IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v139y2020ics0960077920304744.html
   My bibliography  Save this article

Spreading of infections on random graphs: A percolation-type model for COVID-19

Author

Listed:
  • Croccolo, Fabrizio
  • Roman, H. Eduardo

Abstract

We introduce an epidemic spreading model on a network using concepts from percolation theory. The model is motivated by discussing the standard SIR model, with extensions to describe effects of lockdowns within a population. The underlying ideas and behaviour of the lattice model, implemented using the same lockdown scheme as for the SIR scheme, are discussed in detail and illustrated with extensive simulations. A comparison between both models is presented for the case of COVID-19 data from the USA. Both fits to the empirical data are very good, but some differences emerge between the two approaches which indicate the usefulness of having an alternative approach to the widespread SIR model.

Suggested Citation

  • Croccolo, Fabrizio & Roman, H. Eduardo, 2020. "Spreading of infections on random graphs: A percolation-type model for COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
  • Handle: RePEc:eee:chsofr:v:139:y:2020:i:c:s0960077920304744
    DOI: 10.1016/j.chaos.2020.110077
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077920304744
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2020.110077?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. Fernández-Villaverde, Jesús & Jones, Charles I., 2022. "Estimating and simulating a SIRD Model of COVID-19 for many countries, states, and cities," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    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. Dimou, Argyris & Maragakis, Michael & Argyrakis, Panos, 2022. "A network SIRX model for the spreading of COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    2. Huang, Binchao & Yang, Jin-Xuan & Li, Xin, 2021. "Identifying influential links to control spreading of epidemics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    3. Matouk, A.E., 2020. "Complex dynamics in susceptible-infected models for COVID-19 with multi-drug resistance," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    4. Yiannis Contoyiannis & Stavros G. Stavrinides & Michael P. Hanias & Myron Kampitakis & Pericles Papadopoulos & Rodrigo Picos & Stelios M. Potirakis, 2020. "A Universal Physics-Based Model Describing COVID-19 Dynamics in Europe," IJERPH, MDPI, vol. 17(18), pages 1-19, September.
    5. Hector Eduardo Roman & Fabrizio Croccolo, 2021. "Spreading of Infections on Network Models: Percolation Clusters and Random Trees," Mathematics, MDPI, vol. 9(23), pages 1-22, November.
    6. Ronald Manríquez & Camilo Guerrero-Nancuante & Felipe Martínez & Carla Taramasco, 2021. "Spread of Epidemic Disease on Edge-Weighted Graphs from a Database: A Case Study of COVID-19," IJERPH, MDPI, vol. 18(9), pages 1-25, April.
    7. Gandzha, I.S. & Kliushnichenko, O.V. & Lukyanets, S.P., 2021. "Modeling and controlling the spread of epidemic with various social and economic scenarios," Chaos, Solitons & Fractals, Elsevier, vol. 148(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. David Baqaee & Emmanuel Farhi, 2020. "Nonlinear Production Networks with an Application to the Covid-19 Crisis," NBER Working Papers 27281, National Bureau of Economic Research, Inc.
    2. M. Hashem Pesaran & Cynthia Fan Yang, 2022. "Matching theory and evidence on Covid‐19 using a stochastic network SIR model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1204-1229, September.
    3. Nicola Fuchs-Schündeln & Dirk Krueger & André Kurmann & Etienne Lalé & Alexander Ludwig & Irina Popova, 2023. "The Fiscal and Welfare Effects of Policy Responses to the Covid-19 School Closures," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(1), pages 35-98, March.
    4. Bisin, Alberto & Moro, Andrea, 2022. "Spatial‐SIR with network structure and behavior: Lockdown rules and the Lucas critique," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 370-388.
    5. Talal Daghriri & Michael Proctor & Sarah Matthews, 2022. "Evolution of Select Epidemiological Modeling and the Rise of Population Sentiment Analysis: A Literature Review and COVID-19 Sentiment Illustration," IJERPH, MDPI, vol. 19(6), pages 1-20, March.
    6. Chen, Xiaowei & Chong, Wing Fung & Feng, Runhuan & Zhang, Linfeng, 2021. "Pandemic risk management: Resources contingency planning and allocation," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 359-383.
    7. Andrew G. Atkeson & Karen A. Kopecky & Tao Zha, 2024. "Four Stylized Facts About Covid‐19," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(1), pages 3-42, February.
    8. Lazebnik, Teddy & Shami, Labib & Bunimovich-Mendrazitsky, Svetlana, 2023. "Intervention policy influence on the effect of epidemiological crisis on industry-level production through input–output networks," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    9. Harrison Hong & Neng Wang & Jinqiang Yang, 2020. "Implications of Stochastic Transmission Rates for Managing Pandemic Risks," NBER Working Papers 27218, National Bureau of Economic Research, Inc.
    10. Lin William Cong & Ke Tang & Bing Wang & Jingyuan Wang, 2021. "An AI-assisted Economic Model of Endogenous Mobility and Infectious Diseases: The Case of COVID-19 in the United States," Papers 2109.10009, arXiv.org.
    11. Hector Eduardo Roman & Fabrizio Croccolo, 2021. "Spreading of Infections on Network Models: Percolation Clusters and Random Trees," Mathematics, MDPI, vol. 9(23), pages 1-22, November.
    12. Nicolò Gatti & Beatrice Retali, 2021. "Fighting the spread of Covid-19 : was the Swiss lockdown worth it?," IdEP Economic Papers 2101, USI Università della Svizzera italiana.
    13. Pol Antràs & Stephen J. Redding & Esteban Rossi-Hansberg, 2023. "Globalization and Pandemics," American Economic Review, American Economic Association, vol. 113(4), pages 939-981, April.
    14. Viral Acharya & Zhengyang Jiang & Robert J. Richmond & Ernst-Ludwig von Thadden, 2020. "Divided We Fall: International Health and Trade Coordination During a Pandemic," CRC TR 224 Discussion Paper Series crctr224_2020_248, University of Bonn and University of Mannheim, Germany.
    15. Dizioli, Allan & Pinheiro, Roberto, 2021. "Information and inequality in the time of a pandemic," Journal of Economic Dynamics and Control, Elsevier, vol. 130(C).
    16. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).
    17. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," Working Papers 21-18, Federal Reserve Bank of Philadelphia.
    18. Lin Ma & Gil Shapira & Damien de Walque & Quy‐Toan Do & Jed Friedman & Andrei A. Levchenko, 2022. "The Intergenerational Mortality Trade‐Off Of Covid‐19 Lockdown Policies," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1427-1468, August.
    19. Nicola Borri & Francesco Drago & Chiara Santantonio & Francesco Sobbrio, 2021. "The “Great Lockdown”: Inactive workers and mortality by Covid‐19," Health Economics, John Wiley & Sons, Ltd., vol. 30(10), pages 2367-2382, September.
    20. Nicolò Gatti & Beatrice Retali, 2021. "Saving lives during the COVID-19 pandemic: the benefits of the first Swiss lockdown," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 157(1), pages 1-21, December.

    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:eee:chsofr:v:139:y:2020:i:c:s0960077920304744. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.