The prime objective of the current study is to propose a novel mathematical framework under the fractional-order derivative, which describes the complex within-host behavior of SARS-CoV-2 by taking into account the effects of memory and carrier. To do this, we formulate a mathematical model of SARS-CoV-2 under the Caputo fractional-order derivative. We derived the conditions for the existence of equilibria of the model and computed the basic reproduction number ${\mathcal{R}}_0$. We used mathematical analysis to establish the proposed model’s local and global stability results. Some numerical resolutions of our theoretical results are presented. The main result of this study is that as the fractional derivative order increases, the approach of the solution to the equilibrium points becomes faster. It is also observed that the value of ${\mathcal{R}}_0$ increases as the value of $\beta$ and ${\pi }_v$ increases.

This research investigates the impact of second-order slip conditions, Stefan flow, and convective boundary constraints on the stagnation-point flow of couple stress nanofluids over a solid sphere. The nanofluid density is expressed as a nonlinear function of temperature, while the diffusion-thermo effect, chemical reaction, and thermal radiation are incorporated through linear models. The governing equations are transformed using appropriate non-similar transformations and solved numerically via the finite difference method (FDM). Key physical parameters, including the heat transfer rate, are analyzed in relation to the Dufour number, velocity, and slip parameters using an artificial neural network (ANN) framework. Furthermore, response surface methodology (RSM) is employed to optimize skin friction, heat transfer, and mass transfer by considering the influence of radiation, thermal slip, and chemical reaction rate. Results indicate that velocity slip enhances flow behavior while reducing temperature and concentration distributions. Additionally, an increase in the Dufour number leads to higher temperature profiles, ultimately lowering the overall heat transfer rate. The ANN-based predictive model exhibits high accuracy with minimal errors, offering a robust tool for analyzing and optimizing the thermal and transport characteristics of couple stress nanofluids.

Fractional calculus generalizes well-known differentiation and integration to noninteger orders, allowing a more accurate framework for modeling complex dynamical behaviors. The application of fractional-order systems is quite wide in engineering, biology, and physics because they inherently capture the memory effects and long-range dependencies. Out of these, fractional jerk chaotic systems have gained attention regarding their applications in secure communication, signal processing, and control systems. This work develops a comparative analysis of a fractional jerk system that includes constant- and variable-order derivatives to contribute to chaos–stability analysis. Additionally, this study uncovers novel chaotic behaviors, further expanding our understanding of complex dynamical systems. The results yield new insights into using variable-order dynamics to enable chaotic systems to better adapt to real applications.