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Changes in mobility and socioeconomic conditions during the COVID-19 outbreak

Author

Listed:
  • Marco Dueñas

    (International Trade and Social Policy–Universidad de Bogotá Jorge Tadeo Lozano)

  • Mercedes Campi

    (Instituto Interdisciplinario de Economía Política de Buenos Aires (IIEP))

  • Luis E. Olmos

    (University of California
    National Institute of Health
    Universidad de Medellín)

Abstract

Since the outbreak of the 2019 novel coronavirus (COVID-19) pandemic, governments have been implementing containment measures aimed at mitigating the spread of the virus, including restrictions to human mobility. The ability to adapt to the pandemic and respond to containment measures can be bound by socioeconomic conditions, which are heterogeneous in large urban areas of low-income and middle-income countries. In this paper, we analyse mobility changes following the implementation of containment measures in Bogotá, Colombia. We characterise the mobility network before and during the pandemic and analyse its evolution and changes between January and July 2020. We observe a general reduction in mobility trends, but the overall connectivity between different areas of the city remains after the lockdown, reflecting the resilience of the mobility network. Then, we estimate a gravity model to assess the effect of socioeconomic conditions on mobility flows. We find that the responses to lockdown policies depend on the socioeconomic conditions of the population. Before the pandemic, the population with better socioeconomic conditions shows higher mobility flows. Since the lockdown, mobility presents a general decrease, but the population with worse socioeconomic conditions shows lower reductions in mobility flows. We conclude by deriving policy implications.

Suggested Citation

  • Marco Dueñas & Mercedes Campi & Luis E. Olmos, 2021. "Changes in mobility and socioeconomic conditions during the COVID-19 outbreak," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-10, December.
    • Handle: RePEc:pal:palcom:v:8:y:2021:i:1:d:10.1057_s41599-021-00775-0
    DOI: 10.1057/s41599-021-00775-0
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    2. Yang Song & Sungmin Lee & Amaryllis H Park & Chanam Lee, 2023. "COVID-19 impacts on non-work travel patterns: A place-based investigation using smartphone mobility data," Environment and Planning B, , vol. 50(3), pages 642-659, March.
    3. Marco Due~nas & Federico Nutarelli & V'ictor Ortiz & Massimo Riccaboni & Francesco Serti, 2021. "Assessing the Heterogeneous Impact of Economy-Wide Shocks: A Machine Learning Approach Applied to Colombian Firms," Papers 2104.04570, arXiv.org, revised Nov 2024.
    4. Vega-Gonzalo, Maria & Gomez, Juan & Christidis, Panayotis, 2023. "How has COVID-19 changed private car use in European urban areas? An analysis of the effect of socio-economic characteristics and mobility habits," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    5. Jiang, Shixiong & Cai, Canhuang, 2022. "Unraveling the dynamic impacts of COVID-19 on metro ridership: An empirical analysis of Beijing and Shanghai, China," Transport Policy, Elsevier, vol. 127(C), pages 158-170.
    6. Yunke Zhang & Fengli Xu & Lin Chen & Yuan Yuan & James Evans & Luis Bettencourt & Yong Li, 2024. "Counterfactual mobility network embedding reveals prevalent accessibility gaps in U.S. cities," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    7. Gabriel Dias & Elisabete Arsenio & Paulo Ribeiro, 2021. "The Role of Shared E-Scooter Systems in Urban Sustainability and Resilience during the Covid-19 Mobility Restrictions," Sustainability, MDPI, vol. 13(13), pages 1-19, June.
    8. 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.
    9. 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).
    10. Dueñas, Marco & Ortiz, Víctor & Riccaboni, Massimo & Serti, Francesco, 2021. "Assessing the Impact of COVID-19 on Trade: a Machine Learning Counterfactual Analysis," Working papers 79, Red Investigadores de Economía.
    11. Jacek Oskarbski & Krystian Birr & Karol Żarski, 2021. "Bicycle Traffic Model for Sustainable Urban Mobility Planning," Energies, MDPI, vol. 14(18), pages 1-36, September.
    12. Toger, Marina & Türk, Umut & Östh, John & Kourtit, Karima & Nijkamp, Peter, 2023. "Inequality in leisure mobility: An analysis of activity space segregation spectra in the Stockholm conurbation," Journal of Transport Geography, Elsevier, vol. 111(C).
    13. Linqing Liu & Weiran Wang & Xiaofei Yan & Mengyun Shen & Haizhi Chen, 2023. "The cascade influence of grain trade shocks on countries in the context of the Russia-Ukraine conflict," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-28, December.
    14. Yaiza Montero-Lamas & Alfonso Orro & Margarita Novales & Francisco-Alberto Varela-García, 2022. "Analysis of the Relationship between the Characteristics of the Areas of Influence of Bus Stops and the Decrease in Ridership during COVID-19 Lockdowns," Sustainability, MDPI, vol. 14(7), pages 1-19, April.

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