Journal of Shandong University (Health Sciences) ›› 2020, Vol. 58 ›› Issue (10): 66-73.doi: 10.6040/j.issn.1671-7554.0.2020.0746

Previous Articles     Next Articles

Epidemic characteristics and spatial analysis of COVID-19 in Zhejiang Province

JIA Yan1, LI Chunyu1, LIU Lili1, SHE Kaili1, LIU Tingxuan1, ZHU Yuchen1, QI Chang1, ZHANG Dandan1, WANG Xu1, CHEN Enfu2, LI Xiujun1   

  1. 1. Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China;
    2. Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, Zhejiang, China
  • Published:2020-10-08

PDF (PC)

351

Abstract: Objective To explore the temporal and spatial distribution characteristics of confirmed cases of coronavirus disease(COVID-19)in Zhejiang Province and to determine the correlation between number of confirmed cases and geographical demographic factors, so as to provide theoretical basis for the prevention and control of COVID-19. Methods Data of COVID-19 cases confirmed during Jan. 21 and Feb. 19, 2020 in Zhejiang Province were collected. The demographic, temporal and spatial distribution characteristics and exposure history were descriptively analyzed. With county as a unit, the spatial autocorrelation was analyzed, and 11 cities were classified with hierarchical clustering. The correlation between number of confirmed cases and geographical demographic factors was determined with Spearman rank correlation analysis. Results 71.44%(848 cases)of the patients were aged 18-60 years, and there was no statistically significant difference between the sexes(P=0.742). The number of daily confirmed new cases reached the peak around Jan. 29 in various cities. After Jan. 30, The majority of daily confirmed new cases had exposure history of other areas. The confirmed cases in various counties and districts of Zhejiang Province showed characteristic of spatial clustering, and the clustering hotspots were some counties of Wenzhou and Taizhou City. The 11 cities were classified into 4 categories: Wenzhou; Ningbo; Hangzhou and Taizhou; other cities. Population size moving in from Wuhan was positively correlated with the number of cases(rs=0.93, P<0.001). Conclusion In the early stage of COVID-19 epidemic, the majority of cases had exposure history of Hubei; in the later stage, reported cases were mainly secondary cases. Clustering hotspots were some counties of Wenzhou and Taizhou City. Currently, the prevention and control of the epidemic in Zhejiang Province has been effective. It is necessary to continue implementing control measures to prevent the outbreak from rebounding in high-risk areas, and to actively respond to the epidemic risk caused by return to work and school. In addition, people from high-risk areas should be strictly monitored and managed.

Key words: Coronavirus disease 2019, Zhejiang Province, Epidemiological characteristics, Spatial autocorrelation, Cluster analysis

CLC Number: 

