G. Ilangarathna, H. Weligampola, Y. Ranasinghe, E. Attygalla, R. Godaliyaddha, V. Herath, P. Ekanayake, S.Y. Ekanayake, M. Pinnawela, S. Dharmaratne, G. Tilakaratne, J. Ekanayake
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Artificial Intelligence framework for threat assessment and containment for COVID-19 and future epidemics while mitigating the socioeconomic impact to women, children, and underprivileged groups
With the emergency situation that arises with COVID-19, the intense containment strategies adopted by many countries had little or no consideration towards socio-economic ramifications or the impact on women, children, socioeconomically underprivileged groups. The existence of many adverse impacts raises questions on the approaches taken and demands proper analysis, scrutiny and review of the policies. Therefore, a framework was developed using the artificial intelligence (Al) techniques to detect, model, and predict the behaviour of the COVID-19 pandemic containment strategies, understanding the socio-economic impact of these strategies on identified diverse vulnerable groups, and the development of AI-based solutions, to predict and manage a future spread of COVID or similar infectious disease outbreaks while mitigating the social and economic toil. Based on generated behaviour and movements, Al tools were developed to conduct contact tracing and socio-economic impact mitigation actions in a more informed, socially conscious and responsible manner in the case of the next wave of COVID-19 infections or a different future infectious disease. © 2022, National Science Foundation. All rights reserved.