Table 2.

Linear Regression Models Predicting Number of Days to Highest Case and Death Count for Country-level Analysis (n = 41)

Method of Classifying Exposure Variable (Number of Days Between 1st Reported Case and Mandate)	Measured Effect on Peak A: Number of Days from First Reported Case to Highest Number of Daily New Cases **
	Coefficient	95% CI	P-value
Continuous Variable	0.7	0.2, 1.1	.000*
Categorical Terciles: Early, middle, late	10.2	1.6, 18.8	.021*
Early vs. middle/late	−13.1	−28.5, 2.3	.093
Middle vs. early/late	−4.2	−19.9, 11.5	.592
Late vs. early/middle	17.4	2.5, 32.3	.023*
Categorical: Earliest 10%	−7.6	−32.8, 17.5	.543
Categorical: Latest 10%	30.0	6.9, 53.2	.012*
	Measured Effect on Peak B: Number of Days from First Reported Case to Highest Number of Daily New Deaths **
	Coefficient	95% CI	P-value
Continuous Variable	.5	0.2, 0.9	.002*
Categorical Terciles: Early, middle, late	6.1	−0.5, 12.6	.068
Early vs. middle/late	−7.4	−18.9, 4.1	.201
Middle vs. early/late	−3.2	−14.8, 8.4	.582
Late vs. early/middle	10.6	−0.6, 21.9	.063
Categorical: Earliest 10%	−4.7	−23.3, 8.5	.609
Categorical: Latest 10%	26.3	9.9, 42.7	.002*

*Significant results at p < 0.05

**Models controlled for case rates per region, defined as number of new daily cases per 100,000 persons on the date of the implemented mandate