  Dengue is a vector-borne disease transmitted to humans by vectors of genus
Aedes and is a global threat with health, social, and economic impact in many
of the tropical countries including Sri Lanka. The virus transmission is
significantly impacted by environmental conditions, with a notable contribution
from elevated per-capita vector density. These conditions are dynamic in nature
and specially having the tropical climate, Sri Lanka experiences seasonal
weather patterns dominated by monsoons. In this work, we investigate the
dynamic influence of environmental conditions on dengue emergence in Colombo
district where dengue is extremely prevalent in Sri Lanka. A novel approach
leveraging the Markov chain Monte Carlo simulations has been employed to
identify seasonal patterns of dengue disease emergence, utilizing the dynamics
of weather patterns governing in the region. The newly developed algorithm
allows us to estimate the timing of dengue outbreaks with uncertainty, enabling
accurate forecasts of upcoming disease emergence patterns for better
preparedness.
