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March 25, 2026Boundary Value Problems6 citationsOpen Access

Fractional optimal control and numerical analysis of a Zika virus transmission model

GBG. M. BahaaAQA. H. Qamlo

Key Points

  • The aim is to develop a fractional-order model for Zika virus transmission that incorporates memory effects.
  • Developed a fractional-order optimal control model using Caputo fractional derivatives.
  • Incorporated time-dependent control measures including prevention, treatment, and vector control.
  • Established qualitative properties of the system and derived a threshold parameter using next-generation matrix approach.
  • Formulated an optimal control problem and derived optimality conditions via the fractional Pontryagin Maximum Principle.
  • Performed numerical simulations with a forward–backward sweep algorithm.
  • Fractional-order dynamics significantly influence Zika epidemic behavior.
  • The combined control strategy was found to be most effective in reducing infections in both human and mosquito populations.
  • Memory effects are crucial for more accurate predictions and control of Zika virus outbreaks.

Abstract

Abstract Zika virus is a mosquito-borne infectious disease that poses a significant public health threat in many regions of the world. Mathematical modeling plays a crucial role in understanding its transmission dynamics and in designing effective control strategies. In this paper, a fractional-order optimal control model describing the transmission of Zika virus between human and mosquito populations is proposed and analyzed. The model is formulated using Caputo fractional derivatives in order to capture memory and hereditary effects that are often neglected in classical integer-order models. Three time-dependent control measures, representing prevention, treatment of infected individuals, and insecticide-based vector control, are incorporated into the model. Fundamental qualitative properties of the system, including positivity and boundedness of solutions, are established. A threshold parameter governing disease persistence is derived using the next-generation matrix approach. An optimal control problem is then formulated, and the necessary optimality conditions are obtained via the fractional Pontryagin Maximum Principle. Numerical simulations, implemented using a forward–backward sweep algorithm combined with a fractional predictor–corrector scheme, illustrate the effects of fractional order and control strategies on the disease dynamics. The results demonstrate that fractional-order dynamics significantly influence epidemic behavior and that the combined control strategy is the most effective in reducing both human and mosquito infections. These findings highlight the importance of memory effects and coordinated interventions in controlling Zika virus outbreaks.

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Cite This Study

Bahaa et al. (2026) studied this question.

synapsesocial.com/papers/69c37afeb34aaaeb1a67d057https://doi.org/10.1186/s13661-026-02236-6
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