陈向阳, 张鹤美, 王大勇, 叶振淼, 汪若秋, 苏德华, 赵丽娜. 2016-2019年浙江省温州市梅毒疫情时空特征分析[J]. 疾病监测, 2021, 36(2): 172-176. DOI: 10.3784/jbjc.202008130277
引用本文: 陈向阳, 张鹤美, 王大勇, 叶振淼, 汪若秋, 苏德华, 赵丽娜. 2016-2019年浙江省温州市梅毒疫情时空特征分析[J]. 疾病监测, 2021, 36(2): 172-176. DOI: 10.3784/jbjc.202008130277
Chen Xiangyang, Zhang Hemei, Wang Dayong, Ye Zhenmiao, Wang Ruoqiu, Su Dehua, Zhao Lina. Spatiotemporal distribution of syphilis cases in Wenzhou, 2016–2019[J]. Disease Surveillance, 2021, 36(2): 172-176. DOI: 10.3784/jbjc.202008130277
Citation: Chen Xiangyang, Zhang Hemei, Wang Dayong, Ye Zhenmiao, Wang Ruoqiu, Su Dehua, Zhao Lina. Spatiotemporal distribution of syphilis cases in Wenzhou, 2016–2019[J]. Disease Surveillance, 2021, 36(2): 172-176. DOI: 10.3784/jbjc.202008130277

2016-2019年浙江省温州市梅毒疫情时空特征分析

Spatiotemporal distribution of syphilis cases in Wenzhou, 2016–2019

  • 摘要:
      目的  分析浙江省温州市2016 — 2019年梅毒疫情的时空分布特征,探测聚集区域,为梅毒防控提供理论依据。
      方法  利用ArcGIS 10.2软件作为数据管理和呈现的平台,建立温州市2016 — 2019年梅毒空间分析数据库,对梅毒疫情进行空间自相关分析,采用SaTScan 9.6软件进行时空扫描分析。
      结果  2016 — 2019年温州市共报告梅毒发病13 778例,纳入分析13 550例,年报告发病率为37.13/10万(0~365.14/10万),全局自相关结果显示梅毒疫情呈聚集性分布,局部自相关分析表明温州市南部有4个空间相近的高–高聚集区域(共18个乡镇);局部G统计量热点分析结果显示,温州市梅毒存在31个“正热点”和5个“负热点”区域;SaTScan时空扫描探测到7个聚集区域。
      结论  2016 — 2019年温州市梅毒报告发病率非随机分布,存在空间聚集性,疾病高发区应采取针对性措施控制梅毒疫情。

     

    Abstract:
      Objective  To analyze the spatiotemporal distribution of syphilis cases in Wenzhou from 2016 to 2019 and provide evidence for prevention and control of syphilis.
      Methods  Using software ArcGIS 10.2 as a platform for data management and presentation, a syphilis spatial distribution database in Wenzhou from 2016 to 2019 was established, and spatial autocorrelation analysis was performed based on the incidence of syphilis in Wenzhou during this period. Software SaTScan 9.6 was used for spatiotemporal scanning analysis.
      Results  From 2016 to 2019, a total of 13 778 syphilis cases were reported in Wenzhou, in which 13 550 were included in this analysis. The average annual incidence rate was 37.13/100 000 (range: 0–365.14/100 000). The results of global spatial autocorrelation analysis indicated that the distribution of syphilis cases showed clustering. The result of local Moran’s I autocorrelation analysis found 4 high-high clustering areas, covering 18 townships, in southern Wenzhou. Result from the Getis-Ord General G spatial autocorrelation analysis showed 31 “positive hot spots” and 5 “negative hot spots”. Using software SaTScan 9.6, results from the Phased spatial-temporal analysis identified 7 clustering areas.
      Conclusion  From 2016 to 2019, the incidence of syphilis in Wenzhou was not randomly distributed but showed temporal-spatial clustering. It is necessary to take targeted syphilis prevention and control measures in areas at high risk.

     

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