2 Hypothesis

$H_1:$ To forecast dengue incidences in a particular district, the influence of the data from past dengue incidences and socio-economic data from its surrounding districts is statistically significant.

$H_2:$ To forecast dengue incidences, a data-driven interpretable, non-parametric time-series forecasting approach (e.g. Generalized Additive Models (GAMs)) is statistically better than parametric modeling approaches (e.g. ARIMA.)

$H_3:$ To forecast dengue incidences, an ensemble forecasting model with Bayesian Network and time-series modeling approach is statistically better than the individual models.