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Monitoring the spread of an epidemic in one region allows epidemiologists to predict the transmission and reduce its spread to other regions. AI and ML allows analysis of multi-modality data including demographics, built environment, urban energy systems, geo-spatial, weather pattern, and molecular level data for devising strategies for long term disease risk reduction. With COVID-19 pandemic exposing inefficiencies in the urban systems like health, built-environment and energy systems in India, causing enormous costs to the public fund and compromising welfare, it is pertinent to study the gaps using evidence-based information. MINE intends to bridge the gaps. The project develops an enriched research network that bring together multi-disciplinary researchers, professionals and urban experts for epidemic prediction and risk reduction using Artificial Intelligence (AI) and Machine learning (ML). 

The workshop is aimed at strengthening the public health system through use of appropriate technology and knowledge transfer, for the benefit of most vulnerable. This workshop will build capacities of early career researchers to acquire interdisciplinary perspectives, knowledge and skills needed for epidemics research using state-of-art knowledge systems. It will enable researchers to establish networks within academia, industry and government so as to conduct impactful collaborative studies in addressing challenges of epidemics with specific reference to the promotion of health of socio-economically deprived groups. 

The network will also contribute to the development of a Master’s level course curriculum to build future capacities in the global south.


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Funding Partners

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