Spatiotemporal patterns of human mobility during the COVID-19 pandemic in China
The outbreak of the COVID-19 pandemic has significantly reshaped population mobility, exerting a sustained impact on the patterns and dynamics of population mobility in China over the next three years. To comprehend the changes in population mobility patterns during the early stages of the COVID-19...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-03-01
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| Series: | Geo-spatial Information Science |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2025.2451757 |
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| _version_ | 1849388184421531648 |
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| author | Jingjing Liu Lei Xu Nengcheng Chen Zeqiang Chen |
| author_facet | Jingjing Liu Lei Xu Nengcheng Chen Zeqiang Chen |
| author_sort | Jingjing Liu |
| collection | DOAJ |
| description | The outbreak of the COVID-19 pandemic has significantly reshaped population mobility, exerting a sustained impact on the patterns and dynamics of population mobility in China over the next three years. To comprehend the changes in population mobility patterns during the early stages of the COVID-19 outbreak, as well as standard epidemic prevention and control measures, we conducted an analysis using data from Baidu Huiyan’s migration scale index. This data was used to examine the characteristics of population movement in China during the Spring Festival and National Day from 2020 to 2022. We employed the Louvain algorithm and SVD decomposition to examine the spatiotemporal patterns of population movement. In addition, we calculated the response speed of urban population arrival flow to the pandemic using the Pearson correlation coefficient. Furthermore, we analyzed the factors influencing this correlation and response speed using random forest eigenvalues. The findings suggest that daily commuting and holiday travel patterns were not significantly altered by the pandemic. Over the past three years, there has been a trend in population mobility toward quicker responses to the pandemic, influenced primarily by economic, policy, medical conditions, and population density. Areas with higher population density and greater structural complexity exhibit increased sensitivity of population mobility to the severity of the pandemic. Examining population movement patterns and influencing factors against the backdrop of the COVID-19 pandemic can offer valuable insights for devising more targeted and effective prevention and control measures. Ultimately, this endeavor contributes to enhancing health-related urban resilience and sustainability. |
| format | Article |
| id | doaj-art-de9b95e045c640838f8e1390d314c3d8 |
| institution | Kabale University |
| issn | 1009-5020 1993-5153 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geo-spatial Information Science |
| spelling | doaj-art-de9b95e045c640838f8e1390d314c3d82025-08-20T03:42:23ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532025-03-0112110.1080/10095020.2025.2451757Spatiotemporal patterns of human mobility during the COVID-19 pandemic in ChinaJingjing Liu0Lei Xu1Nengcheng Chen2Zeqiang Chen3Hubei Luojia Laboratory & State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, ChinaNational Engineering Research Center for Geographic Information System, School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, ChinaHubei Luojia Laboratory & State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, ChinaNational Engineering Research Center for Geographic Information System, School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, ChinaThe outbreak of the COVID-19 pandemic has significantly reshaped population mobility, exerting a sustained impact on the patterns and dynamics of population mobility in China over the next three years. To comprehend the changes in population mobility patterns during the early stages of the COVID-19 outbreak, as well as standard epidemic prevention and control measures, we conducted an analysis using data from Baidu Huiyan’s migration scale index. This data was used to examine the characteristics of population movement in China during the Spring Festival and National Day from 2020 to 2022. We employed the Louvain algorithm and SVD decomposition to examine the spatiotemporal patterns of population movement. In addition, we calculated the response speed of urban population arrival flow to the pandemic using the Pearson correlation coefficient. Furthermore, we analyzed the factors influencing this correlation and response speed using random forest eigenvalues. The findings suggest that daily commuting and holiday travel patterns were not significantly altered by the pandemic. Over the past three years, there has been a trend in population mobility toward quicker responses to the pandemic, influenced primarily by economic, policy, medical conditions, and population density. Areas with higher population density and greater structural complexity exhibit increased sensitivity of population mobility to the severity of the pandemic. Examining population movement patterns and influencing factors against the backdrop of the COVID-19 pandemic can offer valuable insights for devising more targeted and effective prevention and control measures. Ultimately, this endeavor contributes to enhancing health-related urban resilience and sustainability.https://www.tandfonline.com/doi/10.1080/10095020.2025.2451757COVID-19human mobilitytravel restrictionssmartphone dataurban governance |
| spellingShingle | Jingjing Liu Lei Xu Nengcheng Chen Zeqiang Chen Spatiotemporal patterns of human mobility during the COVID-19 pandemic in China Geo-spatial Information Science COVID-19 human mobility travel restrictions smartphone data urban governance |
| title | Spatiotemporal patterns of human mobility during the COVID-19 pandemic in China |
| title_full | Spatiotemporal patterns of human mobility during the COVID-19 pandemic in China |
| title_fullStr | Spatiotemporal patterns of human mobility during the COVID-19 pandemic in China |
| title_full_unstemmed | Spatiotemporal patterns of human mobility during the COVID-19 pandemic in China |
| title_short | Spatiotemporal patterns of human mobility during the COVID-19 pandemic in China |
| title_sort | spatiotemporal patterns of human mobility during the covid 19 pandemic in china |
| topic | COVID-19 human mobility travel restrictions smartphone data urban governance |
| url | https://www.tandfonline.com/doi/10.1080/10095020.2025.2451757 |
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