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

Fares Qeadan, Trenton Honda, Lisa H. Gren, Jennifer Dailey-Provost, L. Scott Benson, James A. VanDerslice, Christina A. Porucznik, A. Blake Waters, Steven Lacey and Kimberley Shoaf
Additional contact information
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

IJERPH, 2020, vol. 17, issue 8, 1-14

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.

Keywords: COVID-19; pandemic; predictive modeling (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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