1932

Abstract

Infectious diseases, ideas, new products, and other infectants spread in epidemic fashion through social contact. The COVID-19 pandemic, the proliferation of fake news, and the rise of antimicrobial resistance have thrust economic epidemiology into the forefront of public policy debate and reinvigorated the field. Focusing for concreteness on disease-causing pathogens, this review provides a taxonomy of economic-epidemic models, emphasizing both the biology/immunology of the disease and the economics of the social context. An economic epidemic is one whose diffusion through the agent population is generated by agents’ endogenous behavior. I highlight properties of the equilibrium epidemic trajectory and discuss ways in which public health authorities can change the game for the better by () imposing restrictions on agent activity to reduce the harm done during a viral outbreak and () enabling diagnostic-informed interventions to slow or even reverse the rise of antibiotic resistance.

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2021-08-05
2024-12-05
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Literature Cited

  1. Acemoglu D, Chernozhukov V, Werning I, Whinston MD. 2020a.. A multi-risk SIR model with optimally targeted lockdown. NBER Work. Pap. 27102
    [Google Scholar]
  2. Acemoglu D, Makhdoumi A, Malekian A, Ozdaglar A. 2020b.. Testing, voluntary social distancing and the spread of an infection. NBER Work. Pap. 27483
    [Google Scholar]
  3. Adda J. 2016.. Economic activity and the spread of viral diseases: evidence from high frequency data. . Q. J. Econ. 131:(2):891941
    [Google Scholar]
  4. Alvarez F, Argente D, Lippi F. 2021.. A simple planning problem for COVID-19 lockdown, testing, and tracing. . Am. Econ. Rev. Insights. In press
    [Google Scholar]
  5. Anderson ST, Laxminarayan R, Salant SW. 2012.. Diversify or focus? Spending to combat infectious diseases when budgets are tight. . J. Health Econ. 31:(4):65875
    [Google Scholar]
  6. Auld MC. 2003.. Choices, beliefs, and infectious disease dynamics. . J. Health Econ. 22:(3):36177
    [Google Scholar]
  7. Avery C, Bossert W, Clark A, Ellison G, Ellison SF. 2020a.. An economist's guide to epidemiology models of infectious disease. . J. Econ. Perspect. 34:(4):79104
    [Google Scholar]
  8. Avery C, Bossert W, Clark A, Ellison G, Ellison SF. 2020b.. Policy implications of models of the spread of Coronavirus: perspectives and opportunities for economists. . Covid Econ. 12::2168
    [Google Scholar]
  9. Balázs É, Guillemette Y, Murtin F, Turner D. 2021.. Walking the tightrope: avoiding a lockdown while containing the virus. . Covid Econ. 64::10134
    [Google Scholar]
  10. Banerjee AV. 1992.. A simple model of herd behavior. . Q. J. Econ. 107:(3):797817
    [Google Scholar]
  11. Banerjee AV. 1993.. The economics of rumours. . Rev. Econ. Stud. 60:(2):30927
    [Google Scholar]
  12. Bassetti S, Battegay M. 2004.. Staphylococcus aureus infections in injection drug users: risk factors and prevention strategies. . Infection 32:(3):16369
    [Google Scholar]
  13. Basu P, Bell C, Edwards T. 2020.. COVID social distancing and the poor: an analysis of the evidence for England. . Covid Econ. 45::77110
    [Google Scholar]
  14. Bauch CT, Earn DJ. 2004.. Vaccination and the theory of games. . PNAS 101:(36):1339194
    [Google Scholar]
  15. Bauch CT, Galvani AP, Earn DJ. 2003.. Group interest versus self-interest in smallpox vaccination policy. . PNAS 100:(18):1056467
    [Google Scholar]
  16. Begley S. 2020.. If everyone wore a mask, Covid-19 would be brought under control, CDC director urges. . STAT, July 14
    [Google Scholar]
