Geographically weighted regression analysis of dengue incidence in the Philippines. - Dureza, Christine Joy C.
The association of temperature, relative humidity, rainfall, and population density with dengue incidence was determined using Geographically Weighted Regression (GWR) wherein the regression coefficients are allowed to vary according to geographic area. The impact of two bandwidths, fixed and adaptive, of Gaussian-shaped kernel on model fit of the GWR models was compared. The results showed that GWR models using adaptive bandwidth comparatively provided lower AIC and higher r2 values. The best fit GWR model was the model that utilized adaptive bandwidth. This model contains the independent variable minimum temperature and population density expressed as: dengue incidence = β0 (ui,vi) + β1 (ui,vi) (population density) + β2 (ui,vi) (minimum temperature), where, β0 = 6.45 to 76.31 ; β1 = -0.58 to 2.67 ; β2 = -2.83 to 0.01. GIS provided assistance to the GWR analysis to further interpret the results by pinpointing areas where the association was important and where the model was working best. Particularly, only in the provinces of Albay, Mindoro Occidental, Mindoro Oriental, Palawan and Samar where both minimum temperature and population density were seen to have a significant effect to dengue incidence having a negative and positive relationship, respectively.