Epidemic modelling of multiple virus strains: a case study of SARS-CoV-2 B.1.1.7 in Moscow
This addresses the challenge of multi-strain epidemic modeling for public health planning, though it is incremental as it builds on existing SEIR models.
The authors tackled the problem of modeling multiple virus strains in epidemics by developing a modified SEIR model, and as a case study, they predicted a high risk of a new wave of SARS-CoV-2 B.1.1.7 infections in Moscow with up to 35,000 daily infections at peak.
During a long-running pandemic a pathogen can mutate, producing new strains with different epidemiological parameters. Existing approaches to epidemic modelling only consider one virus strain. We have developed a modified SEIR 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.