| 基于多源数据的湖北省COVID-19疫情时空扩散影响因子分析 |
| |
| 引用本文： | 廖文悦,孙美薇,余楚滢,邓应彬,李苗,杨骥,李勇,许剑辉,陈裕婵,严滢伟.基于多源数据的湖北省COVID-19疫情时空扩散影响因子分析[J].热带地理,2021,41(1):12-24. |
| |
| 作者姓名： | 廖文悦 孙美薇 余楚滢 邓应彬 李苗 杨骥 李勇 许剑辉 陈裕婵 严滢伟 |
| |
| 作者单位： | 1.a. 广东省科学院广州地理研究所;广东省地理空间信息技术与应用公共实验室;广东省遥感与地理信息系统应用重点实验室，广州 510070;2.哈尔滨师范大学 地理科学学院，哈尔滨 150025;3.南方海洋科学与工程广东省实验室（广州），广州 511458;4.中山大学 地理科学与规划学院，广州 510275］ |
| |
| 基金项目： | 南方海洋科学与工程广东省实验室（广州）人才团队引进重大专项(GML2019ZD0301);广东省引进创新创业团队项目(2016ZT06D336) |
| |
| 摘 要： | 利用武汉市人口迁出规模指数与武汉迁入到湖北各市人口比例的乘积(MSI)及市内交通强度(TI),建立时间回归模型,分析各市的COVID-19每日新增病例;利用交通可达性及各市GDP比例,建立空间回归模型,分析湖北省各市COVID-19的万人累计感染率.结果显示:1)基于人口迁徙数据与各市每日新增COVID-19病例构建的...
|
| 关 键 词： | 迁徙大数据 COVID-19 疫情扩散 交通网络 湖北 |
| 收稿时间： | 2020-05-26 |
Impact Factors of COVID-19 Epidemic Spread in Hubei Province Based on Multi-Source Data |
| |
| Wenyue Liao,Meiwei Sun,Chuying Yu,Yingbin Deng,Miao Li,Ji Yang,Yong Li,Jianhui Xu,Yuchan Chen,Yingwei Yan.Impact Factors of COVID-19 Epidemic Spread in Hubei Province Based on Multi-Source Data[J].Tropical Geography,2021,41(1):12-24. |
| |
| Authors: | Wenyue Liao Meiwei Sun Chuying Yu Yingbin Deng Miao Li Ji Yang Yong Li Jianhui Xu Yuchan Chen Yingwei Yan |
| |
| Abstract: | With more than 26 million confirmed cases and over two million case-fatalities worldwide, the coronavirus disease (COVID-19) pandemic has transformed the dynamics of human lives globally. It has been designated as a pandemic by the World Health Organization. The COVID-19 virus can be transmitted through droplets, aerosols, or direct contact. It possesses evident characteristics of human-to-human transmission. Additionally, COVID-19 is a highly pathogenic new coronavirus, and people are prone to serious respiratory diseases resulting in high mortality after becoming infected. It has posed a great security threat to the entire human society and caused hundreds of billions of economic losses. The novel coronavirus disease 2019 (COVID-19) epidemic spread from Wuhan to all other cities in China before Spring Festival, causing serious public health issues and preventing the growth of the social economy. Analyzing the spatial-temporal spread pattern of COVID-19 can support the prevention of the epidemic. Thus, this study aims to analyze the temporal-spatial spread characteristics of COVID-19 in Hubei Province. First, a regression model with variables of migration big data (mobility scale index (MSI) and traffic intensity) is employed to explore the temporal pattern of the spread of the epidemic. Second, the spatial spread characteristics of COVID-19 are analyzed using a regression model comprising transportation information (primary and secondary road transportation networks) and social economic information (2018 GDP data). The results illustrate the following. First, the regression model based on population migration data and daily COVID-19 cases in each city was significant (Sig.=0.00), with R2 up to 0.715, indicating that the independent variable could explain the dependent variable. As indicated by the standardized coefficient results, MSI (0.85) has a greater impact on the daily new cases in each city. Second, the cumulative infection rate per 10000 people was positively correlated with the number of medical institutions and GDP with correlation coefficients of 0.689 and 0.774, respectively, Sig. was less than 0.05. However, it was not correlated with the number of beds (Sig. > 0.05). Third, the spatial regression model based on the traffic network, socio-economic data and cumulative infection rate of ten thousand people in each city of Hubei was also significant. The independent variables in the model can explain the variability of 67.2% of the dependent variables. The results of the standardized coefficient show that the GDP ratio of each city has a greater impact on the model. The results of the study are expected to provide scientific data support for the government and epidemic prevention workers to formulate efficient epidemic prevention and policy decisions. In conclusion, the model fit of multiple regression on the time scale is better than that on the spatial scale. Population migration has the greatest impact on the spread of the epidemic. That is, population mobility has a greater effect on the prevention and control of epidemic situations. The results of the study are expected to provide scientific data support for the government on formulating epidemic prevention policies. |
| |
| Keywords: | migration big data COVID-19 epidemic spread transportation network Hubei |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《热带地理》浏览原始摘要信息 |
| 点击此处可从《热带地理》下载免费的PDF全文 |
|
