Predicting future spatial patterns in COVID-19 booster vaccine uptake

This research has not been peer-reviewed. It is a preliminary report that should not be regarded as conclusive, guide clinical practice or health-related behaviour, or be reported in news media as established information.

Vaccination is a critical tool for controlling infectious diseases, with its use to protect against COVID-19 being a prime example. Where a disease is highly transmissible, even a small proportion of unvaccinated individuals can have substantial implications for disease burdens and compromise efforts for control. As socio-demographic factors such as deprivation and ethnicity have been shown to influence uptake rates, identifying how vaccine uptake varies with socio-demographic indicators is a critical step for reducing vaccine hesitancy and issues of access, and identifying plausible future uptake patterns. Here, we analyse the numbers of COVID-19 vaccinations subdivided by age, gender, date, dose and geographical location. We use publicly available socio-demographic data, and use random forest models to capture patterns of uptake at high spatial resolution, with systematic variation restricted to fine spatial scale (~1km in urban areas). We show that uptake of first vaccine booster doses in Scotland can be used to predict with high precision the distribution of second booster doses across deprivation deciles, age and gender despite the substantially lower uptake of second boosters compared to first. This analysis shows that while age and gender have the greatest impact on the model fit, there is a substantial influence of several deprivation factors and the proportion of BAME residents. The high correlation amongst these factors also suggests that, should vaccine uptake decrease, the impact of deprivation is likely to increase, furthering the disproportionate impact of COVID-19 on individuals living in highly deprived areas. As our analysis is based solely on publicly available socio-demographic data and readily recorded vaccination uptake figures, it would be easily adaptable to analysing vaccination uptake data from countries where data recording is similar, and for aiding vaccination campaigns against other infectious diseases.

Author list



  1. Roslin Institute, University of Edinburgh
  2. School of Physics and Astronomy, University of Edinburgh 
  3. Institute for Social Marketing and Health, University of Stirling


A.J. Wood1, A.M. MacKintosh3, M. Stead3, and R.R. Kao∗1,2

Novel Coronavirus SARS-CoV-2