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Reopening Under COVID-19: What to Watch For

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  • Jeffrey E. Harris

Abstract

We critically analyze the currently available status indicators of the COVID-19 epidemic so that state governors will have the guideposts necessary to decide whether to further loosen or instead retighten controls on social and economic activity. Overreliance on aggregate, state-level data in Wisconsin, we find, confounds the effects of the spring primary elections and the outbreak among meat packers. Relaxed testing standards in Los Angeles may have upwardly biased the observed trend in new infection rates. Reanalysis of New Jersey data, based upon the date an ultimately fatal case first became ill rather than the date of death, reveals that deaths have already peaked in that state. Evidence from Cook County, Illinois shows that trends in the percentage of positive tests can be wholly misleading. Trends on emergency department visits for influenza-like illness, advocated by the White House Guidelines, are unlikely to be informative. Data on hospital census counts in Orange County, California suggest that healthcare system-based indicators are likely to be more reliable and informative. An analysis of cumulative infections in San Antonio, Texas, shows how mathematical models intended to guide decisions on relaxation of social distancing are severely limited by untested assumptions. Universal coronavirus testing may not on its own solve difficult problems of data interpretation and causal inference.

Suggested Citation

  • Jeffrey E. Harris, 2020. "Reopening Under COVID-19: What to Watch For," NBER Working Papers 27166, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:27166
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    File URL: http://www.nber.org/papers/w27166.pdf
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    References listed on IDEAS

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    1. Jeffrey E. Harris, 2020. "The Coronavirus Epidemic Curve is Already Flattening in New York City," NBER Working Papers 26917, National Bureau of Economic Research, Inc.
    2. Jeffrey E. Harris, 2020. "The Subways Seeded the Massive Coronavirus Epidemic in New York City," NBER Working Papers 27021, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Aparicio Fenoll, Ainoa & Grossbard, Shoshana, 2020. "Intergenerational residence patterns and Covid-19 fatalities in the EU and the US," Economics & Human Biology, Elsevier, vol. 39(C).
    2. Ainoa Aparicio & Shoshana Grossbard, 2021. "Are COVID fatalities in the US higher than in the EU, and if so, why?," Review of Economics of the Household, Springer, vol. 19(2), pages 307-326, June.
    3. Dergiades, Theologos & Milas, Costas & Panagiotidis, Theodore, 2022. "Unemployment claims during COVID-19 and economic support measures in the U.S," Economic Modelling, Elsevier, vol. 113(C).
    4. Tommaso Ferraresi & Leonardo Ghezzi & Fabio Vanni & Alessandro Caiani & Mattia Guerini & Francesco Lamperti & Severin Reissl & Giorgio Fagiolo & Mauro Napoletano & Andrea Roventini, 2021. "On the economic and health impact of the COVID-19 shock on Italian regions: A value chain approach," LEM Papers Series 2021/10, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Jeffrey E. Harris, 2021. "Los Angeles County SARS-CoV-2 Epidemic: Critical Role of Multi-generational Intra-household Transmission," Journal of Bioeconomics, Springer, vol. 23(1), pages 55-83, April.
    6. Md. Abdur Rouf, 2022. "Impact of Consumers’ Buying Behavior on Luxurious Goods during COVID 19," International Journal of Science and Business, IJSAB International, vol. 16(1), pages 59-68.
    7. Alina Butu & Ioan Sebastian Brumă & Lucian Tanasă & Steliana Rodino & Codrin Dinu Vasiliu & Sebastian Doboș & Marian Butu, 2020. "The Impact of COVID-19 Crisis upon the Consumer Buying Behavior of Fresh Vegetables Directly from Local Producers. Case Study: The Quarantined Area of Suceava County, Romania," IJERPH, MDPI, vol. 17(15), pages 1-25, July.
    8. Jeffrey E. Harris, 2020. "Data from the COVID-19 epidemic in Florida suggest that younger cohorts have been transmitting their infections to less socially mobile older adults," Review of Economics of the Household, Springer, vol. 18(4), pages 1019-1037, December.

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    More about this item

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

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