@proceedings{Hinsch_M-2023_144499,
title = {Simulating the Evolutionary Response of a Viral Pandemic to Behaviour Change},
author = {Hinsch, M. and Silverman, E. and Robertson, D.},
month = {jul},
year = {2023},
abstract = {The progression of the global SARS-CoV-2 pandemic has been characterised by the emergence of novel ‘variants of concern’ (VOCs), which have altered transmission rates and immune escape capabilities. While numerous studies have used agent-based simulation to model the transmission and spread of the virus within populations, few have examined the impact of altered human behaviour in response to the evolution of the virus. Here we demonstrate a prototype simulation in which a simulated virus continually evolves as the agent population alters its behaviour in response to the perceived threat posed by the virus. Both mutations influencing intra-host and inter-host evolution are simulated. The model shows that evolution can dramatically reduce the effect of individual behaviour and policies on the spread of a pandemic. In particular only a small proportion of non-compliance with policies is sufficient to render countermeasures ineffective and lead to the spread of highly infectious variants.},
journal = {ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference},
publisher = {Massachusetts Institute of Technology},
url = {https://doi.org/10.1162/isal_a_00691},
}
