COVID-19 Dynamics in Africa Under the Influence of Asymptomatic Cases and Re-infection

International Journal of Mathematical Modelling & Computations

مقاله 4، دوره 12، 1 (WINTER) - شماره پیاپی 45، خرداد 2022، صفحه 37-49   

نوع مقاله: Full Length Article

شناسه دیجیتال (DOI): 10.30495/ijm2c.2022.684827

نویسندگان

Abayomi Samuel Oke^{* 1}؛ Oluwafemi Isaac Bada²؛ Ganiyu Rasaq³؛ Victoria Adodo³؛ Belindar Atieno Juma⁴

¹Department of Mathematics and Actuarial Science,

²Department of Mathematics, University of Benin, Nigeria

³Department of Mathematical Sciences, Adekunle Ajasin University, Nigeria

⁴Department of Mathematical and Actuarial Science, Kenyatta University, Kenya.

چکیده

Since December 2019 that the coronavirus pandemic (COVID-19) has hit the world, with over 13 million cases recorded, only a little above 4.67 percent of the cases have been recorded in the continent of Africa. The percentage of cases in Africa rose significantly from 2 percent in the month of May 2020 to above 4.67 percent by the end of July 15, 2020. This rapid increase in the percentage indicates a need to study the transmission, control strategy, and dynamics of COVID-19 in Africa. In this study, a nonlinear mathematical model to investigate the impact of asymptomatic cases on the transmission dynamics of COVID-19 in Africa is proposed. The model is analyzed, the reproduction number is obtained, the local and the global asymptotic stability of the equilibria were established. We investigate the existence of backward bifurcation and we present the numerical simulations to verify our theoretical results. The study shows that the reproduction number is a decreasing function of detection rate and as the rate of re-infection increases, both the asymptomatic and symptomatic cases rise significantly. The results also indicate that repeated and increase testing to detect people living with the disease will be very effective in containing and reducing the burden of COVID-19 in Africa.

کلیدواژه‌ها

Coronavirus؛ COVID-19؛ Reproduction number؛ Re-infections؛ Asymptomatic case detection