Analyzing and Controlling COVID-19 Using SageMath Toolbox: A case Study in the D.R. Congo

Authors

  • Herman MATONDO MANANGA University of Kinshasa
  • Pokuaa Gambrah Patience Department of Mathematics Sciences, Kumasi Technical University, Kumasi, Ghana
  • Nguemfouo Marcial Department of Mathematics, University of Yaoundé I, Yaoundé, Cameroon
  • Milolo Kanumuambidi Lea-Irène Department of Mathematics, Statistics and Computer Sciences, University of Kinshasa D.R. Congo
  • Kasende Mundeke Peter Department of Mathematics, Statistics and Computer Sciences, University of Kinshasa D.R. Congo
  • Consolant Majegeza Benjamin Department of Observatory of Morbidity phenomena, One Health Institute for Africa, D.R. Congo

DOI:

https://doi.org/10.30871/jaic.v9i4.9828

Keywords:

COVID-19, Stability analysis, Basic Reproduction Number, SageMath (version 9.3)

Abstract

Understanding the dynamics of an epidemic, to control, manage, or eradicate it, requires a wealth of knowledge in biology and mathematics. Computer tools also make significant contributions, thus, enabling us to carry out analyses and find approximate solutions, as well as run simulations to determine trends over time. In this study, we present a compartmental SVEIHAR model for the propagation and prevention of COVID-19. Using the computational and mathematical competencies of SageMath software (version 9.3) we simulate and evaluate the spread of the virus. Equilibria are calculated and adjusted according to the data. Again, the basic reproduction number, stabilities, and parameter sensitivities were studied. Our findings indicate that vaccination and cure rates are the most sensitive parameters, playing a crucial role in the fight against COVID-19. Again, the use of traditional plants, prayer, and meditation significantly decreases the value of the basic reproduction number. We also found that the disease will disappear after a time. Lastly, our study has shown the usefulness of SageMath software (version 9.3) which could be adapted to a variety of mathematical epidemic models.

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Published

2025-08-03

How to Cite

[1]
H. MATONDO MANANGA, P. G. Patience, N. Marcial, M. K. Lea-Irène, K. M. Peter, and C. M. Benjamin, “Analyzing and Controlling COVID-19 Using SageMath Toolbox: A case Study in the D.R. Congo”, JAIC, vol. 9, no. 4, pp. 1103–1114, Aug. 2025.

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