Dynamic Epidemic Control via Sequential Resource Allocation

TL;DR

This paper introduces a novel multi-round dynamic control framework for epidemic diffusion, using sequential resource allocation with limited network access, and demonstrates its effectiveness through SIS epidemic simulations.

Contribution

It presents the first sequential decision-based approach to dynamic epidemic control with restricted network information and access.

Findings

Multi-round approach outperforms traditional strategies in simulations.

Sequential decision process offers new insights into resource allocation.

Framework applicable to real-world epidemic management.

Abstract

In the Dynamic Resource Allocation (DRA) problem, an administrator has to allocate a limited amount of resources to the nodes of a network in order to reduce a diffusion process (DP) (e.g. an epidemic). In this paper we propose a multi-round dynamic control framework, which we realize through two derived models: the Restricted and the Sequential DRA (RDRA, SDRA), that allows for restricted information and access to the entire network, contrary to standard full-information and full-access DRA models. At each intervention round, the administrator has only access -- simultaneous for the former, sequential for the latter -- to a fraction of the network nodes. This sequential aspect in the decision process offers a completely new perspective to the dynamic DP control, making this work the first to cast the dynamic control problem as a series of sequential selection problems. Through in-depth SIS epidemic simulations we compare the performance of our multi-round approach with other resource allocation strategies and several sequential selection algorithms on both generated, and real-data networks. The results provide evidence about the efficiency and applicability of the proposed framework for real-life problems.