Epidemic Modeling of Multiple Virus Strains: A Case Study of SARS-CoV-2 B.1.1.7 In Moscow

Abstract

During a long-running pandemic a pathogen can mutate, producing new strains with different epidemiological parameters. Existing approaches to epidemic modeling only consider one virus strain. We have developed a modified Susceptible-Exposed-Infected-Recovered model to simulate multiple virus strains within the same population. As a case study, we investigate the potential effects of SARS-CoV-2 strain B.1.1.7 on the city of Moscow. Our analysis indicates a high risk of a new wave of infections in September-October 2021 with up to 35 000 daily infections at peak. We open-source our code and data.