increased gradually from the southern to northern regions. Inner Mongolia Autonomous Region and Hebei and Gansu provinces had the High-high (H-H) clusters of scarlet fever in China. Conclusion Scarlet fever still has a high incidence in China with an obvious spatial clustering. For the northern regions of China with H-H clusters of scarlet fever, the allocation of health resources and public health education dynamics should be strengthened, and local scarlet fever prevention and control policies should be made to contain the hotspots of scarlet fever.

Key words: scarlet fever; epidemic trend; spatial epidemiology; autocorrelation analysis