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张倩, 陈旭光, 胡建雄, 容祖华, 朱志华, 程明基, 李剑森, 殷李华, 赵建国, 唐烨榕, 周燕, 李懿涵, 全意, 马文军, 肖建鹏, 吴为. 广州市一起新冠肺炎暴发疫情时空聚集性[J]. 中国公共卫生, 2022, 38(8): 980-984. DOI: 10.11847/zgggws1137165
引用本文: 张倩, 陈旭光, 胡建雄, 容祖华, 朱志华, 程明基, 李剑森, 殷李华, 赵建国, 唐烨榕, 周燕, 李懿涵, 全意, 马文军, 肖建鹏, 吴为. 广州市一起新冠肺炎暴发疫情时空聚集性[J]. 中国公共卫生, 2022, 38(8): 980-984. DOI: 10.11847/zgggws1137165
ZHANG Qian, CHEN Xu-guang, HU Jian-xiong, . Spatial-temporal clustering of cases in a COVID-19 outbreak in Guangzhou city[J]. Chinese Journal of Public Health, 2022, 38(8): 980-984. DOI: 10.11847/zgggws1137165
Citation: ZHANG Qian, CHEN Xu-guang, HU Jian-xiong, . Spatial-temporal clustering of cases in a COVID-19 outbreak in Guangzhou city[J]. Chinese Journal of Public Health, 2022, 38(8): 980-984. DOI: 10.11847/zgggws1137165

广州市一起新冠肺炎暴发疫情时空聚集性

Spatial-temporal clustering of cases in a COVID-19 outbreak in Guangzhou city

  • 摘要:
      目的  以广东省广州市一起新冠肺炎本土暴发疫情为例,定量评估不同时空界值下新冠肺炎疫情的传播风险及时空聚集强度,以期为疫情防控措施的制定提供依据。
      方法  收集2020年4 — 5月广州市新冠肺炎疫情的病例报告数据,描述分析本次疫情的时间、空间、人群分布特征,采用Knox时空聚集性分析方法,通过设置不同的时间界值(0~14 d,间隔1 d)和空间界值(0~1000 m,间隔 100 m),分析暴发疫情的感染风险(RR)和聚集强度,并对不同性别和不同年龄组病例对子的时空聚集性进行深入分析。
      结果  聚集性分析结果显示,新冠肺炎感染风险和聚集强度随时间间隔 、空间距离的增加而降低。在时间间隔为1 d,空间距离最近时RR值最高。病例对子在时间间隔1 d、空间距离为100 m处 RR 值为 2.4,距离达 3 km时 RR 值降为 1.2。从性别组合看,男 – 男病例对子在1~5 d( < 300 m)时空聚集性较强,而女 – 女、男 – 女病例对子分别在1~7 d( < 400 m)和1~4 d( < 500 m)时空聚集性较强。女 – 女病例对子总的时空聚集强度高于男 – 男病例对子。从年龄组来看,儿童 – 儿童病例对子在间隔1 d内的时空聚集强度明显高于其他组合,中青年 – 中青年病例对子在1~5 d( < 300 m)聚集性较强。
      结论  本次广州市新冠肺炎本土暴发疫情提示,病例对子时空聚集性较强,不同性别、年龄组病例对子的时空聚集性有所差异。

     

    Abstract:
      Objective   To explore spatial-temporal clustering of coronavirus disease 2019 (COVID-19) cases in an outbreak epidemic in Guangzhou city, Guangdong province and to provide evidences for developing COVID-19 prevention and control measures.
      Methods  The data on 215 local COVID-19 cases reported in Guangzhou city from April 4 to May 2, 2020 were collected and the cases′ demographics and spatial-temporal distribution were described statistically. Knox test was used to identify possible spatial-temporal clustering of the cases by given specific critical thresholds. The spatial thresholds for the distance between the two cases′ residential address were set varying from 0 to 1000 meters (m) with an interval of 100 m; the temporal thresholds for the time interval between the two cases′ incident time were set varying from 1 to 15 days with an interval of 1 day. The strength of clustering (S-value) and relative risk (RR) of clustering for each gender- and age-group-specific case pair were calculated to analyze temporal-spatial clustering of case pairs.
      Results  The S-value and RR of the COVID-19 case pairs decreased with the increment in pairs′ spatial distance and time interval. The RR value was the highest for a pair with the nearest spatial distance under the interval time of 1 day. For a case pair with the time interval of 1 day, the RR was 2.4 when the spatial distance between the pair′s two cases being 100 m, while the RR was only 1.2 when the spatial distance being 3 kilometers (km). For male-male pairs, the S-value was higher under the time interval of 1 – 5 days with a spatial distance less than 300 m; for female-female pairs, the S-value was higher under the time interval of 1 – 7 days with a spatial distance less than 400 m; and for male-female pairs, the S-value was higher under the time interval of 1 – 4 days with a spatial distance less than 500 m. A stronger trend of spatial-temporal clustering was observed among female-female case pairs than among male-male case pairs. For age-group-specific case pairs, the S-value of child-child pairs with the time interval of 1 day was significantly higher than that of other age-group pairs and the S-value of middle-aged-youth pairs was higher under the time interval of 1 – 5 days with a spatial distance of less than 300 m.
      Conclusion  Spatial-temporal clustering with between gender and age group differences was observed among the COVID-19 cases of an outbreak epidemic in Guangzhou city.

     

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