TY - JOUR
T1 - On the Modeling of COVID-19 Spread via Fractional Derivative
T2 - A Stochastic Approach
AU - Bonyah, E.
AU - Juga, M. L.
AU - Matsebula, L. M.
AU - Chukwu, C. W.
N1 - Publisher Copyright:
© 2023, Pleiades Publishing, Ltd.
PY - 2023/4/11
Y1 - 2023/4/11
N2 - Abstract: The coronavirus disease (COVID-19) pandemic has caused more harm than expected in developed and developing countries. In this work, a fractional stochastic model of COVID-19 which takes into account the random nature of the spread of disease, is formulated and analyzed. The existence and uniqueness of solutions were established using the fixed-point theory. Two different fractional operators’, namely, power-law and Mittag–Leffler function, numerical schemes in the stochastic form, are utilized to obtain numerical simulations to support the theoretical results. It is observed that the fractional order derivative has effect on the dynamics of the spread of the disease.
AB - Abstract: The coronavirus disease (COVID-19) pandemic has caused more harm than expected in developed and developing countries. In this work, a fractional stochastic model of COVID-19 which takes into account the random nature of the spread of disease, is formulated and analyzed. The existence and uniqueness of solutions were established using the fixed-point theory. Two different fractional operators’, namely, power-law and Mittag–Leffler function, numerical schemes in the stochastic form, are utilized to obtain numerical simulations to support the theoretical results. It is observed that the fractional order derivative has effect on the dynamics of the spread of the disease.
KW - power-law, Mittag–Leffler, existence and uniqueness, stochastic model, COVID-19
UR - https://www.scopus.com/pages/publications/85152590241
UR - https://link.springer.com/article/10.1134/S2070048223020023
U2 - 10.1134/S2070048223020023
DO - 10.1134/S2070048223020023
M3 - Article
AN - SCOPUS:85152590241
SN - 2070-0482
VL - 15
SP - 338
EP - 356
JO - Mathematical Models and Computer Simulations
JF - Mathematical Models and Computer Simulations
IS - 2
ER -