Important message: Due to recent site outage we are still restoring full functionality to Authorea powered sites. Please bear with us until full functionality is restored

loading page

Fractional modelling and optimal control strategies for mutated COVID-19 pandemic
  • +2
  • Weiyuan Ma,
  • Nuri Ma,
  • Changping Dai,
  • YangQuan Chen,
  • Xinwei Wang
Weiyuan Ma
Northwest Minzu University

Corresponding Author:[email protected]

Author Profile
Nuri Ma
Northwest Minzu University
Author Profile
Changping Dai
Northwest Minzu University
Author Profile
YangQuan Chen
University of California Merced
Author Profile
Xinwei Wang
Dalian University of Technology
Author Profile

Abstract

As the COVID-19 continues to mutate, the number of infected people is increasing dramatically, and the vaccine is not enough to fight the mutated strain. In this paper, a SEIR-type fractional model with reinfection and vaccine inefficacy is proposed, which can successfully capture the mutated COVID-19 pandemic. The existence, uniqueness, boundedness and nonnegativeness of the fractional model are derived. Based on the basic reproduction number R 0 , locally stability and globally stability are analyzed. The sensitivity analysis evaluate the influence of each parameter on the R 0 and rank key epidemiological parameters. Finally, the necessary conditions for implementing fractional optimal control are obtained by Pontryagin's Maximum Principle, and the corresponding optimal solutions are derived for mitigation COVID-19 transmission. The numerical results show that humans will coexist with COVID-19 for a long time under the current control strategy. Furthermore, it is particularly important to develop new vaccines with higher protection rates.
17 Oct 2022Submitted to Mathematical Methods in the Applied Sciences
18 Oct 2022Submission Checks Completed
18 Oct 2022Assigned to Editor
25 Oct 2022Review(s) Completed, Editorial Evaluation Pending
26 Oct 2022Reviewer(s) Assigned
08 Mar 2023Editorial Decision: Revise Major
20 Mar 20231st Revision Received
22 Mar 2023Submission Checks Completed
22 Mar 2023Assigned to Editor
22 Mar 2023Review(s) Completed, Editorial Evaluation Pending
22 Mar 2023Reviewer(s) Assigned
11 Apr 2023Editorial Decision: Accept