Planning as Inference in Epidemiological Dynamics Models

Wood, Frank and Warrington, Andrew and Naderiparizi, Saeid and Weilbach, Christian and Masrani, Vaden and Harvey, William and Ścibior, Adam and Beronov, Boyan and Grefenstette, John and Campbell, Duncan and Nasseri, S. Ali (2022) Planning as Inference in Epidemiological Dynamics Models. Frontiers in Artificial Intelligence, 4. ISSN 2624-8212

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Abstract

In this work we demonstrate how to automate parts of the infectious disease-control policy-making process via performing inference in existing epidemiological models. The kind of inference tasks undertaken include computing the posterior distribution over controllable, via direct policy-making choices, simulation model parameters that give rise to acceptable disease progression outcomes. Among other things, we illustrate the use of a probabilistic programming language that automates inference in existing simulators. Neither the full capabilities of this tool for automating inference nor its utility for planning is widely disseminated at the current time. Timely gains in understanding about how such simulation-based models and inference automation tools applied in support of policy-making could lead to less economically damaging policy prescriptions, particularly during the current COVID-19 pandemic.

Item Type: Article
Subjects: Institute Archives > Medical Science
Depositing User: Managing Editor
Date Deposited: 01 Feb 2023 06:05
Last Modified: 17 Jul 2024 07:17
URI: http://eprint.subtopublish.com/id/eprint/1021

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