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Table 2 Linear regression coefficients for factors associated with prediction accuracy (AEIL)

From: Predictive accuracy of a hierarchical logistic model of cumulative SARS-CoV-2 case growth until May 2020

 

Number of data points in weeks

(95% CI)

Growth in logarithmic case counts until estimation

(95% CI)

Interaction term

(95% CI)

Day of estimation

−0.077*** (− 0.114 to − 0.040)

−0.016 (− 0.055 to 0.023)

0.002 (− 0.005 to 0.009)

Two weeks forecast

−0.073* (− 1.304 to − 0.015)

−0.100** (− 1.614 to − 0.039)

0.011* (0.000 to 0.022)

One month forecast

− 0.131** (− 0.216 to − 0.046)

−0.145** (− 0.235 to − 0.054)

0.017* (0.001 to 0.034)

Two months forecast

−0.242*** (− 0.361 to − 0.124)

−0.242*** (− 0.368 to − 0.117)

0.032** (0.010 to 0.055)

  1. AEIL = absolute difference between logarithmic predicted and observed case counts; CI = confidence interval; *p < .050; **p < .010; ***p < .001