Gao Zekun, Jiang Yutong, He Junyu, Wu Jiaping, Xu Jian, Christakos George
Ocean College, Zhejiang University, Zhoushan, 316021 China.
Department of Geography, San Diego State University, San Diego, CA 92182 USA.
Model Earth Syst Environ. 2022;8(2):2525-2538. doi: 10.1007/s40808-021-01244-y. Epub 2021 Jul 28.
Since the COVID-19 outbreak, four cities-Wuhan, Beijing, Urumqi and Dalian-have experienced the process from outbreak to stabilization. According to the China Statistical Yearbook and China Center for Disease Control records, regional, pathological, medical and response attributes were selected as regional vulnerability factors of infectious diseases. Then the Analytic Hierarchy Process (AHP) method was used to build a regional vulnerability index model for the infectious disease. The influence of the COVID-19 outbreak at a certain place was assessed computationally in terms of the number of days of epidemic duration and cumulative number of infections, and then fitted to the city data. The resulting correlation coefficient was 0.999952. The range of the regional vulnerability index for COVID-19 virus was from 0.0513 to 0.9379. The vulnerability indexes of Wuhan, Urumqi, Beijing and Dalian were 0.8733, 0.1951, 0.1566 and 0.1119, respectively. The lack of understanding of the virus became the biggest breakthrough point for the rapid spread of the virus in Wuhan. Due to inadequate prevention and control measures, the city of Urumqi was unable to trace the source of infection and close contacts, resulting in a relatively large impact. Beijing has both high population density and migration rate, which imply that the disease outbreak in this city had a great impact. Dalian has perfect prevention and good regional attributes. In addition, the regional vulnerability index model was used to analyze other Chinese cities. Accordingly, the regional vulnerability index and the prevention and control suggestions for them were discussed.
The online version contains supplementary material available at 10.1007/s40808-021-01244-y.
自新冠疫情爆发以来,武汉、北京、乌鲁木齐和大连四个城市经历了从爆发到稳定的过程。根据《中国统计年鉴》和中国疾病预防控制中心的记录,选取地区、病理、医疗和应对属性作为传染病的地区脆弱性因素。然后采用层次分析法(AHP)构建传染病地区脆弱性指数模型。根据疫情持续天数和累计感染数,通过计算评估新冠疫情在某地的影响,然后将其与城市数据进行拟合。得到的相关系数为0.999952。新冠病毒地区脆弱性指数范围为0.0513至0.9379。武汉、乌鲁木齐、北京和大连的脆弱性指数分别为0.8733、0.1951、0.1566和0.1119。对病毒缺乏了解成为病毒在武汉快速传播的最大突破口。由于防控措施不力,乌鲁木齐市无法追踪传染源和密切接触者,造成了较大影响。北京人口密度高且迁移率高,这意味着该市的疫情爆发产生了很大影响。大连具有完善的预防措施和良好的地区属性。此外,利用地区脆弱性指数模型对中国其他城市进行了分析。据此,讨论了这些城市的地区脆弱性指数及防控建议。
网络版包含可在10.1007/s40808-021-01244-y获取的补充材料。