Table 2.

Coefficients and variables from temporal regression models.

	Model1	Model2	Model3	Model4	ModelC
Auto-regression
1st order	0.64*				0.31*
2nd order			0.61*
Precipitation
prcp3wk (3 wk lag)		0.35*
prcp3wk (4 wk lag)				0.43*
prcp5wk (11 wk lag)
prcp_annual (prior year)	-0.78**	-1.57*	-1.30*	-1.89*
Temperature
DW (1 wk lag)	0.16*	0.42*
DW (4 wk lag)			0.21*	0.59*
DWC (1 wk lag)					-0.08*
R2	0.80	0.70	0.65	0.58	0.42

Model 1 and Model 2 measured the effect of weather on mosquito WNv Minimum Infection Rate (MIR) and the best statistical models first with and then without an autoregressive term (AR) for MIR. Models 3 and 4 are less robust statistically but estimate MIR using weather conditions at earlier points in time to provide forecasting. The Model C models the cooling period, after amplification and includes only one option of variables (Additional File 2: Temporal, Part C includes the full equation for each model).

*p-value < 0.05

** p-value < 0.1