Predicting Culex pipiens/restuans population dynamics by interval lagged weather data

Parasites & Vectors

Table 2 Model summary

	β	SE	z value	p
Daily data
Intercept	−22.3142	0.5200	−42.9118	< 0.0001
D _{0, 0}	1.0901	0.0281	38.8183	< 0.0001
D _{85, 85}	0.6453	0.0216	29.8125	< 0.0001
T _{0, 0}	0.0441	0.0037	11.8177	< 0.0001
T _{12, 1}	−0.0751	0.0065	−11.5170	< 0.0001
P _{0, 0}	0.0044	0.0013	3.4509	0.0006
P _{51, 16}	0.0990	0.0081	12.2828	< 0.0001
H _{0, 0}	−0.0131	0.0013	−10.2594	< 0.0001
H _{38, 1}	0.0453	0.0027	17.0574	< 0.0001
W _{119, 86}	−0.5238	0.0325	−16.1039	< 0.0001
Weekly data
Intercept	−22.4553	1.4451	−15.5389	< 0.0001
D _{0, 0}	1.1318	0.0820	13.8066	< 0.0001
D _{13, 13}	0.6034	0.0551	10.9537	< 0.0001
T _{0, 0}	0.0386	0.0150	2.5816	0.0098
T _{1, 1}	−0.0612	0.0148	−4.1208	< 0.0001
P _{7, 3}	0.1036	0.0208	4.9686	< 0.0001
H _{4, 1}	0.0354	0.0061	5.7550	< 0.0001
W _{17, 12}	−0.5573	0.0940	−5.9315	< 0.0001

Summary of the regression model after the parameter optimization of the lags (OPT) from the daily and weekly data (trainings data set). For each quantity the regression coefficient β and the standard error of the regression coefficient SE, the test statistic (z value) and the p-value is given. The used environmental quantities were D - daytime length, T - temperature, P - precipitation, H - relative humidity, and W - wind speed. The subscript 0,0 represents the environmental quantity at the time of capture. Two subscripts indicate the beginning and the end of the lagged time period.

ISSN: 1756-3305