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Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data
Rapid urbanization has gradually strengthened the spatial links between cities, which greatly aggravates the possibility of the spread of an epidemic. Traditional methods lack the early and accurate detection of epidemics. This study took the Hubei province as the study area and used Tencent's...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10251770/ https://www.ncbi.nlm.nih.gov/pubmed/37304123 http://dx.doi.org/10.3389/fpubh.2023.1029385 |
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author | Hua, Lei Ran, Rong Li, Tingrou |
author_facet | Hua, Lei Ran, Rong Li, Tingrou |
author_sort | Hua, Lei |
collection | PubMed |
description | Rapid urbanization has gradually strengthened the spatial links between cities, which greatly aggravates the possibility of the spread of an epidemic. Traditional methods lack the early and accurate detection of epidemics. This study took the Hubei province as the study area and used Tencent's location big data to study the spread of COVID-19. Using ArcGIS as a platform, the urban relation intensity, urban centrality, overlay analysis, and correlation analysis were used to measure and analyze the population mobility data of 17 cities in Hubei province. The results showed that there was high similarity in the spatial distribution of urban relation intensity, urban centrality, and the number of infected people, all indicating the spatial distribution characteristics of “one large and two small” distributions with Wuhan as the core and Huanggang and Xiaogan as the two wings. The urban centrality of Wuhan was four times higher than that of Huanggang and Xiaogan, and the urban relation intensity of Wuhan with Huanggang and Xiaogan was also the second highest in the Hubei province. Meanwhile, in the analysis of the number of infected persons, it was found that the number of infected persons in Wuhan was approximately two times that of these two cities. Through correlation analysis of the urban relation intensity, urban centrality, and the number of infected people, it was found that there was an extremely significant positive correlation among the urban relation intensity, urban centrality, and the number of infected people, with an R(2) of 0.976 and 0.938, respectively. Based on Tencent's location big data, this study conducted the epidemic spread research for “epidemic spatial risk classification and prevention and control level selection” to make up for the shortcomings in epidemic risk analysis and judgment. This could provide a reference for city managers to effectively coordinate existing resources, formulate policy, and control the epidemic. |
format | Online Article Text |
id | pubmed-10251770 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102517702023-06-10 Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data Hua, Lei Ran, Rong Li, Tingrou Front Public Health Public Health Rapid urbanization has gradually strengthened the spatial links between cities, which greatly aggravates the possibility of the spread of an epidemic. Traditional methods lack the early and accurate detection of epidemics. This study took the Hubei province as the study area and used Tencent's location big data to study the spread of COVID-19. Using ArcGIS as a platform, the urban relation intensity, urban centrality, overlay analysis, and correlation analysis were used to measure and analyze the population mobility data of 17 cities in Hubei province. The results showed that there was high similarity in the spatial distribution of urban relation intensity, urban centrality, and the number of infected people, all indicating the spatial distribution characteristics of “one large and two small” distributions with Wuhan as the core and Huanggang and Xiaogan as the two wings. The urban centrality of Wuhan was four times higher than that of Huanggang and Xiaogan, and the urban relation intensity of Wuhan with Huanggang and Xiaogan was also the second highest in the Hubei province. Meanwhile, in the analysis of the number of infected persons, it was found that the number of infected persons in Wuhan was approximately two times that of these two cities. Through correlation analysis of the urban relation intensity, urban centrality, and the number of infected people, it was found that there was an extremely significant positive correlation among the urban relation intensity, urban centrality, and the number of infected people, with an R(2) of 0.976 and 0.938, respectively. Based on Tencent's location big data, this study conducted the epidemic spread research for “epidemic spatial risk classification and prevention and control level selection” to make up for the shortcomings in epidemic risk analysis and judgment. This could provide a reference for city managers to effectively coordinate existing resources, formulate policy, and control the epidemic. Frontiers Media S.A. 2023-05-26 /pmc/articles/PMC10251770/ /pubmed/37304123 http://dx.doi.org/10.3389/fpubh.2023.1029385 Text en Copyright © 2023 Hua, Ran and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Hua, Lei Ran, Rong Li, Tingrou Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data |
title | Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data |
title_full | Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data |
title_fullStr | Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data |
title_full_unstemmed | Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data |
title_short | Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data |
title_sort | analysis of covid-19 outbreak in hubei province based on tencent's location big data |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10251770/ https://www.ncbi.nlm.nih.gov/pubmed/37304123 http://dx.doi.org/10.3389/fpubh.2023.1029385 |
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