  • R181.3
[1] Zaki AM, van Boheemen S, Bestebroer TM, et al. Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia [J]. N Engl J Med, 2012, 367(19): 1814-1820.
[2] 武汉市卫生健康委员会. 武汉市卫健委关于当前我市肺炎疫情的情况通报[EB/OL].(2019-12-31)[2020-05-24]. http://wjw.wuhan.gov.cn/xwzx_28/gsgg/202004/t20200430_1199576.shtml.
[3] Zhu N, Zhang D, Wang W, et al. A novel coronavirus from patients with pneumonia in China, 2019 [J]. N Engl J Med, 2020, 382(8): 727-733.
[4] Lipsitch M, Cohen T, Cooper B, et al. Transmission dynamics and control of severe acute respiratory syndrome [J]. Science, 2003, 300(5627): 1966-1970.
[5] Riley S, Fraser C, Donnelly CA, et al. Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions [J]. Science, 2003, 300(5627): 1961-1966.
[6] Breban R, Riou J, Fontanet A. Interhuman transmissibility of Middle East respiratory syndrome coronavirus: estimation of pandemic risk [J]. Lancet, 2013, 382(9893): 694-699.
[7] Chowell G, Abdirizak F, Lee S, et al. Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study [J]. BMC Med, 2015, 13:210. doi: 10.1186/s12916-015-0450-0.
[8] Zumla A, Hui DS, Perlman S. Middle East respiratory syndrome [J]. Lancet, 2015, 386(9997): 995-1007.
[9] Donnelly CA, Ghani AC, Leung GM, et al. Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong [J]. Lancet, 2003, 361(9371): 1761-1766.
[10] Chan JF, Yuan S, Kok KH, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster [J]. Lancet, 2020, 395(10223): 514-523.
[11] Li Q, Guan X, Wu P, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia [J]. N Engl J Med, 2020, 382(13): 1199-1207.
[12] World Health Organization(WHO). Coronavirus disease 2019(COVID-19)Situation Report-30 [EB/OL].(2020-02-19)[2020-04-20]. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports.
[13] 刘张, 千家乐, 杜云艳, 等. 基于多源时空大数据的区际迁徙人群多层次空间分布估算模型——以COVID-19疫情期间自武汉迁出人群为例[J]. 地球信息科学学报, 2020, 22(2): 147-160.
[14] 苏理云, 郭雯. 中国各省新型冠状病毒肺炎累计确诊人数的空间聚集及时空格局演变分析[J]. 重庆理工大学学报(自然科学), 2020, 34(4): 51-58, 65.
[15] Fan J, Liu X, Pan W, et al. Epidemiology of Coronavirus Disease in Gansu Province, China, 2020 [J]. Emerg Infect Dis, 2020, 26(6): 1257-1265.
[16] Weiming T, Huipeng L, Gifty M, et al. The changing patter of COVID-19 in China: A tempo-geographic analysis of the SARS-CoV-2 epidemic [J]. Clin Infect Dis, 2020, 71(15):818-824.
[17] 浙江省统计局. 2019年浙江统计年鉴 [EB/OL].(2019-09)[2020-04-20]. http://tjj.zj.gov.cn/col/col1525563/index.html.
[18] 武汉市新型冠状病毒感染的肺炎疫情防控指挥部. 武汉市新型冠状病毒感染的肺炎疫情防控指挥部通告(第1号)[EB/OL].(2020-01-23)[2020-04-25]. http://www.hubei.gov.cn/zhuanti/2020/gzxxgzbd/zxtb/202001/t20200123_2014402.shtml.
[19] 百度地图慧眼. 百度迁徙-百度地图慧眼[EB/OL].(2020-01-22)[2020-04-10]. https://qianxi.baidu.com/?from=shoubai.
[20] Tsai PJ, Lin ML, Chu CM, et al. Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006 [J]. BMC Public Health, 2009, 9: 464. doi:10.1186/1471-2458-9-464.
[21] Mao Q, Zeng C, Zheng D, et al. Analysis on spatial-temporal distribution characteristics of smear positive pulmonary tuberculosis in China, 2004-2015[J]. Int J Infect Dis, 2019, 80S: S36-S44. doi: 10.1016/j.ijid.2019.02.038.
[22] Kang D, Choi H, Kim JH, et al. Spatial epidemic dynamics of the COVID-19 outbreak in China[J].Int J Infect Dis, 2020, 94: 96-102. doi: 10.1016/j.ijid.2020.03.076.
