Fractional mathematical modeling on monkeypox using the Laplace-Adomian decomposition method

The monkeypox virus has become a major global health concern due to its rapid spread. Medical intervention and isolation are essential to control the outbreak until an effective treatment is discovered. In this article, we develop a fractional SEIQR model to study the transmission dynamic of the monkeypox virus by including key epidemiological factors and memory effects. The nonlinear model describing the spread of viruses is investigated using the fractional Laplace-Adomian decomposition method (LADM), a powerful analytical technique to address complex infectious disease models. The results are strictly validated by comparing them with those derived from the fractional fourth-order Runge-Kutta (RK4) method. The results demonstrate strong agreement for ζ=0.99, which confirms the reliability of the fractional framework. The error analysis shows that adding more LADM terms increases the accuracy. Positivity and sensitivity analyses confirm the model is biologically valid and show that early detection, isolation, quarantine, and reduced contact strongly affect infection levels. The phase portraits and contour plots provide insight into system behavior and threshold conditions. The study highlights the effectiveness of fractional LADM in describing nonlocal and memory-driven dynamics that cannot be represented in classical models.