AI Framework for Threat Assessment and Containment of Pandemics

Many of the measures taken by governments worldwide to combat COVID-19 were no doubt done in good faith while considering the ‘best data and information available at the time’ and aimed to reduce the spread of the coronavirus disease (i.e. “flatten the curve”). In the face of the sudden rise in the number of cases and deaths due to COVID-19, many countries adopted diverse containment strategies ranging from open (no containment), social-distancing, restricted, lockdown, to complete shutdown.

The intense containment strategies adopted by many countries had little or no consideration of the socio-economic ramifications on women, children and socio-economically underprivileged groups. The existence of many adverse impacts raises questions on the measures taken and demands proper scrutiny and review of public policies.

This proposal was developed with three main objectives: (1) develop and use artificial intelligence (AI) techniques to detect, model and predict the behaviour of ‘identified diverse groups’ under COVID-19 pandemic containment strategies; (2) understand the impact of these strategies initiated in the Global South with special emphasis on Sri Lanka and Malaysia; and (3) develop AI-based solutions to predict and manage a future spread of COVID or similar infectious disease outbreaks.

Based on generated behaviour and movements, it proposes to develop AIs to conduct contact-tracing and socio-economic impact mitigation action in a more informed, socially-conscious and responsible manner in case of the next wave of COVID-19 infections or a crisis arising from an infectious disease of similar magnitude in the future. To face this type of future crisis, this study proposes to transform AI-informed policy into a set of recommendations that policymakers and medical practitioners can access without any barriers.

Research team

Dr. Ganga Tilakaratna
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Funding

IDRC

Published Year

TBA