[23] 蔡亚男, 韩旭, 魏亚梅, 等. 河北省2005-2016年肾综合征出血热时空聚集性分析[J]. 中华流行病学杂志, 2019, 40(8): 930-935. CAI Yanan, HAN Xu, WEI Yamei, et al. Spatial-temporal cluster of hemorrhagic fever with renal syndrome in Hebei province, 2005-2016[J]. Chinese journal of Epidemiology, 2019, 40(8): 930-935.
[24] 李学义, 李岩. SVG在线空间自相关分析方法及其应用[J]. 地理与地理信息科学, 2012, 28(5): 43-46. LI Xueyi, LI Yan. A method of online spatial autocorrelation analysis based on SVG and its application [J]. Geography and Geo-Information Science, 2012, 28(5): 43-46.
[25] 唐益, 龚德华, 白丽琼, 等. 湖南省2003-2011年活动性肺结核患者登记的空间分析[J].中国防痨杂志, 2012, 34(12): 764-767. TANG Yi, GONG Dehua, BAI Liqiong, et al. Spatial analysis on the active pulmonary tuberculosis patients registered between 2003 and 2011 in Hunan province[J]. Chinese Journal of Antituberculosis, 2012, 34(12): 764-767.
[26] 张珺茹, 王爱, 邹长青. 2014年各省人口出生死亡资料的系统聚类分析[J].中国卫生统计, 2017, 34(3): 469-471.
[27] 中国疾病预防控制中心新型冠状病毒肺炎应急响应机制流行病学组. 新型冠状病毒肺炎流行病学特征分析[J]. 中华流行病学杂志, 2020, 41(2): 145-151. The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases(COVID-19)in China [J]. Chinese Journal of Epidemiology, 2020, 41(2): 145-151.
[28] 陈奕, 王爱红, 易波, 等. 宁波市新型冠状病毒肺炎密切接触者感染流行病学特征分析[J]. 中华流行病学杂志, 2020, 41(5): 667-671. CHEN Yi, WANG Aihong, YI Bo, et al. The epidemiological characteristics of infection in close contacts of COVID-19 in Ningbo city [J]. Chinese Journal of Epidemiology, 2020, 41(5): 667-671.
[29] 何冠豪, 容祖华, 胡建雄, 等. 新型冠状病毒肺炎两种不同流行模式及其防控效果比较: 基于广州和温州市的分析[J]. 中华流行病学杂志, 2020,41(8):1214-1219. HE Guanhao, RONG Zuhua, HU Jianxiong, et al. Comparison of two epidemic patterns of COVID-19 and evaluation of prevention and control effectiveness: an analysis based on Guangzhou and Wenzhou [J]. Chinese Journal of Epidemiology, 2020, 41(8):1214-1219.
[30] Wu JT, Leung K, Leung GM. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study [J]. Lancet, 2020, 395(10225): 689-697.
[31] 许小可, 文成, 张光耀, 等. 新冠肺炎爆发前期武汉外流人口的地理去向分布及影响[J]. 电子科技大学学报, 2020,49(3):324-329. XÜ Xiaoke, WEN Cheng, ZHANG Guangyao, et al. The geographical destination distribution and effect of outflow population of Wuhan when the outbreak of the 2019-nCoV pneumonia [J]. Journal of University of Electronic Science and Technology of China, 2020, 49(3): 324-329.
[32] 胡建雄, 何冠豪, 刘涛, 等. 新型冠状病毒肺炎疫情初期湖北省输出风险评估[J]. 中华预防医学杂志, 2020, 54(4): 362-366. HU Jianxiong, HE Guanhao, LIU Tao, et al. Risk assessment of exported risk of novel coronavirus pneumonia from Hubei Province[J]. Chinese Journal of Preventive Medicine, 2020, 54(4): 362-366.
[33] Jia JS, Lu X, Yuan Y, et al. Population flow drives spatio-temporal distribution of COVID-19 in China [J]. Nature, 2020, 582(7812): 389-394.
[34] 刘碧瑶, 戚小华, 江敏, 等. 浙江省境外输入新型冠状病毒肺炎病例流行特征分析[J]. 预防医学, 2020,32(6): 550-554. LIU Biyao, QI Xiaohua, JIANG Min, et al. Epidemiological characteristics of imported COVID-19 cases from aboard to Zhejiang Province[J]. Preventive Medicine, 2020,32(6): 550-554.
[1] BAI Yao, CHEN Zhijun, SONG Shuxuan, HE Zhen, CHEN Baozhong, SHAO Zhongjun, LIU Kun. Investigation of a family cluster outbreak of coronavirus disease 2019 in Xian [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 95-99.
[2] ZHANG Hui, SONG Shuxuan, LIU Jifeng, HE Zhen, SHAO Zhongjun, LIU Kun. Epidemiological characteristics of COVID-19 in Xi’an city [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 89-94.
