Table 1.

Models for the relationship between weather and variations in Campylobacter cases.

Variable	Coefficient	95% CI	p	Overall statistics
Summer period model (April–September)				N. obs = 78,842; X2 = 24,036; p < 0.001; R2 = 0.51
Temperature	0.09	0.09–0.10	< 0.001
Precipitation	0.30	0.29–0.32	< 0.001
Heat wave	− 0.10	− 0.15 to − 0.05	< 0.001
Heavy precipitation	0.79	0.76–0.82	< 0.001
Winter period model (October–May)				N. obs = 66,648; x2 = 18,235; p < 0.001; R2 = 0.33
Temperature	0.18	0.17–0.18	< 0.001
Precipitation	− 0.18	− 0.19 to − 0.18	< 0.001
Heavy precipitation	− 0.05	− 0.07 to − 0.03	< 0.001

Explanatory variables are related to the outcome with a 1 week time-lag (the weather in 1 week determines the following week’s number of cases).