Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic

TL;DR

This paper advocates using game theory and social network models to optimize COVID-19 vaccination strategies, addressing challenges like limited resources and vaccine hesitancy to improve pandemic containment.

Contribution

It introduces a game-theoretic framework for modeling vaccination prioritization and uptake under uncertainty, aiding policy decisions for COVID-19 control.

Findings

Game-theoretic models can guide vaccination strategies effectively.

Modeling social networks helps understand vaccine hesitancy impacts.

Framework supports decision-making under imperfect information.

Abstract

Since the recent introduction of several viable vaccines for SARS-CoV-2, vaccination uptake has become the key factor that will determine our success in containing the COVID-19 pandemic. We argue that game theory and social network models should be used to guide decisions pertaining to vaccination programmes for the best possible results. In the months following the introduction of vaccines, their availability and the human resources needed to run the vaccination programmes have been scarce in many countries. Vaccine hesitancy is also being encountered from some sections of the general public. We emphasize that decision-making under uncertainty and imperfect information, and with only conditionally optimal outcomes, is a unique forte of established game-theoretic modelling. Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritization and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic.