IDEAS home Printed from https://ideas.repec.org/a/nat/nathum/v7y2023i10d10.1038_s41562-023-01660-3.html
   My bibliography  Save this article

COVID-19 is linked to changes in the time–space dimension of human mobility

Author

Listed:
  • Clodomir Santana

    (University of Exeter)

  • Federico Botta

    (University of Exeter
    The Alan Turing Institute)

  • Hugo Barbosa

    (University of Exeter)

  • Filippo Privitera

    (Spectus)

  • Ronaldo Menezes

    (University of Exeter
    The Alan Turing Institute
    Federal University of Ceará)

  • Riccardo Di Clemente

    (University of Exeter
    The Alan Turing Institute
    Northeastern University London)

Abstract

Socio-economic constructs and urban topology are crucial drivers of human mobility patterns. During the coronavirus disease 2019 pandemic, these patterns were reshaped in their components: the spatial dimension represented by the daily travelled distance, and the temporal dimension expressed as the synchronization time of commuting routines. Here, leveraging location-based data from de-identified mobile phone users, we observed that, during lockdowns restrictions, the decrease of spatial mobility is interwoven with the emergence of asynchronous mobility dynamics. The lifting of restriction in urban mobility allowed a faster recovery of the spatial dimension compared with the temporal one. Moreover, the recovery in mobility was different depending on urbanization levels and economic stratification. In rural and low-income areas, the spatial mobility dimension suffered a more considerable disruption when compared with urbanized and high-income areas. In contrast, the temporal dimension was more affected in urbanized and high-income areas than in rural and low-income areas.

Suggested Citation

  • Clodomir Santana & Federico Botta & Hugo Barbosa & Filippo Privitera & Ronaldo Menezes & Riccardo Di Clemente, 2023. "COVID-19 is linked to changes in the time–space dimension of human mobility," Nature Human Behaviour, Nature, vol. 7(10), pages 1729-1739, October.
    • Handle: RePEc:nat:nathum:v:7:y:2023:i:10:d:10.1038_s41562-023-01660-3
    DOI: 10.1038/s41562-023-01660-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41562-023-01660-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/s41562-023-01660-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sheth, Jagdish, 2020. "Impact of Covid-19 on consumer behavior: Will the old habits return or die?," Journal of Business Research, Elsevier, vol. 117(C), pages 280-283.
    2. Luca Pappalardo & Filippo Simini & Salvatore Rinzivillo & Dino Pedreschi & Fosca Giannotti & Albert-László Barabási, 2015. "Returners and explorers dichotomy in human mobility," Nature Communications, Nature, vol. 6(1), pages 1-8, November.
    3. Riccardo Di Clemente & Miguel Luengo-Oroz & Matias Travizano & Sharon Xu & Bapu Vaitla & Marta C. González, 2018. "Sequences of purchases in credit card data reveal lifestyles in urban populations," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    4. Serina Chang & Emma Pierson & Pang Wei Koh & Jaline Gerardin & Beth Redbird & David Grusky & Jure Leskovec, 2021. "Mobility network models of COVID-19 explain inequities and inform reopening," Nature, Nature, vol. 589(7840), pages 82-87, January.
    5. Minha Lee & Jun Zhao & Qianqian Sun & Yixuan Pan & Weiyi Zhou & Chenfeng Xiong & Lei Zhang, 2020. "Human mobility trends during the early stage of the COVID-19 pandemic in the United States," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-15, November.
    6. Sparks, Kevin & Moehl, Jessica & Weber, Eric & Brelsford, Christa & Rose, Amy, 2022. "Shifting temporal dynamics of human mobility in the United States," Journal of Transport Geography, Elsevier, vol. 99(C).
    7. Nicolò Gozzi & Michele Tizzoni & Matteo Chinazzi & Leo Ferres & Alessandro Vespignani & Nicola Perra, 2021. "Estimating the effect of social inequalities on the mitigation of COVID-19 across communities in Santiago de Chile," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    8. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
    9. Laura Alessandretti & Ulf Aslak & Sune Lehmann, 2020. "The scales of human mobility," Nature, Nature, vol. 587(7834), pages 402-407, November.
    10. Qi Wang & John E Taylor, 2014. "Quantifying Human Mobility Perturbation and Resilience in Hurricane Sandy," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-5, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liam Berrisford & Eraldo Ribeiro & Ronaldo Menezes, 2024. "Estimating annual ambient air pollution using structural properties of road networks," Environment and Planning B, , vol. 51(9), pages 2031-2054, November.
    2. Kaixin Zhu & Zhifeng Cheng & Jianghao Wang, 2024. "Measuring Chinese mobility behaviour during COVID-19 using geotagged social media data," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    3. Baudains, Peter & Kalatian, Arash & Choudhury, Charisma F. & Manley, Ed, 2024. "Social inequality and the changing patterns of travel in the pandemic and post-pandemic era," Journal of Transport Geography, Elsevier, vol. 118(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Heyang & Zeng, An, 2022. "Improving recommendation by connecting user behavior in temporal and topological dimensions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    2. Zhang, Wenjia & Wu, Yulin & Deng, Guobang, 2024. "Social and spatial disparities in individuals’ mobility response time to COVID-19: A big data analysis incorporating changepoint detection and accelerated failure time models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 184(C).
    3. Yang, Hu & Lv, Sirui & Guo, Bao & Dai, Jianjun & Wang, Pu, 2024. "Uncovering spatiotemporal human mobility patterns in urban agglomerations: A mobility field based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    4. Takahiro Yabe & Bernardo García Bulle Bueno & Xiaowen Dong & Alex Pentland & Esteban Moro, 2023. "Behavioral changes during the COVID-19 pandemic decreased income diversity of urban encounters," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    5. Matteo Böhm & Mirco Nanni & Luca Pappalardo, 2022. "Gross polluters and vehicle emissions reduction," Nature Sustainability, Nature, vol. 5(8), pages 699-707, August.
    6. Li, Ze-Tao & Nie, Wei-Peng & Cai, Shi-Min & Zhao, Zhi-Dan & Zhou, Tao, 2023. "Exploring the topological characteristics of urban trip networks based on taxi trajectory data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    7. Lin Chen & Fengli Xu & Zhenyu Han & Kun Tang & Pan Hui & James Evans & Yong Li, 2022. "Strategic COVID-19 vaccine distribution can simultaneously elevate social utility and equity," Nature Human Behaviour, Nature, vol. 6(11), pages 1503-1514, November.
    8. Yang, Xiong & Zhuge, Chengxiang & Shao, Chunfu & Huang, Yuantan & Hayse Chiwing G. Tang, Justin & Sun, Mingdong & Wang, Pinxi & Wang, Shiqi, 2022. "Characterizing mobility patterns of private electric vehicle users with trajectory data," Applied Energy, Elsevier, vol. 321(C).
    9. Mofeng Yang & Yixuan Pan & Aref Darzi & Sepehr Ghader & Chenfeng Xiong & Lei Zhang, 2022. "A data-driven travel mode share estimation framework based on mobile device location data," Transportation, Springer, vol. 49(5), pages 1339-1383, October.
    10. Xuesong Gao & Hui Wang & Lun Liu, 2021. "Profiling Residents’ Mobility with Grid-Aggregated Mobile Phone Trace Data Using Chengdu as the Case," Sustainability, MDPI, vol. 13(24), pages 1-13, December.
    11. Uğurel, Ekin & Huang, Shuai & Chen, Cynthia, 2024. "Learning to generate synthetic human mobility data: A physics-regularized Gaussian process approach based on multiple kernel learning," Transportation Research Part B: Methodological, Elsevier, vol. 189(C).
    12. Chao Fan & Yang Yang & Ali Mostafavi, 2024. "Neural embeddings of urban big data reveal spatial structures in cities," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    13. Rezapour, Shabnam & Baghaian, Atefe & Naderi, Nazanin & Sarmiento, Juan P., 2023. "Infection transmission and prevention in metropolises with heterogeneous and dynamic populations," European Journal of Operational Research, Elsevier, vol. 304(1), pages 113-138.
    14. Pengjun Zhao & Hao Wang & Qiyang Liu & Xiao-Yong Yan & Jingzhong Li, 2024. "Unravelling the spatial directionality of urban mobility," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    15. Timo Mitze & Reinhold Kosfeld, 2022. "The propagation effect of commuting to work in the spatial transmission of COVID-19," Journal of Geographical Systems, Springer, vol. 24(1), pages 5-31, January.
    16. Thomas Collins & Riccardo Di Clemente & Mario Gutiérrez-Roig & Federico Botta, 2024. "Spatiotemporal gender differences in urban vibrancy," Environment and Planning B, , vol. 51(7), pages 1430-1446, September.
    17. Liang, Zhenglin & Jiang, Chen & Sun, Muxia & Xue, Zongqi & Li, Yan-Fu, 2023. "Resilience analysis for confronting the spreading risk of contagious diseases," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    18. Zhang, Bin & Rasouli, Soora & Feng, Tao, 2024. "A novel data-driven approach for customizing destination choice set: A case study in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 190(C).
    19. Hwang, Jaewoo & Lee, Hyojung & Lee, Sunmi & Jang, Bongsoo & Do, Younghae & Lai, Ying-Cheng, 2024. "Comprehensive risk management of infectious diseases," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).
    20. Michele Tizzoni & Elaine O. Nsoesie & Laetitia Gauvin & Márton Karsai & Nicola Perra & Shweta Bansal, 2022. "Addressing the socioeconomic divide in computational modeling for infectious diseases," Nature Communications, Nature, vol. 13(1), pages 1-7, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nathum:v:7:y:2023:i:10:d:10.1038_s41562-023-01660-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.