. 2021 Jan 9;104:370–372. doi: 10.1016/j.ijid.2020.12.083

Table 1.

Bivariable and multivariable linear regression models exploring predictors of COVID-19 testing at the country-level (N = 86).

Variable	Bivariable models			Multivariable models
				Model 1 (Health expenditure only)			Model 2 (UHC only)			Model 3 (Health expenditure and UHC)
	$\hat{β}$	SE	Z-value	$\hat{β}$	SE	Z-value	$\hat{β}$	SE	Z-value	$\hat{β}$	SE	Z-value
HDI	8.05^***	1.95	4.13	7.62^*	3.73	2.04	9.07^*	3.60	2.52	10.22^*	4.06	2.52
UHC	0.06^***	0.02	3.40	–	–	–	−0.06	0.04	−1.58	−0.06	0.04	−1.53
Health expenditure (USD)	0.00016^***	0.00	3.33	−0.00007	0.00	−0.74	–	–	–	−0.00006	0.00	−0.63
Urban population (% of total population)	0.05^***	0.01	4.38	0.04^*	0.02	2.21	0.05^**	0.02	2.64	0.04^*	0.02	2.55
Service industry (% total employment)	0.05^***	0.01	3.88	−0.02	0.03	−0.68	−0.02	0.03	−0.55	−0.01	0.03	−0.42
Air pollution (ug/m³)	−0.02	0.01	−1.87	−0.01	0.01	−0.796	−0.01	0.01	−1.13	−0.01	0.01	−1.15

UHC: Universal Health Coverage; HDI: Human Development Index; and SE: Standard Error.

p-value < 0.05.

^**

p-value < 0.01.

^***

p-value < 0.0001.