摘要
对于传染性较强、潜伏期较长且主要通过人口流动传播的新型冠状病毒肺炎疫情,旣往的空间传播预警方式存在灵敏度低、时效性和准确性较差的问题,而依靠航空客流量的新兴预警方式不适用于内部联系以陆路交通为主的都市圈。以疫情高发的武汉城市圈为对象,以湖北省卫健委公布的确诊病例数量为基准,提出运用城市联系度、铁路客运密度和人口流动大数据3种方法进行疫情空间扩散预警。研究显示,与另两种预警方式相比,人口流动大数据对都市圈层面疫情空间扩散趋势的推测具有最高准确度。依据研究结论,提出推动多源数据融合、细化预警空间范围及开展数字化社区治理等建议,以求提升区域应对重大公共卫生事件的治理水平。
For the COVID-19,which is highly infectious,has a long incubation period and relies on population flow to spread,the previous warning model has the problems of low sensitivity,timeliness and poor accuracy.On the other hand,the early spatial warning model relying on air passenger flow only applies to eities with direet fights,but not applicable to the urban areas like Wuhan city circle,which is dominated by land-rafie.Taking Wuhan city circle as an example,the paper uses official new COVID-19 confirmed cases data announced by Health Commission of Hubei Province as a benchmark.Firstly,the time interval between virus carriers leaving Wuhan and diagnosed in other cities has been calculated.Secondly,the analysis results of three methods including city connection degree,railway passenger density and population flow big data have been compared.In conclusion,the accuracy of the population flow big data to warn the spatial spread trend of COVID-19 in metropolitan area was verified.Finally,some suggestions are put forward for better spatial tracing of infection sources and early warning of secondary transmission.
作者
邹游
赵倩
周婕
ZOU You;ZHAO Qian;ZHOU Jie
出处
《现代城市研究》
CSSCI
2020年第10期30-37,共8页
Modern Urban Research
