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It is well established that people with diabetes are more likely to haveserious complications from COVID-19. Nearly 1 in 5 COVID-19 deaths in theAfrican region are linked to diabetes. World Health Organization (WHO) findsthat 18.3% of COVID-19 deaths in Africa are among people with diabetes. In thispaper, we have formulated and analysed a mathematical comorbidity model ofdiabetes - COVID-19 of the deterministic type. The basic properties of themodel were explored. The basic reproductive number, equilibrium points andstability of the equilibrium points were examined. Sensitivity analysis of themodel was carried on to determine the impact of the model parameters on thebasic reproduction number of the model. The model had a unique endemicequilibrium point, which was stable for R_0>1. Time-dependent optimal controlswere incorporated into the model with the sole aim of determining the beststrategy for curtailing the spread of the disease. COVID-19 cases from March toSeptember 2020 in Ghana were used to validate the model. Results of thenumerical simulation suggest a greater number of individuals deceased when theinfected individual had an underlying condition of diabetes. More so COVID-19is endemic in Ghana with the basic reproduction number found to be R_0=1.4722.The numerical simulation of the optimal control model reveals the lockdowncontrol minimized the rate of decay of the susceptible individuals whereas thevaccination led to a number of susceptible individuals becoming immune toCOVID-19 infections. In all the two preventive control measures were botheffective in curbing the spread of the COVID-19 disease as the number ofCOVID-19 infections was greatly reduced. We conclude that more attention shouldbe paid to COVID-19 patients with an underlying condition of diabetes as theprobability of death in this population was significantly higher.

A Mathematical Model of Transmission Dynamics of SARS-Cov-2 (Covid-19) with an Underlying Condition of Diabetes