Interval-Valued Caputo Fractional Derivative Dynamics Model of Infectious Disease

Mithun Kumar

Abstract: Mathematical modelling on interval valued plays a crucial role in understanding the transmission dynamics and control strategies of infectious diseases. This study presents a comprehensive interval-based mathematical model for an infectious disease, aimed at capturing the uncertainties and variability?s inherent in epidemiological data. Unlike traditional models that use fixed parameters, the proposed model incorporates interval-valued parameters to account for data imprecision and variability in transmission rates, contact rates, and recovery rates. By employing interval analysis, the model provides a range of possible outcomes, offering a healthier framework for predicting disease spread and assessing the impact of various intervention strategies. Simulations are conducted to explore different outbreak scenarios, examining the effects of varying parameter intervals on disease dynamics. The results demonstrate the model's ability to provide more flexible and realistic predictions, which are crucial for decision-making in public health policy. This interval-based approach offers a novel perspective on infectious disease modelling, highlighting the importance of accounting for uncertainty in epidemiological predictions and contributing to more effective disease control strategies.

Keywords: Interval, Fractional Calculus, Caputo Fractional Derivative Infectious Disease Dynamics, Endemic Equilibrium, Disease-Free Equilibrium, Basic Reproduction Number, Stability Analysis

How to Cite?: Mithun Kumar, "Interval-Valued Caputo Fractional Derivative Dynamics Model of Infectious Disease", Volume 14 Issue 6, June 2025, International Journal of Science and Research (IJSR), Pages: 751-756, https://www.ijsr.net/getabstract.php?paperid=SR25610120308, DOI: https://dx.doi.org/10.21275/SR25610120308