IDEAS home Printed from https://ideas.repec.org/p/bge/wpaper/1193.html
   My bibliography  Save this paper

Public Health Interventions in the Face of Pandemics: Network Structure, Social Distancing, and Heterogeneity

Author

Listed:
  • Mohammad Ghaderi

Abstract

Complexity, resulting from interactions among many components, is a characterizing property of healthcare systems and related decisions. Such complexity scales up quickly in the face of pandemics, where multiple sources of uncertainty are involved and various contextual factors interacting with policy parameters yield outcome distribution. This paper presents a uni ed framework to assist and inform policy decisions in confronting pandemics. The general framework consists of a model of contagion that makes the policy- relevant variables explicit and exogenous, establishes links between them and the main features of the environment in which the policy is going to be implemented, and treats various sources of uncertainty at different layers of the system. At the macro level, special attention is devoted to the network structure, for which we provide a simple characterization based on two constructive factors. Our results show that by conditioning on these two factors, a large proportion of the stochasticity resulted from the inherent randomness in the network can be captured. Components of the model are synthesized in a broader agent-based model that enables accounting for heterogeneous individual-level attributes that collectively yield the macro-level outcomes. Using several stylized examples and a comprehensive controlled experiment, insights on the overall tendency of the complex system in terms of multidimensional outputs are derived across a range of scenarios and under various types of policy conditions.

Suggested Citation

  • Mohammad Ghaderi, 2020. "Public Health Interventions in the Face of Pandemics: Network Structure, Social Distancing, and Heterogeneity," Working Papers 1193, Barcelona School of Economics.
  • Handle: RePEc:bge:wpaper:1193
    as

