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Volume 27, Number 9—September 2021
Research

Estimating the Impact of Statewide Policies to Reduce Spread of Severe Acute Respiratory Syndrome Coronavirus 2 in Real Time, Colorado, USA

Andrea G. Buchwald1, Jude Bayham, Jimi Adams, David Bortz, Kathryn Colborn, Olivia Zarella, Meghan Buran, Jonathan Samet, Debashis Ghosh, Rachel Herlihy, and Elizabeth J. CarltonComments to Author 
Author affiliations: Colorado School of Public Health, Aurora, Colorado, USA (A.G. Buchwald, O. Zarella, M. Buran, J. Samet, D. Ghosh, E.J. Carlton); Colorado State University, Fort Collins, Colorado, USA (J. Bayham); University of Colorado, Denver, Colorado, USA (J. Adams); University of Colorado, Boulder, Colorado, USA (D. Bortz); University of Colorado School of Medicine, Aurora (K. Colborn); Colorado Department of Public Health and Environment, Denver (R. Herlihy)

Main Article

Figure 4

Projected coronavirus disease hospitalizations, Colorado, USA, 2020, if current trajectory continued (black line) and for a range of social distancing scenarios (colored lines) generated by models calibrated at 4 time points during April‒June (fit 1: Apr 3; fit 2: April 16; fit 3: May 15; fit 4: June 16). Current trajectory was based on estimated parameters generated for each fit. Social distancing is modeled as a percent reduction in the contact rate (from baseline), and changes in social distancing are introduced 2 weeks after model fitting date. All other fitted parameters are held at the estimated values for each fit. Because peak hospitalization estimates from fit 1 were substantially higher than estimated for later fits, the y-axis is scaled to 50,000 as opposed to 25,000 for fits 2–4. Numbers in parentheses are current values.

Figure 4. Projected coronavirus disease hospitalizations, Colorado, USA, 2020, if current trajectory continued (black line) and for a range of social distancing scenarios (colored lines) generated by models calibrated at 4 time points during April‒June (fit 1: Apr 3; fit 2: April 16; fit 3: May 15; fit 4: June 16). Current trajectory was based on estimated parameters generated for each fit. Social distancing is modeled as a percent reduction in the contact rate (from baseline), and changes in social distancing are introduced 2 weeks after model fitting date. All other fitted parameters are held at the estimated values for each fit. Because peak hospitalization estimates from fit 1 were substantially higher than estimated for later fits, the y-axis is scaled to 50,000 as opposed to 25,000 for fits 2–4. Numbers in parentheses are current values.

Main Article

1Current affiliation: University of Maryland School of Medicine, Baltimore, Maryland, USA.

Page created: June 02, 2021
Page updated: August 17, 2021
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