Mathematical Modelling of COVID-19 Incidence in Moscow with an Agent-Based Model

Abstract

Abstract: The outbreak of the COVID-19 pandemic created an emergency situation in the publichealth system in Russia and in the world, which entailed the need to develop tools for predictingthe progression of the pandemic and assessing the potential interventions. In the present daycontext, numerical simulation is actively used to solve such problems. The paper considers aCOVID-19 agent-based megalopolis model. The model was developed in 2020 and was furtherrefined in subsequent years. The capabilities of the model include the description of simultaneousspread of several virus strains and taking into account data on vaccination and populationactivity. The model parameters are calculated using statistical data on the daily number of newlydiagnosed COVID-19 cases. The application of the model to describe the epidemiological situation in Moscowin 2021 and early 2022 is demonstrated. The capability for constructing predictions for 1–3months with allowance for the emergence of new SARS-CoV-2 variants, i.e., the delta and omicronstrains, is shown.