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.

In swarm robotics simple identical robots have to be made to coordinate in such a way that they can perform a task. Multi-cellular organisms similarly during development have to be able to create spatial patterns using many identical components (cells) without being able to draw on an absolute frame of reference. Finding and understanding existing solutions to the latter problem might therefore be a promising route to solving the former. Cell-surface mechanics, i.e. cell movement based on surface tension or adhesion is a mechanism that is known to be involved in many basic processes of morphogenesis. We implemented a simplified model of cell surface mechanics on the kilobot, a small robot with limited computational power and without any spatial orientation capabilities. Using only distance measurements to their neighbours kilobots were able to perform various morphogenetic tasks.