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Learning Epidemiology by Doing: The Empirical Implications of a Spatial SIR Model with Behavioral Responses

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  • Bisin, Alberto
  • Moro, Andrea

Abstract

We simulate a spatial behavioral model of the diffusion of an infection to understand the role of geographical characteristics: the number and distribution of outbreaks, population size, density, and agents' movements. We show that several invariance properties of the SIR model with respect to these variables do not hold when agents are placed in a (two dimensional ) geographical space. Indeed, local herd immunity plays a fundamental role in changing the dynamics of the infection. We also show that geographical factors affect how behavioral responses affect the epidemics. We derive relevant implications for the estimation of epidemiological models with panel data from several geographical units.

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  • Bisin, Alberto & Moro, Andrea, 2020. "Learning Epidemiology by Doing: The Empirical Implications of a Spatial SIR Model with Behavioral Responses," MPRA Paper 101059, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:101059
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    Cited by:

    1. Dirk Niepelt & Mart n Gonzalez-Eiras, 2020. "Optimally Controlling an Epidemic," Diskussionsschriften dp2019, Universitaet Bern, Departement Volkswirtschaft.
    2. 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.
    3. Bello, Piera & Rocco, Lorenzo, 2022. "Education and COVID-19 excess mortality," Economics & Human Biology, Elsevier, vol. 47(C).
    4. Bisin, Alberto & Gottardi, Piero, 2021. "Efficient policy interventions in an epidemic," Journal of Public Economics, Elsevier, vol. 200(C).
    5. Joshua S. Gans, 2020. "The Economic Consequences of R̂ = 1: Towards a Workable Behavioural Epidemiological Model of Pandemics," NBER Working Papers 27632, National Bureau of Economic Research, Inc.
    6. 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.
    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. Giannone, Elisa & Paixão, Nuno & Pang, Xinle, 2022. "JUE Insight: The geography of pandemic containment," Journal of Urban Economics, Elsevier, vol. 127(C).
    9. Badi H. Baltagi & Ying Deng & Jing Li & Zhenlin Yang, 2023. "Cities in a pandemic: Evidence from China," Journal of Regional Science, Wiley Blackwell, vol. 63(2), pages 379-408, March.
    10. Mario J. Crucini & Oscar O'Flaherty, 2020. "Stay-at-Home Orders in a Fiscal Union," NBER Working Papers 28182, National Bureau of Economic Research, Inc.
    11. Glaeser, Edward L. & Gorback, Caitlin & Redding, Stephen J., 2022. "JUE Insight: How much does COVID-19 increase with mobility? Evidence from New York and four other U.S. cities," Journal of Urban Economics, Elsevier, vol. 127(C).
    12. Jacek Rothert & Ryan Brady & Michael Insler, 2020. "The Fragmented United States of America: The impact of scattered lock-down policies on country-wide infections," Departmental Working Papers 65, United States Naval Academy Department of Economics.
    13. INOUE Tomoo & OKIMOTO Tatsuyoshi, 2022. "Exploring the Dynamic Relationship between Mobility and the Spread of COVID-19, and the Role of Vaccines," Discussion papers 22011, Research Institute of Economy, Trade and Industry (RIETI).
    14. Borsati, Mattia & Nocera, Silvio & Percoco, Marco, 2022. "Questioning the spatial association between the initial spread of COVID-19 and transit usage in Italy," Research in Transportation Economics, Elsevier, vol. 95(C).
    15. Richard Breen & John Ermisch, 2021. "The distributional impact of COVID-19: Geographic variation in mortality in England," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(17), pages 397-414.
    16. Redding, Stephen & Glaeser, Edward & Gorback, Caitlin, 2020. "How Much Does COVID-19 Increase with Mobility? Evidence from New York and Four Other US Cities," CEPR Discussion Papers 15050, C.E.P.R. Discussion Papers.
    17. Desmet, Klaus & Wacziarg, Romain, 2022. "JUE Insight: Understanding spatial variation in COVID-19 across the United States," Journal of Urban Economics, Elsevier, vol. 127(C).
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    More about this item

    Keywords

    Covid-19; Spatial-SIR; SIR; Behavioral responses; Infection dynamics;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • I1 - Health, Education, and Welfare - - Health

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