Table 1. Linear correlations and regression between meteorological factors and number of influenza positive cases (March 2012 –May 2014).

		Bivariate Correlations(Correlation between each predictors and the no. of positive cases)		Partial Correlations(Correlation between each predictor and the no. of positive cases controlling for all other predictors)		Standardized regression coefficients	t
Meteorological Factors (Predictors)	Mean (± S.D.)	r	p	r	p	Beta	t
Total Rainfall Amount (mm)	287.867 (± 168.141)	0.545	0.003*	0.176	0.423	0.265	0.817
Relative Humidity (%)	76.259 (±5.015)	0.518	0.006*	-0.143	0.514	-0.391	-0.664
No. of Rain Days	16.590 (±5.995)	0.520	0.005*	0.154	0.482	0.351	0.716
Particulate Matter (μg/m3)	38.551 (±12.352)	-0.407	0.035*	0.029	0.896	0.034	0.132
Ground Temperature (°C)	28.200 (±0.747)	-0.636	<0.001*	-0.450	0.031*	-0.545	-2.308

S.D.: standard deviation; r: Pearson correlation coefficient (high correlation: 0.5 to 1.0 or -0.5 to -1.0; moderate correlation: 0.3 to 0.5 or -0.3 to -0.5); p: level of significance (2-tailed);

* correlation is significant at the 0.05 level.