EXPLORING COVID-19 DISPARITIES IN NIGERIA THROUGH MATHEMATICAL MODELING

Authors

  • Chinedu Obinna Nwankwo Department of Industrial Mathematics and Health Statistics David Umahi Federal University of Health Sciences, Uburu, Ebonyi State, Nigeria

DOI:

https://doi.org/10.5281/zenodo.15435725

Keywords:

COVID-19; NCDC Nigeria; COVID-19 profile; First sensitivity; Initial infected population; Logistic growths; Mathematical modelling; Second sensitivity

Abstract

In this paper, we analyzed the sensitivity of coronavirus disparities in Nigeria using a dynamical mathematical model. Due to the government implementing strict measures such as banning public gatherings, closing places of worship and businesses and encouraging social distancing, we looked closely at the statistics and developed a mathematical model that showed the possible control of this virus and thereby preventing an individual getting infected with the virus. The method of solution involves the first and second sensitivities with a fixed population size that is no further births or migration and the only deaths infections are taken due to baby infections with indication on the initial infected population. The first sensitivity is solved using method separation of variables whose COVID-19 profiles were sketched using ODE45. Obtaining the second sensitivity gives a non-linear ordinary differential equation which is used to determine the behavior of the fixed population size.  If the second sensitivity greater than zero then the COVID19 patients steadily decreases to zero while if the second sensitivity less than zero then the COVID19 patients steadily increases and reach maximum. After this maximum point the number of COVID-19 patients decreases and tends to zero. In either case, the COVID-19 patients tends to extinction. The mathematical model showed that the control of this virus is possible.

 

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Published

2025-05-19

How to Cite

Nwankwo, C. O. (2025). EXPLORING COVID-19 DISPARITIES IN NIGERIA THROUGH MATHEMATICAL MODELING. Contemporary Journal of Statistics and Applied Mathematics, 13(1), 1–12. https://doi.org/10.5281/zenodo.15435725

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