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Naive Forecast for COVID-19 in Utah Based on the South Korea and Italy Models-the Fluctuation between Two Extremes

Author

Listed:
  • Fares Qeadan

    (Division of Public Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA)

  • Trenton Honda

    (Division of Physician Assistant Studies, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA)

  • Lisa H. Gren

    (Division of Public Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA)

  • Jennifer Dailey-Provost

    (Division of Public Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA)

  • L. Scott Benson

    (Division of Public Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA)

  • James A. VanDerslice

    (Division of Public Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA)

  • Christina A. Porucznik

    (Division of Public Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA)

  • A. Blake Waters

    (Division of Public Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA)

  • Steven Lacey

    (Division of Public Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA)

  • Kimberley Shoaf

    (Division of Public Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT 84108, USA)

Abstract

Differences in jurisdictional public health actions have played a significant role in the relative success of local communities in combating and containing the COVID-19 pandemic. We forecast the possible COVID-19 outbreak in one US state (Utah) by applying empirical data from South Korea and Italy, two countries that implemented disparate public health actions. Forecasts were created by aligning the start of the pandemic in Utah with that in South Korea and Italy, getting a short-run forecast based on actual daily rates of spread, and long-run forecast by employing a log-logistic model with four parameters. Applying the South Korea model, the epidemic peak in Utah is 169 cases/day, with epidemic resolution by the end of May. Applying the Italy model, new cases are forecast to exceed 200/day by mid-April, with the potential for 250 new cases a day at the epidemic peak, with the epidemic continuing through the end of August. We identify a 3-month variation in the likely length of the pandemic, a 1.5-fold difference in the number of daily infections at outbreak peak, and a 3-fold difference in the expected cumulative cases when applying the experience of two developed countries in handling this virus to the Utah context.

Suggested Citation

  • Fares Qeadan & Trenton Honda & Lisa H. Gren & Jennifer Dailey-Provost & L. Scott Benson & James A. VanDerslice & Christina A. Porucznik & A. Blake Waters & Steven Lacey & Kimberley Shoaf, 2020. "Naive Forecast for COVID-19 in Utah Based on the South Korea and Italy Models-the Fluctuation between Two Extremes," IJERPH, MDPI, vol. 17(8), pages 1-14, April.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:8:p:2750-:d:346208
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    Citations

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    Cited by:

    1. Ali Asgary & Svetozar Zarko Valtchev & Michael Chen & Mahdi M. Najafabadi & Jianhong Wu, 2020. "Artificial Intelligence Model of Drive-Through Vaccination Simulation," IJERPH, MDPI, vol. 18(1), pages 1-10, December.
    2. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    3. Fares Qeadan & Nana Akofua Mensah & Benjamin Tingey & Rona Bern & Tracy Rees & Sharon Talboys & Tejinder Pal Singh & Steven Lacey & Kimberley Shoaf, 2020. "What Protective Health Measures Are Americans Taking in Response to COVID-19? Results from the COVID Impact Survey," IJERPH, MDPI, vol. 17(17), pages 1-18, August.

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