TY - JOUR
T1 - Dynamical analysis and numerical assessment of the 2019-nCoV virus transmission with optimal control
AU - Li, Shuo
AU - Khan, Tahir
AU - Al-Mdallal, Qasem M.
AU - Awwad, Fuad A.
AU - Zaman, Gul
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - In this article, we discuss the qualitative analysis and develop an optimal control mechanism to study the dynamics of the novel coronavirus disease (2019-nCoV) transmission using an epidemiological model. With the help of a suitable mathematical model, health officials often can take positive measures to control the infection. To develop the model, we assume two disease transmission sources (humans and reservoirs) keeping in view the characteristics of novel coronavirus transmission. We formulate the model to study the temporal dynamics and determine an optimal control mechanism to minimize the infected population and control the spreading of the novel coronavirus disease propagation. In addition, to understand the significance of each model parameter, we compute the threshold quantity and perform the sensitivity analysis of the basic reproductive number. Based on the temporal dynamics of the model and sensitivity analysis of the threshold parameter, we develop a control mechanism to identify the best control policy for eradicating the disease. We then conduct numerical experiments using large-scale numerical simulations to validate the theoretical findings.
AB - In this article, we discuss the qualitative analysis and develop an optimal control mechanism to study the dynamics of the novel coronavirus disease (2019-nCoV) transmission using an epidemiological model. With the help of a suitable mathematical model, health officials often can take positive measures to control the infection. To develop the model, we assume two disease transmission sources (humans and reservoirs) keeping in view the characteristics of novel coronavirus transmission. We formulate the model to study the temporal dynamics and determine an optimal control mechanism to minimize the infected population and control the spreading of the novel coronavirus disease propagation. In addition, to understand the significance of each model parameter, we compute the threshold quantity and perform the sensitivity analysis of the basic reproductive number. Based on the temporal dynamics of the model and sensitivity analysis of the threshold parameter, we develop a control mechanism to identify the best control policy for eradicating the disease. We then conduct numerical experiments using large-scale numerical simulations to validate the theoretical findings.
KW - Epidemiological model
KW - Numerical simulation
KW - Optimal control theory
KW - Stability analysis
KW - Threshold parameter
UR - http://www.scopus.com/inward/record.url?scp=86000317347&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=86000317347&partnerID=8YFLogxK
U2 - 10.1038/s41598-025-90915-2
DO - 10.1038/s41598-025-90915-2
M3 - Article
C2 - 40038386
AN - SCOPUS:86000317347
SN - 2045-2322
VL - 15
JO - Scientific reports
JF - Scientific reports
IS - 1
M1 - 7587
ER -