# Game theoretic modelling of infectious disease dynamics and intervention methods: a mini-review

## TL;DR

This mini-review examines how game theory models individual decision-making during epidemics, highlighting recent trends towards network-based models with imitation strategies and their implications for intervention strategies.

## Contribution

It classifies existing literature based on population modeling, game frequency, and strategy adoption, and identifies emerging trends in the field.

## Key findings

- Early studies used compartmental models with self-evaluation strategies.
- Recent studies favor network-based models with imitation strategies.
- Game theory remains effective for modeling intervention decisions.

## Abstract

We review research papers which use game theory to model the decision making of individuals during an epidemic, attempting to classify the literature and identify the emerging trends in this field. We show that the literature can be classified based on (i) type of population modelling (compartmental or network-based), (ii) frequency of the game (non-iterative or iterative), and (iii) type of strategy adoption (self-evaluation or imitation). We highlight that the choice of model depends on many factors such as the type of immunity the disease confers, the type of immunity the vaccine confers, and size of population and level of mixing therein. We show that while early studies used compartmental modelling with self-evaluation based strategy adoption, the recent trend is to use network-based modelling with imitation-based strategy adoption. Our review indicates that game theory continues to be an effective tool to model intervention (vaccination or social distancing) decision-making by individuals.