Title: Real-time monitoring and predictive modelling of the impact of human behaviour and vaccine characteristics on COVID-19 vaccination in Scotland
Funder: Economic and Social Research Council

Abstract: While COVID-19 vaccination will likely be transformative, many uncertainties may influence how quickly and comprehensively vaccination will have an impact. Current evidence suggests high levels of protection from the available vaccines, with some evidence that it also reduces transmission. However the evaluation of the evidence is ongoing, with the potential for new variants of concern to change the overall picture. To evaluate this in real time, we shall address here two interlinked factors: the potential for vaccinated individuals to shed and 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, with a signal either indicating potential for transmission or a signal that must be accounted for to reduce the likelihood of false alarms in future situations where wastewater surveillance is being utilised. Using an established 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, clustering of low vaccine uptake, 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, refusal and difficulties of access could result in lower uptake rates in some communities and therefore continued higher levels of infection or risk of outbreaks. We shall embed these scenarios into our simulation models. From this project, 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 amongst vaccine attitudes, accessibility, and regions of low vaccine uptake and refine approaches to surveillance and control.

Lay abstract: While COVID-19 vaccination will likely be transformative, many uncertainties may influence how quickly and comprehensively vaccination will have an impact. Current evidence suggests high levels of protection from the available vaccines, with some evidence that it also reduces transmission. However the evaluation of the evidence is ongoing, with the potential for new variants of concern to change the overall picture. To evaluate this in real time, we shall address here two interlinked factors: the potential for vaccinated individuals to shed and 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, with a signal either indicating potential for transmission or a signal that must be accounted for to reduce the likelihood of false alarms in future situations where wastewater surveillance is being utilised. Using an established 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, clustering of low vaccine uptake, 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, refusal and difficulties of access could result in lower uptake rates in some communities and therefore continued higher levels of infection or risk of outbreaks. We shall embed these scenarios into our simulation models. From this project, 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 amongst vaccine attitudes, accessibility, and regions of low vaccine uptake and refine approaches to surveillance and control.

Research activity codes: 3.4 VACCINES
Health categories: INFECTION