A general computational framework for COVID-19 modelling, with applications to testing varied interventions in education environments

Moore, J. W.; Lau, Z.; Kaouri, K.; Dale, T. C.; Woolley, T. E.

We construct a compartmental individual-based model of Covid-19 infection spread. The model can be used to predict the infection trajectory in general environments with various interventions introduced. Tasked by the Welsh Government, we apply the model to secondary schools and Further and Higher Education environments. Specifically, we consider populations mixing in both a classroom and Halls of Residence. Our particular focus was to question the potential efficacy of Lateral Flow Devices (LFDs) when used in broad-based screens for asymptomatic infection or in "test-to-release" contexts in which individuals who have been exposed to infection are released from isolation. To compare scales of efficacy LFDs are compared to other non-pharmacological interventions. We find that, although tests can be used to reduce disease incidence, investments in personal protective equipment (e.g. masks) and increasing ventilation quality in enclosed environments is more effective in lowering disease prevalence.