An agent-based epidemics simulation to compare and explain screening and vaccination prioritisation strategies

TL;DR

This paper presents an agent-based epidemic model designed to compare screening and vaccination strategies, emphasizing understanding mechanisms rather than prediction, and providing interactive simulations for experimentation.

Contribution

It introduces a simplified, interactive agent-based model implemented in Netlogo for comparing epidemic control strategies, accessible online for public experimentation.

Findings

Screening by quarantining infectious individuals effectively controls epidemics.

Vaccinating high-risk older populations versus socially active younger populations shows different impacts.

The model facilitates understanding of epidemic dynamics and intervention effects.

Abstract

This paper describes an agent-based model of epidemics dynamics. This model is willingly simplified, as its goal is not to predict the evolution of the epidemics, but to explain the underlying mechanisms in an interactive way. This model allows to compare screening prioritisation strategies, as well as vaccination priority strategies, on a virtual population. The model is implemented in Netlogo in different simulators, published online to let people experiment with them. This paper reports on the model design, implementation, and experimentations. In particular we have compared screening strategies to evaluate the epidemics vs control it by quarantining infectious people; and we have compared vaccinating older people with more risk factors, vs younger people with more social contacts.