  17. Bethune ZA, Korinek A. 2020.. Covid-19 infection externalities: trading off lives versus livelihoods. . Covid Econ. 11::134
    [Google Scholar]
  18. Bikhchandani S, Hirshleifer D, Welch I. 1992.. A theory of fads, fashion, custom, and cultural change as informational cascades. . J. Political Econ. 100:(5):9921026
    [Google Scholar]
  19. Bootsma MC, Ferguson NM. 2007.. The effect of public health measures on the 1918 influenza pandemic in US cities. . PNAS 104:(18):758893
    [Google Scholar]
  20. Brauer F, Castillo-Chavez C, Castillo-Chavez C. 2012.. Mathematical Models in Population Biology and Epidemiology, Vol. 2. New York:: Springer
    [Google Scholar]
  21. Brotherhood L, Kircher P, Santos C, Tertilt M. 2020.. An economic model of the Covid-19 epidemic: the importance of testing and age-specific policies. IZA Discuss. Pap. 13265 , Inst. Labor Econ., Bonn, Ger:
    [Google Scholar]
  22. book. 2013.. Antibiotic Resistance Threats in the United States, 2013. Atlanta, GA:: CDC. http://www.cdc.gov/drugresistance/pdf/ar-threats-2013-508.pdf
    [Google Scholar]
  23. Chan TY, Hamilton BH, Papageorge NW. 2016.. Health, risky behaviour and the value of medical innovation for infectious disease. . Rev. Econ. Stud. 83:(4):1465510
    [Google Scholar]
  24. Chen F. 2004.. Rational behavioral response and the transmission of STDs. . Theor. Popul. Biol. 66:(4):30716
    [Google Scholar]
  25. Chen F. 2006.. A susceptible-infected epidemic model with voluntary vaccinations. . J. Math. Biol. 53:(2):25372
    [Google Scholar]
  26. Chen F. 2012.. A mathematical analysis of public avoidance behavior during epidemics using game theory. . J. Theor. Biol. 302::1828
    [Google Scholar]
  27. Chen F, Toxvaerd F. 2014.. The economics of vaccination. . J. Theor. Biol. 363::10517
    [Google Scholar]
  28. Chotiner I. 2020.. Paul Romer's case for nationwide coronavirus testing. . New Yorker, May 3
    [Google Scholar]
  29. Cochrane JC. 2020.. An SIR model with behavior. . The Grumpy Economist, May 4. https://johnhcochrane.blogspot.com/2020/05/an-sir-model-with-behavior.html
    [Google Scholar]
  30. Cressman R, Křivan V, Garay J. 2004.. Ideal free distributions, evolutionary games, and population dynamics in multiple-species environments. . Am. Nat. 164:(4):47389
    [Google Scholar]
  31. Dall'Antonia M, Coen P, Wilks M, Whiley A, Millar M. 2005.. Competition between methicillin-sensitive and -resistant Staphylococcus aureus in the anterior nares. . J. Hosp. Infect. 61:(1):6267
    [Google Scholar]
  32. Deb R, Pai M, Vohra A, Vohra R. 2020.. Testing alone is insufficient. Work. Pap., Univ. Toronto, Toronto:
    [Google Scholar]
  33. DeBrabander F. 2020.. The great irony of America's armed anti-lockdown protesters. . Atlantic, May 13
    [Google Scholar]
  34. Del Valle S, Hethcote H, Hyman JM, Castillo-Chavez C. 2005.. Effects of behavioral changes in a smallpox attack model. . Math. Biosci. 195:(2):22851
    [Google Scholar]
  35. Dixit A. 2020.. R0for Covid research: an early estimate and policy implications. Work. Pap., Princeton Univ., Princeton, NJ:
    [Google Scholar]
  36. Ekdahl K, Hansson HB, Mölstad S, Sóderström M, Walder M, Persson K. 1998.. Limiting the spread of penicillin-resistant Streptococcus pneumoniae: experiences from the South Swedish Pneumococcal Intervention Project. . Microb. Drug Resist. 4:(2):99105
    [Google Scholar]
  37. Eksin C, Paarporn K, Weitz JS. 2019.. Systematic biases in disease forecasting—the role of behavior change. . Epidemics 27::96105
    [Google Scholar]
  38. Ellison G. 2020.. Implications of heterogeneous SIR models for analyses of COVID-19. . Covid Econ. 53::132
    [Google Scholar]
  39. Fang H, Wang L, Yang Y. 2020.. Human mobility restrictions and the spread of the Novel Coronavirus (2019-nCoV) in China. NBER Work. Pap. 26906
