Forecasting trends in COVID-19 infections is vital for the global economy, national governments and physical and mental well-being. Using the per capita number of new cases as a proxy for the abundance of the SARS-CoV-2 virus, and the number of deaths as a measure of virulence, the dynamics of the pandemic and the outcomes emerging from it are examined for three locations (England, Italy and New York State). The data are analysed with a new version of a population dynamics model that combines exponential/logistic growth with time-varying carrying capacity, allowing predictions of persistence or extinction of the virus. In agreement with coevolutionary theory, the model suggests a transition from exponential virus growth to low abundance, coupled with reduced virulence, during colonisation of the alternate human host. The structure of the model allows a straightforward assessment of key parameters, which can be contrasted with standard epidemiological models and interpreted with respect to ecological and evolutionary processes and isolation policies.
Collection : COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv