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Table 2 Coefficients and variables from temporal regression models.

From: Local impact of temperature and precipitation on West Nile virus infection in Culex species mosquitoes in northeast Illinois, USA

  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*
R 2 0.80 0.70 0.65 0.58 0.42
  1. 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).
  2. *p-value < 0.05
  3. ** p-value < 0.1