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Volume 27, Number 3—March 2021
Research

Daily Forecasting of Regional Epidemics of Coronavirus Disease with Bayesian Uncertainty Quantification, United States

Yen Ting LinComments to Author , Jacob Neumann, Ely F. Miller, Richard G. Posner, Abhishek Mallela, Cosmin Safta, Jaideep Ray, Gautam Thakur, Supriya Chinthavali, and William S. Hlavacek
Author affiliations: Los Alamos National Laboratory, Los Alamos, New Mexico, USA (Y.T. Lin, W.S. Hlavacek); Northern Arizona University, Flagstaff, Arizona, USA (J. Neumann, E.F. Miller, R.G. Posner); University of California, Davis, California, USA (A. Mallela); Sandia National Laboratories, Livermore, California, USA (C. Safta, J. Ray); Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA (G. Thakur, S. Chinthavali)

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Table 2

Estimates for the fixed parameters of compartmental model for forecasting regional epidemics of coronavirus disease, United States

Parameter Estimate Source
S0 19,216,182* US Census Bureau (13)
I0 1 Assumption
n 0† Assumption
mb 0.1 Assumption
ρE 1.1 Arons et al. (14)
ρA 0.9 Nguyen et al. (15)
kL 0.94/d Lauer et al. (12)
kQ 0.0038/d Assumption
jQ 0.4/d Assumption
fA 0.44 (16,17)
fH 0.054 Perez-Saez et al. (18)
fR 0.79 Richardson et al. (19)
cA 0.26/d Sakurai et al. (17)
cI 0.12/d Wölfel et al. (20)
cH 0.17/d Richardson et al. (19)

*All estimates listed in this table are considered to apply to all regions of interest except for n, the number of distinct social distancing periods after an initial social distancing period, and S0, the region-specific initial number of susceptible persons. The value given here for S0 is the US Census Bureau estimated total population of the New York City metropolitan statistical area. 
†n = 0, unless stated otherwise.

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