[3] LIU Lili, JIA Yan, QI Chang, ZHU Yuchen, LI Chunyu, SHE Kaili, LIU Tingxuan, LI Xiujun. Clustering distribution of COVID-19 in Wenzhou from January to March 2020 based on spatiotemporal analysis [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 82-88.
[4] LIU Tingxuan, QI Chang, SHE Kaili, JIA Yan, ZHU Yuchen, LI Chunyu, LIU Lili, WANG Xu, ZHANG Zhihua, LI Xiujun. Epidemiological characteristics and spatial-temporal clustering of COVID-19 in Hebei Province [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 74-81.
[5] LIU Jun, LI Huan, ZHANG Shiyu, ZHANG Peng, AI Siqi, TIAN Fei, LIN Hualiang. Risk factors of severe and critical patients with COVID-19 in Hubei, China [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 60-65.
[6] QI Chang, ZHU Yuchen, LI Chunyu, LIU Lili, ZHANG Dandan, WANG Xu, SHE Kaili, CHEN Ming, KANG Dianmin, LI Xiujun. Influence factors of COVID-19 in Shandong Province based on geographically weighted generalized linear model [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 53-59.
[7] SHE Kaili, ZHANG Dandan, QI Chang, LIU Tingxuan, JIA Yan, ZHU Yuchen, LI Chunyu, LIU Lili, WANG Xu, SU Hong, LI Xiujun. Epidemiological characteristics and incubation period of coronavirus disease 2019 in Anhui Province [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 44-52.
[8] LI Chunyu, ZHU Yuchen, QI Chang, LIU Lili, ZHANG Dandan, WANG Xu, XU Xueli, LI Xiujun. Epidemic dynamics of COVID-19 in Xinyang City, Henan Province [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 38-43.
[9] JIN Xinye, LU Zhenzhen, DING Zhongxing, CHEN Feng, PENG Zhihang. A dynamic modeling study on the effects of Wuhan traffic control and centralized quarantine measures on COVID-19 epidemic [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 25-31.
[10] XU Lijun, LIU Wenhui, LIU Yuan, LI Meixia, LUO Lei, OU Chunquan. Construction of SEIQCR epidemic model and its application in the evaluation of public health interventions on COVID-19 in Guangzhou [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 20-24.
[11] LI Xiujun, LI Xinlou, LIU Kun, ZHAO Xiaobo, MA Meng, SUN Bo. Application of geographic information system in the control of COVID-19 epidemic [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 13-19.
[12] WANG Ling, CAO Haixia, ZHANG Ling, ZHANG Wenna, PAN Yanping, SHI Ying, ZHANG Wei, CUI Feng. Investigation and analysis of the characteristics of a family cluster of coronavirus disease 2019 in Zibo [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 100-104.
[13] WANG Bin, BU Xuehui, KONG Xianggen, ZHANG Zhaohua, WU Anzhao, XIAO Di, JIANG Xuemei. Comparison of the clinical characteristics between 37 adults and 10 children with COVID-19 [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 112-116.
[14] YU Xiaolin, ZHANG Jun, YANG Liu, ZHOU Lin, CUI Liangliang, ZHANG Ji. Epidemiological characteristics of COPD patients attacked by respiratory system diseases during the flu season in Jinan City [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(3): 79-82.
[15] WANG Hao, ZHANG Na, XUE Fuzhong, WANG Ping, KANG Dianmin, LIU Yanxun. Spatial epidemiological characteristics of HIV infections and AIDS patients in Shandong Province [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2015, 53(2): 81-86.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of Journal of Shandong University (Health Sciences)
Supported by Beijing Magtech Co.Ltd