D-TECT uses historical dengue incidence data together with environmental and climatic variables such as rainfall, temperature, humidity, wind spreed, and wind direction to predict potential risk in the coming weeks.

By analyzing past patterns and trends, the model estimates the level of dengue risk (classified as Low, Moderate, or High) for both barangay-level and citywide forecasts.

The system applies time-series and machine learning techniques to identify correlations between climate conditions and dengue transmission, providing insights for early warning and preventive planning.

Note: This system provides predictions based on historical data and observed trends, and the results should be interpreted as estimates rather than exact outcomes.