The spread of information and other stochastic processes in biology: epidemics, misinformation and collective behaviour.

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Non-pharmaceutical interventions, such as mask-wearing and social distancing, are important tools to tackle the spread of emergent pandemic disease. They can be used to slow the progress of an outbreak or suppress it completely if carefully implemented and strictly adhered to. Much of the effectiveness of social distancing strategies rely upon the behaviours of individuals; how conscientiously they follow the advice and how successfully they encourage others to do the same. In the literature, the changes in behaviour arise from the awareness of individuals. This awareness is modelled through the spread of information through contacts. Importantly, there is feedback between changes in behaviour and the progression of the disease itself.Besides that, the spread of awareness has important implications in many complex systems in biology and society. The differences are how the awareness feeds back into other dynamics. In ecology, animals might alert the rest of the community of the presence of invaders or predators - in which case aware individuals would become less vulnerable - or transmit knowledge on food sources' location - increasing the survival rate of those with whom the information has been shared. Furthermore, public opinion regarding a political issue might change as people become more informed about the problem. In recent years, we have seen an increase in the spread of false information designed to influence people's thoughts and views concerning public figures, political issues and health matters - such as climate change and vaccination. Consequently, it is of fundamental interest to develop a means of identifying false information and effective control measures to hinder the transmission of misinformation.My research project concerns the study of information spread processes and their feedback into biological complex systems. So far, using a model for the feedback of awareness and behaviour change on epidemics for a population comprised of trusting and distrusting individuals, we have shown the existence of regions of parameter space in which the disease can be suppressed or merely mitigated. We also studied the stochastic process of information spread in networks and obtained theoretical and numerical results that motivate further work on the topic.To extend the research done so far, we aim to include other information dynamics to make the model more realistic. These might include fading and refreshing mechanisms to account for memory loss and information generation. Due to the complexities of the model, it might be necessary to consider timescale separation frameworks to obtain analytical approximations. In that regard, the work developed by Parsons and Rogers to reduce the manifold dimension for systems with fast-slow dynamics is a prospective tool for initial work. Additionally, we are interested in the spread of misinformation and its effect on society. We are getting in contact with experts on misinformation and human behaviour to develop a realistic model of how people react to and spread (mis-)information. Tim Rogers' expertise will be significant to the analysis of the model on graphs and networks, whilst Kit Yates' experience with stochastic modelling and simulations will be fundamental for the success of the project.