AI.rbo is an AI-powered, Geographic Information System-based, mosquito-borne disease surveillance system equipped with predictive analytics of future outbreaks. This technology was developed to support clinical decision-making in infectious disease management. Its predictive algorithm has been enhanced to cover other arboviral diseases like Zika and Chikungunya.
The dengue dashboard provides a comprehensive set of features to enhance dengue outbreak surveillance and prediction. It includes descriptive dengue data analytics, allowing users to gain insights into the trends and patterns of dengue cases. The geocoded map feature displays the distribution of cases, along with current and past outbreaks, providing a visual representation of the affected areas. Furthermore, the dashboard incorporates a predictive dengue model that leverages Machine Learning Algorithms to forecast future outbreaks, aiding in proactive planning and resource allocation.
The Dengue dashboard uses REDINT (Remote Data Input Interface) to assist in collecting more information such as geocoding, weather, landmarks, geographic and socioeconomic in order to calculate the outbreaks and future outbreaks.
Clients could leverage the forecast output to better strategise their targeted prevention and intervention efforts in potential outbreak locations, resulting in a more efficient cost and resource allocation.
