Table 3.

Logistic regression of risk of positive immune COVID-19 test.

	Model 1: Unadjusted		Model 2: Adjusted for Age and Sex		Model 3: Adjusted for Age, Sex and Region		Full Model *
	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p
Number of customer or patient contacts a day		0.00		0.00		0.00		0.02
0 (reference)	1		1		1		1
1–5	1.8 (1.1–3.0)		1.9 (1.2–3.0)		1.6 (1.0–2.7)		1.4 (0.8–2.5)
6–10	2.2 (1.4–3.7)		2.3 (1.4–3.9)		2.1 (1.3–3.5)		1.7 (0.9–3.0)
11–20	3.1 (1.7–5.6)		3.3 (1.8–5.9)		2.6 (1.4–4.8)		2.3 (1.2–4.6)
20+	4.8 (2.6–8.6)		4.6 (2.6–8.4)		3.4 (1.8–6.4)		2.9 (1.5–5.8)
	Model 4:		Model 5:		Model 6:
Employment type		0.00		0.00		0.00		0.06
Office staff/field staff (reference)	1		1		1		1
Ambulance staff	2.2 (1.4–3.4)		2.7 (1.7–4.3)		2.1 (1.3–3.4)		1.4 (0.8–2.6)
Firefighter	0.4 (0.2–0.9)		0.6 (0.3–1.3)		0.7 (0.3–1.6)		0.6 (0.2–1.3)
Healthcare staff	1.3 (0.8–2.1)		1.2 (0.7–2.1)		1.0 (0.6–1.8)		0.8 (0.4–1.5)
Roadside assistance	0.9 (0.5–1.9)		1.3 (0.6–2.8)		1.5 (0.7–3.2)		1.0 (0.5–2.3)

Table 3 displays seven separate models, all with SARS-CoV-2 seropositivity as the dependent variable. Model 1: number of customer or patient contacts per day was included as the independent variable. Model 2: number of customer or patient contacts per day, age, and sex were included as the independent variables. Model 3: number of customer or patient contacts per day, age, sex, and region of residence were included as the independent variables. Model 4: employment type was included as the independent variable. Model 5: employment type, age, and sex were included as the independent variables. Model 6: employment type, age, sex, and region of residence were included as the independent variables. * The full model included the following covariates: sex, age, region, type of employment, and average number of customer or patient contacts during a workday.