Climate change is altering the distribution and seasonality of vector-borne diseases, posing a growing public health challenge. This study developed predictive models linking temperature, precipitation, and humidity to dengue incidence in urban regions over a ten-year period. Using meteorological data and reported dengue cases (n=15,000), generalized additive models were constructed to forecast outbreak risk. Results indicated that a 1°C increase in average monthly temperature correlated with a 12% rise in dengue cases, while periods of heavy rainfall amplified mosquito breeding and transmission risk. The findings underscore the importance of integrating climate data into public health planning and vector control strategies to mitigate dengue outbreaks in urban environments.

Keywords:
Dengue, Vector-Borne Diseases, Climate Change, Predictive Modeling, Urban Health