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Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data
The outbreak of the COVID-19 has become a worldwide public health challenge for contemporary cities during the background of globalization and planetary urbanization. However, spatial factors affecting the transmission of the disease in urban spaces remain unclear. Based on geotagged COVID-19 cases...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101567/ https://www.ncbi.nlm.nih.gov/pubmed/35564606 http://dx.doi.org/10.3390/ijerph19095208 |
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author | Wang, Ru Liu, Lingbo Wu, Hao Peng, Zhenghong |
author_facet | Wang, Ru Liu, Lingbo Wu, Hao Peng, Zhenghong |
author_sort | Wang, Ru |
collection | PubMed |
description | The outbreak of the COVID-19 has become a worldwide public health challenge for contemporary cities during the background of globalization and planetary urbanization. However, spatial factors affecting the transmission of the disease in urban spaces remain unclear. Based on geotagged COVID-19 cases from social media data in the early stage of the pandemic, this study explored the correlation between different infectious outcomes of COVID-19 transmission and various factors of the urban environment in the main urban area of Wuhan, utilizing the multiple regression model. The result shows that most spatial factors were strongly correlated to case aggregation areas of COVID-19 in terms of population density, human mobility and environmental quality, which provides urban planners and administrators valuable insights for building healthy and safe cities in an uncertain future. |
format | Online Article Text |
id | pubmed-9101567 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91015672022-05-14 Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data Wang, Ru Liu, Lingbo Wu, Hao Peng, Zhenghong Int J Environ Res Public Health Article The outbreak of the COVID-19 has become a worldwide public health challenge for contemporary cities during the background of globalization and planetary urbanization. However, spatial factors affecting the transmission of the disease in urban spaces remain unclear. Based on geotagged COVID-19 cases from social media data in the early stage of the pandemic, this study explored the correlation between different infectious outcomes of COVID-19 transmission and various factors of the urban environment in the main urban area of Wuhan, utilizing the multiple regression model. The result shows that most spatial factors were strongly correlated to case aggregation areas of COVID-19 in terms of population density, human mobility and environmental quality, which provides urban planners and administrators valuable insights for building healthy and safe cities in an uncertain future. MDPI 2022-04-25 /pmc/articles/PMC9101567/ /pubmed/35564606 http://dx.doi.org/10.3390/ijerph19095208 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Ru Liu, Lingbo Wu, Hao Peng, Zhenghong Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data |
title | Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data |
title_full | Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data |
title_fullStr | Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data |
title_full_unstemmed | Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data |
title_short | Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data |
title_sort | correlation analysis between urban elements and covid-19 transmission using social media data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101567/ https://www.ncbi.nlm.nih.gov/pubmed/35564606 http://dx.doi.org/10.3390/ijerph19095208 |
work_keys_str_mv | AT wangru correlationanalysisbetweenurbanelementsandcovid19transmissionusingsocialmediadata AT liulingbo correlationanalysisbetweenurbanelementsandcovid19transmissionusingsocialmediadata AT wuhao correlationanalysisbetweenurbanelementsandcovid19transmissionusingsocialmediadata AT pengzhenghong correlationanalysisbetweenurbanelementsandcovid19transmissionusingsocialmediadata |