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At the end of 2020, policy responses to the SARS-CoV-2 outbreak have beenshaken by the emergence of virus variants. The emergence of these morecontagious, more severe, or even vaccine-resistant strains have challengedworldwide policy interventions. Anticipating the emergence of these mutationsto plan ahead adequate policies, and understanding how human behaviors mayaffect the evolution of viruses by coevolution, are key challenges. In thisarticle, we propose coevolution with genetic algorithms (GAs) as a credibleapproach to model this relationship, highlighting its implications, potentialand challenges. We present a dual GA model in which both viruses aiming forsurvival and policy measures aiming at minimising infection rates in thepopulation, competitively evolve. Simulation runs reproduce the emergence ofmore contagious variants, and identifies the evolution of policy responses as adeterminant cause of this phenomenon. This coevolution opens new possibilitiesto visualise the impact of governments interventions not only on outbreakdynamics, but also on its evolution, to improve the efficacy of policies.

Emergence of more contagious COVID-19 variants from the coevolution of viruses and policy interventions