COVID-19 Dynamics: A Heterogeneous Model - Gerasimov, Andrey; Lebedev, Georgy; Lebedev, Mikhail; Semenycheva, Irina (Frontiers in Public Health, 2021)
The mathematical model reported here describes the dynamics of the ongoing coronavirus disease 2019 (COVID-19) epidemic, which is different in many aspects from the previous epidemic of severe acute respiratory syndrome (SARS). We developed this model when COVID-19 epidemic was at its early phase. We reasoned that, with our model, the effects could be assessed of different measures for infection control. Unlike the homogeneous models, our model accounts for human population heterogeneity, where subpopulations (e.g., age groups) have different infection risks. The heterogeneous model estimates several characteristics of the epidemic more accurately compared to the homogeneous models. According to our analysis, the total number of infections and their peak number are lower compared to the assessment with the homogeneous models. Furthermore, the early-stage infection increase is little changed when population heterogeneity is considered, whereas the late-stage infection decrease slows. The model predicts that the anti-epidemic measures, like the ones undertaken in China and the rest of the world, decrease the basic reproductive number but do not result in the development of a sufficient collective immunity, which poses a risk of the epidemic second wave. More recent developments confirmed our conclusion that the epidemic has a high likelihood to restart after the quarantine measures are lifted.