On the efficiency of decentralized epidemic management and application to Covid-19

TL;DR

This paper models decentralized epidemic control as a game, analyzing how local decision-making impacts overall efficiency during pandemics like Covid-19, and identifies when decentralization is acceptable.

Contribution

It introduces a game-theoretic framework for assessing efficiency loss in decentralized epidemic management and provides conditions for equilibrium analysis.

Findings

Decentralization can lead to significant efficiency loss in epidemic control.

Numerical results quantify the impact of decentralization using PoA and PoC metrics.

The study identifies scenarios where decentralization maintains acceptable efficiency levels.

Abstract

In this paper, we introduce a game that allows one to assess the potential loss of efficiency induced by a decentralized control or local management of a global epidemic. Each player typically represents a region or a country which is assumed to choose its control action to implement a tradeoff between socioeconomic aspects and the health aspect. We conduct the Nash equilibrium analysis of this game. Since the analysis is not trivial in general, sufficient conditions for existence and uniqueness are provided. Then we quantify through numerical results the loss induced by decentralization, measured in terms of price of anarchy (PoA) and price of connectedness (PoC). These results allow one to clearly identify scenarios where decentralization is acceptable or not regarding to the retained global efficiency measures.