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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