College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China.
School of Architecture, Tsinghua University, Beijing 100084, China.
Int J Environ Res Public Health. 2020 Apr 11;17(8):2630. doi: 10.3390/ijerph17082630.
The outbreak of COVID-19 in China has attracted wide attention from all over the world. The impact of COVID-19 has been significant, raising concerns regarding public health risks in China and worldwide. Migration may be the primary reason for the long-distance transmission of the disease. In this study, the following analyses were performed. (1) Using the data from the China migrant population survey in 2017 (Sample size = 432,907), a matrix of the residence-birthplace (R-B matrix) of migrant populations is constructed. The matrix was used to analyze the confirmed cases of COVID-19 at Prefecture-level Cities from February 1-15, 2020 after the outbreak in Wuhan, by calculating the probability of influx or outflow migration. We obtain a satisfactory regression analysis result ( = 0.826-0.887, = 330). (2) We use this R-B matrix to simulate an outbreak scenario in 22 immigrant cities in China, and propose risk prevention measures after the outbreak. If similar scenarios occur in the cities of Wenzhou, Guangzhou, Dongguan, or Shenzhen, the disease transmission will be wider. (3) We also use a matrix to determine that cities in Henan province, Anhui province, and Municipalities (such as Beijing, Shanghai, Guangzhou, Shenzhen, Chongqing) in China will have a high risk level of disease carriers after a similar emerging epidemic outbreak scenario due to a high influx or outflow of migrant populations.
中国新冠肺炎疫情的爆发引起了全世界的广泛关注。新冠肺炎疫情的影响巨大,引发了人们对中国乃至全球公共卫生风险的担忧。疫情的远距离传播可能主要是人口迁移所致。本研究主要进行了以下分析。(1)利用 2017 年中国流动人口动态监测调查数据(样本量=432907)构建流动人口的居住-出生地(R-B)矩阵,通过计算流入或流出的流动人口概率,对 2020 年 2 月 1 日至 15 日武汉疫情发生后,各地级市新冠肺炎确诊病例进行分析,得到了较为满意的回归分析结果(=0.826-0.887,=330)。(2)利用该 R-B 矩阵模拟中国 22 个人口流入城市的疫情爆发情景,并提出了疫情爆发后的风险防范措施。如果温州、广州、东莞、深圳等城市发生类似情况,疾病传播范围将更广。(3)我们还利用矩阵确定了中国河南省、安徽省和北京市、上海市、广州市、深圳市、重庆市等直辖市,在类似新发传染病疫情爆发情景下,由于流动人口的大量流入或流出,将具有较高的疾病携带者风险水平。