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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