    [Google Scholar]
  40. Farboodi M, Jarosch G, Shimer R. 2020.. Internal and external effects of social distancing in a pandemic. . Covid Econ. 9::121
    [Google Scholar]
  41. Fine P, Clarkson J. 1986.. Individual versus public priorities in the determination of optimal vaccination policies. . Am. J. Epidemiol. 124:(6):101220
    [Google Scholar]
  42. Forsyth O. 2020.. Uncertainty and lockdown in COVID-19: an incomplete information SIR model. . Covid Econ. 52::138
    [Google Scholar]
  43. Gans J. 2020a.. Test sensitivity for infection versus infectiousness of SARS-CoV-2. . Covid Econ. 47::116
    [Google Scholar]
  44. Gans J. 2020b.. The economic consequences of = 1: towards a workable behavioural epidemiological model of pandemics. . Covid Econ. 41::2851
    [Google Scholar]
  45. Geoffard PY, Philipson T. 1996.. Rational epidemics and their public control. . Int. Econ. Rev. 37:(3):60324
    [Google Scholar]
  46. Geoffard PY, Philipson T. 1997.. Disease eradication: private versus public vaccination. . Am. Econ. Rev. 87:(1):22230
    [Google Scholar]
  47. Gersovitz M. 2011.. The economics of infection control. . Annu. Rev. Resour. Econ. 3::27796
    [Google Scholar]
  48. Glaeser EL, Gorback CS, Redding SJ. 2020.. How much does COVID-19 increase with mobility? Evidence from New York and four other US cities. . J. Urban Econ. In press. https://doi.org/10.1016/j.jue.2020.103292
    [Crossref] [Google Scholar]
  49. Goolsbee A, Syverson C. 2021.. Fear, lockdown, and diversion: comparing drivers of pandemic economic decline 2020. . J. Public Econ. 193::104311
    [Google Scholar]
  50. Greenwood J, Kircher P, Santos C, Tertilt M. 2019.. An equilibrium model of the African HIV/AIDS epidemic. . Econometrica 87:(4):1081113
    [Google Scholar]
  51. Hendrix MJ, Walde C, Findley K, Trotman R. 2020.. Absence of apparent transmission of SARS-CoV-2 from two stylists after exposure at a hair salon with a universal face covering policy—Springfield, Missouri, May 2020. . Morb. Mortal. Wkly. Rep. 69:(28):93032
    [Google Scholar]
  52. Hethcote H, Zhien M, Shengbing L. 2002.. Effects of quarantine in six endemic models for infectious diseases. . Math. Biosci. 180:(1–2):14160
    [Google Scholar]
  53. Holden R, Thornton D. 2020.. The stochastic reproduction rate of a virus. . Covid Econ. 41::10028
    [Google Scholar]
  54. Hoy M, Polborn MK. 2015.. The value of technology improvements in games with externalities: a fresh look at offsetting behavior. . J. Public Econ. 131::1220
    [Google Scholar]
  55. Hyde TB, Gilbert M, Schwartz SB, Zell ER, Watt JP, et al. 2001.. Azithromycin prophylaxis during a hospital outbreak of Mycoplasma pneumoniae pneumonia. . J. Infect. Dis. 183:(6):90712
    [Google Scholar]
  56. Jackson MO, López-Pintado D. 2013.. Diffusion and contagion in networks with heterogeneous agents and homophily. . Netw. Sci. 1:(1):4967
    [Google Scholar]
  57. Jackson MO, Malladi S, McAdams D. 2021.. Learning through the grapevine: the impact of noise and the breadth and depth of social networks. Work. Pap., Stanford Univ., Stanford, CA:
    [Google Scholar]
  58. Jones C, Philippon T, Venkateswaran V. 2020.. Optimal mitigation policies in a pandemic: social distancing and working from home. NBER Work. Pap. 26984
    [Google Scholar]
  59. Katriel G, Stone L. 2012.. Attack rates of seasonal epidemics. . Math. Biosci. 235:(1):5665
    [Google Scholar]
  60. Keppo J, Kudlyak M, Quercioli E, Smith L, Wilson A. 2020.. The behavioral SIR model, with applications to the swine flu and COVID-19 pandemics. Presentation given at the STICERD Economic Theory Seminars , Lond. Sch. Econ. Political Sci., London:. https://www.lonessmith.com/wp-content/uploads/2020/06/BSIRslides-June.pdf
