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COVID-19 and underlying health conditions: a modeling investigation. (English) Zbl 1471.92362

Summary: We propose a mathematical model based on a system of differential equations, which incorporates the impact of the chronic health conditions of the host population, to investigate the transmission dynamics of COVID-19. The model divides the total population into two groups, depending on whether they have underlying conditions, and describes the disease transmission both within and between the groups. As an application of this model, we perform a case study for Hamilton County, the fourth-most populous county in the US state of Tennessee and a region with high prevalence of chronic conditions. Our data fitting and simulation results quantify the high risk of COVID-19 for the population group with underlying health conditions. The findings suggest that weakening the disease transmission route between the exposed and susceptible individuals, including the reduction of the between-group contact, would be an effective approach to protect the most vulnerable people in this population group.

MSC:

92D30 Epidemiology
34C60 Qualitative investigation and simulation of ordinary differential equation models
35Q92 PDEs in connection with biology, chemistry and other natural sciences

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