Table 3.

Factors associated with in-hospital COVID-19 case fatality rate at the department level in metropolitan France

		Univariate analyses		Multivariate analysis
		SFR (95% CI)	p value	aSFR (95% CI)	p value
Relative lag between first COVID-19-associated death and lockdown on March 17, 2020		1·01 (1·00–1·02)	0·011	1·01 (1·005–1·02)	0·0008
Population age structure estimated in 2020 per department
	Class 1: high proportion aged 25–49 years	1 (ref)	..	1 (ref)	..
	Class 2: high proportion aged <25 years	1·01 (0·91–1·13)	0·84	1·05 (0·92–1·19)	0·51
	Class 3: high proportion aged 50–85 years	1·08 (0·96–1·22)	0·19	1·25 (1·03–1·52)	0·025
	Class 4: high proportion aged >85 years	1·11 (0·93–1·33)	0·25	1·43 (1·08–1·88)	0·011
Number of intensive care beds in 2018		1·00 (0·99–1·0002)	0·29	1·00 (0·99–1·002)	0·77
Number of new chloroquine and hydroxychloroquine dispensations in pharmacies from Jan 1 to April 19, 2020		1·00 (0·99–1·0001)	0·40	1·00 (0·99–1·001)	0·89
Baseline population health and health-care services
	Class 1: high proportion of the population receiving home health assistance	1 (ref)	..	1 (ref)	..
	Class 2: high health professional density	1·01 (0·91–1·12)	0·86	0·95 (0·83–1·09)	0·46
	Class 3: high proportion of hospital stays	1·00 (0·89–1·12)	0·99	0·83 (0·69–0·99)	0·066

Analyses were made using generalised additive models with a negative binomial regression, a Gaussian kriging smoother based on geographical coordinates, and log(population) as an offset. The multivariate model included confounders according to the directed acyclic graph. aSFRs were adjusted for the different cofactors and spatial structure. SFR=standardised fatality ratio. aSFR=adjusted standardised fatality ratio. Ref=reference.