Mathematical Model of Disease Transmission and Control: Incorporating Age and Deprivation Decile

The COVID-19 pandemic has sparked significant interest in developing mathematical models that capture more of the complexities of the dynamics of disease transmission and control. In this study, we presented a deterministic compartmental model for the transmission of COVID-19. The model has eight compartments: susceptible, exposed, asymptomatic, unreported symptomatic, reported symptomatic, hospitalised, recovered, and dead. Individuals in each compartment are discretised into age and deprivation deciles to study the combined effect of both factors on disease dynamics. We analyse the model and present the results for both the disease-free and endemic equilibrium states. We evaluate the basic reproduction number using a next-generation matrix approach. We also prove the local and global stability of the disease-free and endemic equilibria. Sensitivity indices are calculated both analytically and numerically to identify the parameters that have the greatest influence on R0. Our results suggest that transmission, recovery, treatment, and testing rates need to be closely monitored to reduce the disease burden. Specifically, prompt testing, treatment, and recovery are critical for reducing R0.