    [Google Scholar]
  61. Kermack WO, McKendrick AG. 1927.. A contribution to the mathematical theory of epidemics. . Proc. R. Soc. Lond. 115:(772):70021
    [Google Scholar]
  62. Kremer M. 1996.. Integrating behavioral choice into epidemiological models of AIDS. . Q. J. Econ. 111:(2):54973
    [Google Scholar]
  63. Lakdawalla D, Sood N, Goldman D. 2006.. HIV breakthroughs and risky sexual behavior. . Q. J. Econ. 121:(3):1063102
    [Google Scholar]
  64. Laxminarayan R, Brown GM. 2001.. Economics of antibiotic resistance: a theory of optimal use. . J. Environ. Econ. Manag. 42::183206
    [Google Scholar]
  65. Laxminarayan R, Duse A, Wattal C, Zaidi AK, Wertheim HF, et al. 2013.. Antibiotic resistance—the need for global solutions. . Lancet Infect. Dis. 13:(12):105798
    [Google Scholar]
  66. Makris M, Toxvaerd F. 2020.. Great expectations: social distancing in anticipation of pharmaceutical innovations. . Covid Econ. 56::119
    [Google Scholar]
  67. Manfredi P, D'Onofrio A. 2013.. Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases. New York:: Springer
    [Google Scholar]
  68. McAdams D. 2014.. Game-Changer: Game Theory and the Art of Transforming Strategic Situations. New York:: W.W. Norton
    [Google Scholar]
  69. McAdams D. 2017.. Resistance diagnosis and the changing epidemiology of antibiotic resistance. . Ann. N. Y. Acad. Sci. 1388:(1):517
    [Google Scholar]
  70. McAdams D. 2020a.. Economic epidemiology in the wake of Covid-19. . Covid Econ. 48::145
    [Google Scholar]
  71. McAdams D. 2020b.. Nash SIR: an economic-epidemiological model of strategic behavior during a viral epidemic. . Covid Econ. 16::11534
    [Google Scholar]
  72. McAdams D, Day T. 2020.. The political economy of a viral epidemic. Work. Pap., Duke Univ., Durham, NC:
    [Google Scholar]
  73. McAdams D, Song Y. 2020a.. Strategic social distancing with coordination motives. Work. Pap., Duke Univ., Durham, NC:
    [Google Scholar]
  74. McAdams D, Song Y. 2020b.. Viral social learning. Work. Pap., Duke Univ., Durham, NC:
    [Google Scholar]
  75. McAdams D, Wollein Waldetoft K, Tedijanto C, Lipsitch M, Brown SP. 2019.. Resistance diagnostics as a public health tool to combat antibiotic resistance: a model-based evaluation. . PLOS Biol. 17:(5):e3000250
    [Google Scholar]
  76. Meyers LA, Newman ME, Martin M, Schrag S. 2003.. Applying network theory to epidemics: control measures for Mycoplasma pneumoniae outbreaks. . Emerg. Infect. Dis. 9:(2):20410
    [Google Scholar]
  77. Milgrom P, Roberts J. 1990.. Rationalizability, learning, and equilibrium in games with strategic complementarities. . Econometrica 58:(6):125577
    [Google Scholar]
  78. Mitchell J. 2020.. State shutdowns have taken at least a quarter of U.S. economy offline. . Wall Street Journal, April 5
    [Google Scholar]
  79. Moisse K. 2012.. Antibiotic resistance could bring “end of modern medicine. ABC News, March 16
    [Google Scholar]
  80. Newman ME. 2002.. Spread of epidemic disease on networks. . Phys. Rev. E 66:(1):016128
    [Google Scholar]
  81. Perisic A, Bauch CT. 2009.. Social contact networks and disease eradicability under voluntary vaccination. . PLOS Comput. Biol. 5:(2):e1000280
    [Google Scholar]
  82. Philipson T. 2000.. Economic epidemiology and infectious diseases. . In Handbook of Health Economics, Vol. 1, ed. AJ Culyer, JP Newhouse , pp. 176199. Amsterdam:: Elsevier
    [Google Scholar]
  83. Philipson TJ, Posner RA. 1993.. Private Choices and Public Health: The AIDS Epidemic in an Economic Perspective. Cambridge, MA:: Harvard Univ. Press
    [Google Scholar]
