Dynamical Analysis and Modeling of COVID-19 and Related Diseases under Comorbidity in Complex Domains

Authors

  • Florence Adongo School of Biological, Physical, Mathematics and Actuarial Sciences, Jaramogi Oginga Odinga University of Science and Technology, Box 210-40601, Bondo-Kenya.
  • Aminer Titus School of Biological, Physical, Mathematics and Actuarial Sciences, Jaramogi Oginga Odinga University of Science and Technology, Box 210-40601, Bondo-Kenya.
  • Benard Okelo School of Biological, Physical, Mathematics and Actuarial Sciences, Jaramogi Oginga Odinga University of Science and Technology, Box 210-40601, Bondo-Kenya.
  • Benson Onyango School of Biological, Physical, Mathematics and Actuarial Sciences, Jaramogi Oginga Odinga University of Science and Technology, Box 210-40601, Bondo-Kenya.

Abstract

The COVID-19 infection is known for causing more challenges to people with underlying health conditions such as cardiovascular, cerebrovascular and diabetes among others. Due to these complications and outbreak of diseases, there is need to formulate a model for comorbidities. Those who have these two or more diseases died at higher rate, four times, compared to those who are suffering from one disease. For diabetes and COVID-19 infected patients, mortality rate is higher, this means the rate of recovery is low and more resources are used towards patients with diabetes and COVID-19 comorbidity. Containment measures for COVID-19 such as quarantine and social distancing may lead to a decline in exercising and lack of a balanced diet, which are key for managing diabetic complications such as vision loss and kidney failure. This note provides a dynamical analysis comparing the rate of recovery and death rate that is high in those co-morbidities compared to those who do not have co-morbidities, all under vaccinations.

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Published

2025-09-29

Issue

Vol. 18 No. 4 (2025): Int. J. Open Problems Compt. Math., Vol. 18, No. 4, December 2025

Section

Articles

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