Real-time monitoring and predictive modelling of the impact of human behaviour and vaccine characteristics on COVID-19 vaccination in Scotland

While COVID-19 vaccination will likely be transformative, however many uncertainties may influence how quickly and comprehensively vaccination will have an impact. We shall address here two interlinked factors: the potential for vaccinated individuals to transmit virus without displaying clinical symptoms, and the rate of vaccination uptake and how it may cluster in communities. We shall work with Public Health Scotland, to exploit real-time monitoring of vaccine uptake, COVID-19 testing and cases, to identify geographical localised impacts on infection rates. Wastewater surveillance data will help to identify possible shedding of vaccinated individuals by comparing detection rates before and after vaccination. Using an agent-based model fitted to cases across Scotland, we shall use these data to make short term forecasts for COVID-19 case numbers to support PHS planning. Long-term projections will consider vaccine-induced and natural immunity, vaccine refusal, logistics, and possible loss of immunity. An online survey will build on the ongoing OPTIMUM study by correlating vaccination attitudes and ease of access to Scottish demography, mapping these geographically via the Scottish index of multiple deprivation (SIMD). We shall use models of 'vaccination games' to consider possible future scenarios where combinations of hesitancy and refusal could cause higher refusal rates and embed these scenarios into our simulation models. We shall have a more refined understanding of COVID-19 epidemiology in Scotland under vaccination, and better predictions of epidemic trajectories to aid in planning, to inform possible stresses on hospitals and ICU, and to target vaccine deployment and information strategies. Our results will more generally inform relationships between vaccine attitudes and uptake and refine approaches to surveillance and control.