Table 1. Linear regression model results of associations between potential weather, socio-demographic, and viral predictors with norovirus season strength.
| Bivariate – percent change (95%CI) | Multivariate – percent change (95%CI) | |||||
| Dataset | Cases | Outbreaks | Combined | Cases | Outbreaks | Combined |
| Latitude (degree) | −0.09 (−0.41, 0.24) | 0.06 (−0.16, 0.27) | 0.02 (−0.15, 0.19) | |||
| Avg winter temp (°C) | −0.20 (−0.97, 0.58) | −0.69 (−2.04, 0.69) | −0.34 (−1.01, 0.34) | −0.97 (−1.77, −0.17) | ||
| Peak/ trough temp ratio (°C) | 0.21 (−0.21, 0.64) | −0.28 (−0.73, 0.18) | −0.02 (−0.33, 0.29) | |||
| Avg rain in wettest month (cm) | 0.16 (−0.51, 0.84) | 1.78 (0.44, 3.13) | 0.51 (−0.09, 1.11) | 0.67 (−0.32, 1.67) | 2.61 (1.16, 4.08) | 1.01 (0.29, 1.74) |
| GDP (per $1,000) | 0.00 (0.0, 0.0) | 0.00 (0.0, 0.0) | 0.00 (0.0, 0.0) | 0.00 (0.0, 0.0) | ||
| Crude birth rate (births/1,000 ppl) | 0.03 (−1.12, 1.19) | −7.03 (−10.93, −2.96) | −0.44 (−1.55, 0.69) | −8.35 (−12.11, −4.43) | ||
| Pop density (pl/km2) | 0.02 (−0.01, 0.06) | 0.01 (−0.03, 0.05) | 0.02 (−0.01, 0.05) | −0.04 (−0.08, 0.01) | ||
| New strain year | −7.18 (−19.93, 7.6) | −4.9 (−17.89, 10.15) | −6.04 (−15.23, 4.15) | |||
Norovirus season strength is defined as peak to mean ratio of normalized monthly proportion of norovirus cases or outbreaks for each season-year. Estimates are beta coefficients and can be interpreted as expected percent change in norovirus season strength for a one-unit increase in the predictor variable. Results for multivariate linear regression models are only for variables included in the final models based on forward selection (see text for further explanation of modeling strategy).