    Download full text from publisher

    File URL: https://www.barcelonagse.eu/sites/default/files/working_paper_pdfs/1193.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Warwick McKibbin & Roshen Fernando, 2021. "The Global Macroeconomic Impacts of COVID-19: Seven Scenarios," Asian Economic Papers, MIT Press, vol. 20(2), pages 1-30, Summer.
    2. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 2000. "Scale-free characteristics of random networks: the topology of the world-wide web," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 281(1), pages 69-77.
    3. Francesc Obiols-Homs, 2020. "Precaution, Social Distancing and Tests in a Model of Epidemic Disease," Working Papers 1173, Barcelona School of Economics.
    4. Luca Fornaro & Martin Wolf, 2020. "Covid-19 coronavirus and macroeconomic policy," Economics Working Papers 1713, Department of Economics and Business, Universitat Pompeu Fabra.
    5. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    6. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    7. David Berger & Kyle Herkenhoff & Chengdai Huang & Simon Mongey, 2022. "Testing and Reopening in an SEIR Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 43, pages 1-21, January.
    8. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
    9. Facundo Piguillem & Liyan Shi, 2022. "Optimal Covid-19 Quarantine and Testing Policies," The Economic Journal, Royal Economic Society, vol. 132(647), pages 2534-2562.
    10. Leombruni, Roberto & Richiardi, Matteo, 2005. "Why are economists sceptical about agent-based simulations?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 103-109.
    11. Lesley Chiou & Catherine Tucker, 2020. "Social Distancing, Internet Access and Inequality," NBER Working Papers 26982, National Bureau of Economic Research, Inc.
    12. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    13. David Berger & Kyle Herkenhoff & Chengdai Huang & Simon Mongey, 2022. "Testing and Reopening in an SEIR Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 43, pages 1-21, January.
    14. Robert Marks, 2007. "Validating Simulation Models: A General Framework and Four Applied Examples," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 265-290, October.
    15. Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017. "Bayesian estimation of agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
    16. Andrew Atkeson, 2020. "What Will Be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios," NBER Working Papers 26867, National Bureau of Economic Research, Inc.
    17. Muller, Eitan & Peres, Renana, 2019. "The effect of social networks structure on innovation performance: A review and directions for research," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 3-19.
    18. Veronica Guerrieri & Guido Lorenzoni & Ludwig Straub & Iván Werning, 2022. "Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?," American Economic Review, American Economic Association, vol. 112(5), pages 1437-1474, May.
    19. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    20. Anna D. Broido & Aaron Clauset, 2019. "Scale-free networks are rare," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    21. Sculli, D & Wong, KL, 1985. "The maximum and sum of two beta variables and the analysis of PERT networks," Omega, Elsevier, vol. 13(3), pages 233-240.
    22. Hazhir Rahmandad & John Sterman, 2008. "Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models," Management Science, INFORMS, vol. 54(5), pages 998-1014, May.
    23. Réka Albert & Hawoong Jeong & Albert-László Barabási, 1999. "Diameter of the World-Wide Web," Nature, Nature, vol. 401(6749), pages 130-131, September.
    24. Vahideh Manshadi & Sidhant Misra & Scott Rodilitz, 2020. "Diffusion in Random Networks: Impact of Degree Distribution," Operations Research, INFORMS, vol. 68(6), pages 1722-1741, November.
    25. Christophe Van den Bulte & Stefan Stremersch, 2004. "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test," Marketing Science, INFORMS, vol. 23(4), pages 530-544, July.
    26. Eric Abrahamson & Lori Rosenkopf, 1997. "Social Network Effects on the Extent of Innovation Diffusion: A Computer Simulation," Organization Science, INFORMS, vol. 8(3), pages 289-309, June.
    27. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331, January.
    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. Mohammad Ghaderi, 2020. "Public health interventions in the face of pandemics: network structure, social distancing, and heterogeneity," Economics Working Papers 1732, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Ghaderi, Mohammad, 2022. "Public health interventions in the face of pandemics: Network structure, social distancing, and heterogeneity," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1016-1031.
    3. Joshua Bernstein & Alexander W. Richter & Nathaniel A. Throckmorton, 2020. "COVID-19: A View from the Labor Market," Working Papers 2010, Federal Reserve Bank of Dallas.
    4. Abel Brodeur & David Gray & Anik Islam & Suraiya Bhuiyan, 2021. "A literature review of the economics of COVID‐19," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1007-1044, September.
    5. Garriga, Carlos & Manuelli, Rody & Sanghi, Siddhartha, 2022. "Optimal management of an epidemic: Lockdown, vaccine and value of life," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    6. Francesco Busato & Bruno Chiarini & Gianluigi Cisco & Maria Ferrara & Elisabetta Marzano, 2020. "Lockdown Policies: A Macrodynamic Perspective for Covid-19," CESifo Working Paper Series 8465, CESifo.
    7. Charles A.E. Goodhart & Dimitrios P. Tsomocos & Xuan Wang, 2023. "Support for small businesses amid COVID‐19," Economica, London School of Economics and Political Science, vol. 90(358), pages 612-652, April.
    8. Christian Moser & Pierre Yared, 2022. "Pandemic Lockdown: The Role of Government Commitment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 46, pages 27-50, October.
    9. Ma, Chang & Rogers, John H. & Zhou, Sili, 2020. "Modern pandemics: Recession and recovery," BOFIT Discussion Papers 16/2020, Bank of Finland Institute for Emerging Economies (BOFIT).
    10. Cem Çakmaklı & Selva Demiralp & Ṣebnem Kalemli-Özcan & Sevcan Yesiltas & Muhammed A. Yildirim, 2020. "COVID-19 and Emerging Markets: A SIR Model, Demand Shocks and Capital Flows," NBER Working Papers 27191, National Bureau of Economic Research, Inc.
    11. V. V. Chari & Rishabh Kirpalani & Christopher Phelan, 2021. "The Hammer and the Scalpel: On the Economics of Indiscriminate versus Targeted Isolation Policies during Pandemics," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 42, pages 1-14, October.
    12. Korinek, Anton & Bethune, Zachary, 2020. "COVID-19 Infection Externalities: Trading Off Lives vs. Livelihoods," CEPR Discussion Papers 14596, C.E.P.R. Discussion Papers.
    13. Anna Houstecka & Dongya Koh & Raül Santaeulàlia-Llopis, 2020. "Contagion at Work," Working Papers 1225, Barcelona School of Economics.
    14. Ricardo J Caballero & Alp Simsek, 2021. "A Model of Endogenous Risk Intolerance and LSAPs: Asset Prices and Aggregate Demand in a “COVID-19” Shock [Financial intermediaries and the cross-section of asset returns]," Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5522-5580.
    15. Łukasz Rachel, 2020. "An Analytical Model of Covid-19 Lockdowns," Discussion Papers 2029, Centre for Macroeconomics (CFM).
    16. Brotherhood, Luiz & Kircher, Philipp & Santos, Cezar & Tertilt, Michèle, 2020. "An Economic Model of the COVID-19 Epidemic: The Importance of Testing and Age-Specific Policies," IZA Discussion Papers 13265, Institute of Labor Economics (IZA).
    17. Funke, Michael & Tsang, Andrew, 2020. "The People’s bank of China’s response to the coronavirus pandemic: A quantitative assessment," Economic Modelling, Elsevier, vol. 93(C), pages 465-473.
    18. Chang Ma & John H. Rogers & Sili Zhou, 2020. "Modern Pandemics: Recession and Recovery," International Finance Discussion Papers 1295, Board of Governors of the Federal Reserve System (U.S.).
    19. Giuli, Francesco & Maugeri, Gabriele, 2022. "Economic Effects of Covid-19 and Non-Pharmaceutical Interventions: applying a SEIRD-RBC Model to Italy," MPRA Paper 114673, University Library of Munich, Germany.
    20. Giuli, Francesco & Maugeri, Gabriele, 2023. "Economic Effects of Covid-19 and Non-Pharmaceutical Interventions: applying a SEIRD-Macro Model to Italy," MPRA Paper 118422, University Library of Munich, Germany.

    More about this item

    Keywords

    public health interventions; social contagion; random networks; social distancing; simulation;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • I1 - Health, Education, and Welfare - - Health

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bge:wpaper:1193. 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: Bruno Guallar (email available below). General contact details of provider: https://edirc.repec.org/data/bargses.html .

    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.