Dynamic analysis and optimal control of COVID-19 with comorbidity: A modeling study of Indonesia

Muhammad Abdurrahman Rois, Fatmawati, Cicik Alfiniyah, Chidozie W. Chukwu

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Comorbidity is defined as the coexistence of two or more diseases in a person at the same time. The mathematical analysis of the COVID-19 model with comorbidities presented includes model validation of cumulative cases infected with COVID-19 from 1 November 2020 to 19 May 2021 in Indonesia, followed by positivity and boundedness solutions, equilibrium point, basic reproduction number (R0), and stability of the equilibrium point. A sensitivity analysis was carried out to determine how the parameters affect the spread. Disease-free equilibrium points are asymptotically stable locally and globally if R0 < 1 and endemic equilibrium points exist, locally and globally asymptotically stable if R0 > 1. In addition, this disease is endemic in Indonesia, with R0 = 1.47. Furthermore, two optimal controls, namely public education and increased medical care, are included in the model to determine the best strategy to reduce the spread of the disease. Overall, the two control measures were equally effective in suppressing the spread of the disease as the number of COVID-19 infections was significantly reduced. Thus, it was concluded that more attention should be paid to patients with COVID-19 with underlying comorbid conditions because the probability of being infected with COVID-19 is higher and mortality in this population is much higher. Finally, the combined control strategy is an optimal strategy that provides an effective guarantee to protect the public from the COVID-19 infection based on numerical simulations and cost evaluations.

Original languageEnglish
Article number1096141
JournalFrontiers in Applied Mathematics and Statistics
Publication statusPublished - 6 Jan 2023


  • COVID-19
  • comorbidity
  • cost evaluation
  • optimal control
  • sensitivity analysis
  • stability


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