Evaluation of vaccination strategies for the metropolitan area of Madrid via agent-based simulation

Objective: We analyse the impact of different vaccination strategies on the propagation of COVID-19 within the Madrid metropolitan area, starting on 27 December 2020 and ending in Summer of 2021. Materials and methods: The predictions are based on simulation using EpiGraph, an agent-based COVID-19 simulator. We first summarise the different models implemented in the simulator, then provide a comprehensive description of the vaccination model and define different vaccination strategies. The simulator-including the vaccination model-is validated by comparing its results with real data from the metropolitan area of Madrid during the third COVID-19 wave. This work considers different COVID-19 propagation scenarios for a simulated population of about 5 million. Results: The main result shows that the best strategy is to vaccinate first the elderly with the two doses spaced 56 days apart; this approach reduces the final infection rate by an additional 6% and the number of deaths by an additional 3% with respect to vaccinating first the elderly at the interval recommended by the vaccine producer. The reason is the increase in the number of vaccinated individuals at any time during the simulation. Conclusion: The existing level of detail and maturity of EpiGraph allowed us to evaluate complex scenarios and thus use it successfully to help guide the strategy for the COVID-19 vaccination campaign of the Spanish health authorities. ; This work has been partially funded by the agreement between the Community of Madrid and the Carlos III University of Madrid for the funding of research projects on SARS-CoV-2 and COVID-19 disease, project name 'Multi-source and multi-method prediction to support COVID-19 policy decision making', which was supported with REACT-EU funds from the European regional development fund 'a way of making Europe' (2020/00692/003) and the European High-Performance Computing Joint Undertaking (JU) under the ADMIRE project (grant agreement No 956748). We have also used the Spanish Supercomputing Network ...