  84. Prakash BA, Chakrabarti D, Valler NC, Faloutsos M, Faloutsos C. 2012.. Threshold conditions for arbitrary cascade models on arbitrary networks. . Knowl. Inform. Syst. 33:(3):54975
    [Google Scholar]
  85. Quercioli E, Smith L. 2006.. Contagious matching games. Work. Pap., Univ. Tex. Rio Grande Valley, Edinburg:
    [Google Scholar]
  86. Reluga TC. 2010.. Game theory of social distancing in response to an epidemic. . PLOS Comput. Biol. 6:(5). https://doi.org/10.1371/journal.pcbi.1000793
    [Crossref] [Google Scholar]
  87. Reluga TC. 2013.. Equilibria of an epidemic game with piecewise linear social distancing cost. . Bull. Math. Biol. 75:(10):196184
    [Google Scholar]
  88. book. 2014.. Antimicrobial resistance: tackling a crisis for the future health and wealth of nations. AMR Rev. Pap., UK Dep. Health, London:
    [Google Scholar]
  89. book. 2016.. Tackling drug-resistant infections globally: final report and recommendations. AMR Rep., UK Dep. Health, London:
    [Google Scholar]
  90. Ross R. 1916.. An application of the theory of probabilities to the study of a priori pathometry—part I. . Proc. R. Soc. Lond. 92:(638):20430
    [Google Scholar]
  91. Ross R, Hudson HP. 1917.. An application of the theory of probabilities to the study of a priori pathometry—part II. . Proc. R. Soc. Lond. 93:(650):21225
    [Google Scholar]
  92. Rowthorn RE, Laxminarayan R, Gilligan CA. 2009.. Optimal control of epidemics in metapopulations. . J. R. Soc. Interface 6:(41):113544
    [Google Scholar]
  93. Rowthorn RE, Maciejowski J. 2020.. A cost-benefit analysis of the Covid-19 disease. . Oxf. Rev. Econ. Policy 36:(S1):S3855
    [Google Scholar]
  94. Rowthorn RE, Toxvaerd F. 2012.. The optimal control of infectious diseases via prevention and treatment. CEPR Discuss. Pap. DP8925 , Cent. Econ. Policy Res., London:
    [Google Scholar]
  95. Roy S, Sabarwal T. 2010.. Monotone comparative statics for games with strategic substitutes. . J. Math. Econ. 46:(5):793806
    [Google Scholar]
  96. Salanié F, Treich N. 2020.. Public and private incentives for self-protection. . Geneva Risk Insur. Rev. 45::10413
    [Google Scholar]
  97. Serfling RE. 1952.. Historical review of epidemic theory. . Hum. Biol. 24:(3):14566
    [Google Scholar]
  98. Sims C, Finnoff D. 2020.. Uncertainty, hysteresis and lockdowns. . Covid Econ. 54::2961
    [Google Scholar]
  99. Solberg CO. 2000.. Spread of Staphylococcus aureus in hospitals: causes and prevention. . Scand. J. Infect. Dis. 32:(6):58795
    [Google Scholar]
  100. Talamas E, Vohra R. 2018.. Go big or go home: a free and perfectly safe but only partially effective vaccine can make everyone worse off. PIER Work. Pap. 18-006 , Univ. Pa., Philadelphia:
    [Google Scholar]
  101. Toxvaerd F. 2019.. Rational disinhibition and externalities in prevention. . Int. Econ. Rev. 60:(4):173755
    [Google Scholar]
  102. Toxvaerd F. 2020.. Equilibrium social distancing. . Covid Econ. 15::11033
    [Google Scholar]
  103. Troger T. 2020.. Optimal testing and social distancing of individuals with private health signals. . Covid Econ. 55::144
    [Google Scholar]
  104. book. 2014.. Antimicrobial Resistance: Global Report on Surveillance. Geneva, Switz:: WHO
    [Google Scholar]
  105. Yamin D, Gavious A. 2013.. Incentives' effect in influenza vaccination policy. . Manag. Sci. 59:(12):266786
    [Google Scholar]
  106. Yang JJ, Chang TW, Jiang Y, Kao HJ, Chiou BH, et al. 2018.. Commensal Staphylococcus aureus provokes immunity to protect against skin infection of methicillin-resistant Staphylococcus aureus. . Int. J. Mol. Sci. 19:(5):1290
    [Google Scholar]
  107. Zarocostas J. 2020.. How to fight an infodemic. . Lancet 395:(10225):676
    [Google Scholar]
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