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

The epidemic of COVID-19 has opened a significant interest in developing mathematical models that could incorporate more complexities into the dynamics of disease transmission and control. This study aims to perform a rigorous mathematical analysis on incorporating the effects of age mixing and deprivation decile into an epidemic model of infectious diseases using deterministic models. We consider a mathematical model consisting of nine compartments: susceptible, exposed, asymptomatic, unreported and untested, tested and awaiting test results, positively tested symptomatic and hospitalised, recovered, and dead. The basic reproduction number was estimated using the next generation matrix approach. The analysis shows that the most deprived group in the population demonstrated disproportionately higher number of infections compared with the least deprived groups, and this was consistent across the deprivation spectrum. Our work suggests that in order to effectively control disease, support should be given to those individuals with higher levels of deprivation in order to improve uptake of intervention measures in those groups to reduce the burden of disease.