Lea-Irène, Milolo Kanumuambidi
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Analyzing and Controlling COVID-19 Using SageMath Toolbox: A case Study in the D.R. Congo MATONDO MANANGA, Herman; Patience, Pokuaa Gambrah; Marcial, Nguemfouo; Lea-Irène, Milolo Kanumuambidi; Peter, Kasende Mundeke; Benjamin, Consolant Majegeza
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9828

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.