Mathematical modelling of COVID-19 transmission dynamics in a partially comorbid community

A deterministic S,E_m,E_c,I_m,I_c,H,R epidemic model that describes the spreading of SARS-COV-2 within a community with comorbidities is formulated. Size dependent area is incorporated into the model to quantify the effect of social distancing and the results indicate that the risk of community transmission is optimally minimised when the occupancy area is increased. The reproduction number is shown to have a positive relationship with the infection rate, the proportion of individuals with comorbidities and the proportion of susceptible individuals adhering to standard operating procedures. The model exhibits a unique endemic equilibrium whose stability largely depends on the rate of hospitalisation of individuals with underlying health conditions (ω_m) as compared to those without these conditions (ω_c), such that stability is guaranteed if ω_m<ω_c. Furthermore, if individuals with comorbidities effectively report for treatment and hospitalisation at a rate of 0.5 per day, the epidemic curve peaks 3-fold higher among people with comorbidities. The infection peaks are delayed if the area occupied by community is increased. In conclusion, we observed that community infections increase significantly with decreasing detection rates for both individuals with or without comorbidities.