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利用多源时空大数据分析 COVID-19 疫情的传播和控制压力。

Transmission and control pressure analysis of the COVID-19 epidemic situation using multisource spatio-temporal big data.

机构信息

School of Geography, Liaoning Normal University, Dalian, China.

出版信息

PLoS One. 2021 Mar 29;16(3):e0249145. doi: 10.1371/journal.pone.0249145. eCollection 2021.

DOI:10.1371/journal.pone.0249145
PMID:33780496
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8007114/
Abstract

Taking the Guangdong-Hong Kong-Macao Greater Bay Area as the research area, this paper used OD cluster analysis based on Baidu migration data from January 11 to January 25 (before the sealing-off of Wuhan) and concluded that there is a significant correlation 1the migration level from Wuhan to the GBA and the epidemic severity index. This paper also analyzed the migration levels and diffusivity of the outer and inner cities of the GBA. Lastly, four evaluation indexes were selected to research the possibility of work resumption and the rating of epidemic prevention and control through kernel density estimation. According to the study, the amount of migration depends on the geographical proximity, relationship and economic development of the source region, and the severity of the epidemic depends mainly on the migration volume and the severity of the epidemic in the source region. The epidemic risk is related not only to the severity of the epidemic in the source region but also to the degree of urban traffic development and the degree of urban openness. After the resumption of work, the pressure of epidemic prevention and control has been concentrated mainly in Shenzhen and Canton; the further away a region is from the core cities, the lower the pressure in that region. The mass migration of the population makes it difficult to control the epidemic effectively. The study of the relationship between migration volume, epidemic severity and epidemic risk is helpful to further analyze transmission types and predict the trends of the epidemic.

摘要

以粤港澳大湾区为研究区域,利用百度迁徙数据(截至 1 月 25 日武汉封城前,即 1 月 11 日至 1 月 25 日),采用 OD 聚类分析,得出武汉向大湾区的迁徙水平与疫情严重指数呈显著正相关。进一步分析了大湾区内外城市的迁徙水平和扩散程度。最后,通过核密度估计,选取四个评价指标,研究了大湾区复工复产的可能性和疫情防控的评级。研究发现,迁徙量取决于来源地的地理邻近性、关系和经济发展,疫情严重程度主要取决于迁徙量和来源地的疫情严重程度。疫情风险不仅与来源地疫情严重程度有关,还与城市交通发展程度和城市开放程度有关。复工复产后,疫情防控压力主要集中在深圳和广州;一个地区离核心城市越远,该地区的压力就越低。大量人口的迁移使得疫情难以有效控制。研究迁徙量、疫情严重程度和疫情风险之间的关系有助于进一步分析传播类型和预测疫情趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/118d/8007114/982c10121ab7/pone.0249145.g011.jpg
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