Modelling and analysis of infectious diseases considering vaccination, mutation and quarantine strategies

From an experimental point of view, it is difficult to investigate the propagation mechanism of infectious disease and predict its trend. However, applying a nonlinear model offers a more straightforward and effective approach for analyzing transmission characteristics of infectious diseases. This paper proposes an SLVEIMQR dynamic model by dividing the population into susceptible (S), low-risk (L), vaccinated (V), exposed (E), infected (I), mutant (M), quarantined (Q) and recovered (R). The basic reproduction number and the equilibrium of the proposed model are computed, and the local asymptotic stability of the disease-free equilibrium is proved. Furthermore, the transcritical bifurcation at equilibrium and the sensitivity of key parameters are analyzed. To estimate the model parameters and predict the trend of infectious disease, the least squares method is applied by using epidemic data from different phases in Italy. The results show that the average relative errors of the model in the two prediction stages are 1.72% and 3.66%, respectively.