Project Description
COVID-19 is the greatest public health crisis that the world has experienced in the last century. Tackling it requires the collective will of experts from a variety of disciplines. While a lot of efforts have been made by AI researchers in developing agent-based models for simulating the transmission of COVID-19, we believe that AI's enormous potential can (and should) be leveraged to design decision support systems (e.g., in the allocation of limited healthcare resources such as testing kits) which can assist epidemiologists and policy makers in their fight against this pandemic. In particular, COVID-19 testing kits are extremely limited especially in developing countries. Therefore, it is very important to utilize these limited testing resources in the most effective manner. In this project, we research adaptive testing policies to optimally mitigate the COVID-19 epidemic in low-resource developing countries like Panama. Our work is informed through multiple discussions with epidemiologists.
Publications
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Yu Liang, and Amulya Yadav. Let the DOCTOR Decide Whom to Test: Adaptive Testing Strategies to Tackle the COVID-19 Pandemic. In Proc. 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 790–798, 2021.
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Yu Liang, Amulya Yadav. Efficient COVID-19 Testing Using POMDPs. In 3rd International Workshop on Artificial Intelligence for Social Good (AI4SG), 2020.