Recurring outbreaks of dengue during past decades have affected public health and burdened resource constraint health systems across the world. Transmission of such diseases is a conjugation of various complex factors including vector dynamics, transmission mechanism, environmental conditions, cultural behaviours, and public health policies. Modelling and predicting early outbreaks is the key to an effective response to control the spread of disease. In this study, a comprehensive framework has been proposed to model dengue disease by integrating significant factors using different inputs, such as remote sensing, epidemiological data, and health infrastructure inputs. This framework for Dengue Disease Monitoring (DDM) model provides a conceptual architecture for integrating different data sources, visualization and assessment of disease status, and prediction analysis. The developed model will help forewarn the public health administration about the outbreak for planning interventions to limit the spread of dengue. Further, this forecasting model may be applied to manage the existing public health resources for medical and health infrastructure, also to determine the efficacy of vector surveillance and intervention programmes.