Bangalore's AI dengue monitoring platform
Categories: Action Line 1: Surveillance and monitoring, Action Line 3: Innovation and production, Integrated risks, monitoring, early warning, and GHG emissions tracking, Vector distribution and ecology
Country: India
Organizations: The Rockefeller Foundation, Collective Service, Artificial Intelligence and Robotics Technology Park (ARTPARK)
The intervention
In Bangalore, dengue incidence peaks during the monsoon season, when stagnant water, humidity, and higher temperatures create ideal mosquito breeding conditions. Climate change has intensified these outbreaks, with Karnataka recording its highest number of cases in a decade in 2023. In response, the Artificial Intelligence and Robotics Technology Park (ARTPARK) developed an AI-driven Dengue Platform that integrates meteorological, vector surveillance, socioeconomic, and urban land-use data. This platform provides risk classification forecasts up to four weeks in advance, enabling health authorities to anticipate outbreaks, allocate resources efficiently, and coordinate prevention and control activities across Bangalore’s densely populated districts.
Success factors
The platform’s success lies in its accessibility, integration, and adoption across scales. Designed for use by community health workers through a simple mobile app, it supports over 1,000 frontline users conducting more than 10,000 site surveys daily during peak season. The tool has facilitated the identification of over 80,000 mosquito breeding sites and streamlined dengue management for a population exceeding seven million. Its nowcasting service - used by roughly half of state-level practitioners - has strengthened proactive surveillance and guided rapid response. The system’s effectiveness has led to proposals for integration into both municipal and national disease monitoring platforms.
Recommendations
To replicate this model, countries should prioritise developing integrated data systems that combine meteorological, environmental, and health information to generate accurate, location-specific forecasts. Ensuring data integrity through partnerships with verified and trusted sources is essential for maintaining reliability.
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