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arXiv · 1903.06113

Who and When to Screen: Multi-Round Active Screening for Recurrent Infectious Diseases Under Uncertainty

Han-Ching Ou·Arunesh Sinha·Sze-Chuan Suen·Andrew Perrault·Milind Tambe
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Abstract

Controlling recurrent infectious diseases is a vital yet complicated problem. In this paper, we propose a novel active screening model (ACTS) and algorithms to facilitate active screening for recurrent diseases (no permanent immunity) under infection uncertainty. Our contributions are: (1) A new approach to modeling multi-round network-based screening/contact tracing under uncertainty, which is a common real-life practice in a variety of diseases; (2) Two novel algorithms, Full- and Fast-REMEDY. Full-REMEDY considers the effect of future actions and finds a policy that provides high solution quality, where Fast-REMEDY scales linearly in the size of the network; (3) We evaluate Full- and Fast-REMEDY on several real-world datasets which emulate human contact and find that they control diseases better than the baselines. To the best of our knowledge, this is the first work on multi-round active screening with uncertainty for diseases with no permanent immunity.

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Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Milind Tambe. 2019-03-13. Who and When to Screen: Multi-Round Active Screening for Recurrent Infectious Diseases Under Uncertainty. https://arxiv.org/abs/1903.06113

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