IDEAS home Printed from https://ideas.repec.org/a/spr/lsprsc/v16y2023i1d10.1007_s12076-023-00336-w.html
   My bibliography  Save this article

Agent-based simulation of COVID-19 containment measures: the case of lockdowns in cities

Author

Listed:
  • A. Yair Grinberger

    (Hebrew University of Jerusalem)

  • Daniel Felsenstein

    (Hebrew University of Jerusalem)

Abstract

The effectiveness and political feasibility of COVID-19 containment measures such as lockdowns, are contentious. This stems in part from an absence of tools for their rigorous evaluation. Common epidemiological models such as the SEIR model generally lack the spatial resolution required for micro-level containment actions, the visualization capabilities for communicating measures such as localized lockdowns and the scenario-testing capabilities for assessing different alternatives. We present an individual-level ABM that generates geo-social networks animated by agent-agent and agent-building interactions. The model simulates real-world contexts and is demonstrated for the city of Jerusalem. Simulation outputs yield much useful information for evaluating the effectiveness of lockdowns. These include network-generated socio-spatial contagion chains for individual agents, dynamic building level contagion processes and neighborhood-level patterns of COVID-19 imports and exports useful in identifying super-spreader neighborhoods. The policy implications afforded by these various outputs are discussed.

Suggested Citation

  • A. Yair Grinberger & Daniel Felsenstein, 2023. "Agent-based simulation of COVID-19 containment measures: the case of lockdowns in cities," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-16, December.
    • Handle: RePEc:spr:lsprsc:v:16:y:2023:i:1:d:10.1007_s12076-023-00336-w
    DOI: 10.1007/s12076-023-00336-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12076-023-00336-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12076-023-00336-w?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. Pragyan Deb & Davide Furceri & Jonathan D. Ostry & Nour Tawk, 2022. "The Economic Effects of COVID-19 Containment Measures," Open Economies Review, Springer, vol. 33(1), pages 1-32, February.
    Full references (including those not matched with items on IDEAS)

    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. Lalinsky, Tibor & Pál, Rozália, 2022. "Distribution of COVID-19 government support and its consequences for firm liquidity and solvency," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 305-335.
    2. Daniel Rees, 2020. "What Comes Next?," BIS Working Papers 898, Bank for International Settlements.
    3. Rosa Caiazza & Phillip Phan & Erik Lehmann & Henry Etzkowitz, 2021. "An absorptive capacity-based systems view of Covid-19 in the small business economy," International Entrepreneurship and Management Journal, Springer, vol. 17(3), pages 1419-1439, September.
    4. Herrera, Helios & Konradt, Maximilian & Ordoñez, Guillermo & Trebesch, Christoph, 2020. "Corona politics: The cost of mismanaging pandemics," Kiel Working Papers 2165, Kiel Institute for the World Economy (IfW Kiel).
    5. Hayakawa, Kazunobu & Keola, Souknilanh & Urata, Shujiro, 2022. "How effective was the restaurant restraining order against COVID-19? A nighttime light study in Japan," Japan and the World Economy, Elsevier, vol. 63(C).
    6. Mellacher, Patrick, 2020. "COVID-Town: An Integrated Economic-Epidemiological Agent-Based Model," MPRA Paper 103661, University Library of Munich, Germany.
    7. Christian Dreger & Daniel Gros, 2020. "Social Distancing Requirements and the Determinants of the COVID-19 Recession and Recovery in Europe," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 55(6), pages 365-371, November.
    8. Michael König & Adalbert Winkler, 2020. "COVID-19 and Economic Growth: Does Good Government Performance Pay Off?," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 55(4), pages 224-231, July.
    9. Paul Labonne & Leif Anders Thorsrud, 2023. "Risky news and credit market sentiment," Working Papers No 14/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    10. Huang, Wenyang & Wang, Huiwen & Wei, Yigang, 2023. "Identifying the determinants of European carbon allowances prices: A novel robust partial least squares method for open-high-low-close data," International Review of Financial Analysis, Elsevier, vol. 90(C).
    11. Klose, Jens & Tillmann, Peter, 2023. "Stock market response to Covid-19, containment measures and stabilization policies—The case of Europe," International Economics, Elsevier, vol. 173(C), pages 29-44.
    12. Rehse, Dominik & Tremöhlen, Felix, 2020. "Fostering participation in digital public health interventions: The case of digital contact tracing," ZEW Discussion Papers 20-076, ZEW - Leibniz Centre for European Economic Research.
    13. Klose, Jens & Tillmann, Peter, 2022. "The Real and Financial Impact of COVID-19 Around the World," VfS Annual Conference 2022 (Basel): Big Data in Economics 264030, Verein für Socialpolitik / German Economic Association.
    14. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2023. "Which COVID-19 information really impacts stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    15. Valery V. Kizilov, 2021. "Some Macroeconomic Consequences of COVID-19: Specifics of the 2020 World Economic Crisis," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 9-27, February.
    16. Javier G. Gómez-Pineda, 2020. "The depth, length and shape of the covid-19 recession conveyed in 2020 growth forecasts," Borradores de Economia 1123, Banco de la Republica de Colombia.
    17. Gábor Gyarmati, 2024. "Transformation of the Three Pillars of Agri-Food Sustainability around the COVID-19 Crisis—A Literature Review," Sustainability, MDPI, vol. 16(13), pages 1-33, June.
    18. Lalinsky, Tibor & Pál, Rozália, 2021. "Efficiency and effectiveness of the COVID-19 government support: Evidence from firm-level data," EIB Working Papers 2021/06, European Investment Bank (EIB).
    19. Zheng, ShiYong & Li, Xiao & Li, Juan & Li, Biqing & Hafeez, Muhammad, 2023. "Assessing the COVID-19 impact on economy, health and natural resource prices: An evidence from selected Asian economies," Resources Policy, Elsevier, vol. 87(PB).
    20. Ali Mofleh ALSHAHRANI, 2022. "Cost–Benefit Analysis of Interventions to Mitigate the Monkeypox Virus," IJERPH, MDPI, vol. 19(21), pages 1-12, October.

    More about this item

    Keywords

    Agent-based modeling; Lockdowns; Urban simulation; Contagion chains;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • R38 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Government Policy
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

    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:spr:lsprsc:v:16:y:2023:i:1:d:10.1007_s12076-023-00336-w. 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.springer.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.