Modeling and analysis of dynamical behavior in a fractional-order COVID-19 epidemic model with media coverage: A case study of Malaysia

In this paper, we propose a novel Caputo fractional-order Susceptible-Exposed-Infected-Hospitalized-Recovered (SEIHR) model to analyze the impact of media coverage on early coronavirus disease 2019 (COVID-19) transmission dynamics in Malaysia. We first establish the existence, uniqueness, nonnegativity, and boundedness of solutions, and derive the basic reproduction number R0 via the next-generation matrix. Stability analysis shows that the disease-free equilibrium is globally asymptotically stable when R0<1, while endemic equilibria are locally asymptotically stable when R0>1. These theoretical properties are then validated through numerical simulations. Model parameters are calibrated to outbreak data from Perak, Terengganu, and Johor using nonlinear least squares (Lsq) method, and the system is solved numerically via the predict-evaluate-correct-evaluate (PECE) method of Adams–Bashforth–Moulton (ABM). The fitting results demonstrate that the fractional-order model outperforms the integer-order counterpart across all error metrics. Case studies reveal that insufficient media reporting in Perak accelerated transmission, whereas more comprehensive coverage in Terengganu and Johor suppressed peaks and shortened outbreak durations. Finally, sensitivity analysis highlights the roles of key parameters in determining R0. These findings underscore the value of sustained, high-intensity media campaigns as a cost-effective non-pharmaceutical intervention, offering policymakers targeted strategies to enhance epidemic control and strengthen health system resilience.