Three-Step Implicit Multistep Method for Solving Diabetes Mellitus Model

Abstract

Diabetes mellitus is a growing global health problem, especially in low- and middle-income countries. In this study, we compared the SEII_T model with and without genetic factors to predict the trend of diabetes over a 5-year period using data from the Malaysian National Diabetes Registry 2020. The SEII_T model categorizes the population into susceptible (S), exposed (E), infected (I), and infected with treatment (I_T). Three-step implicit multistep calculations were performed using MATLAB, where the Runge-Kutta fourth order (RK4) method was used for the initial solution, and the Adams-Bashforth and Adams-Moulton methods were used for prediction and correction, respectively. The results calculated using the three-step multistep method showed a similar trend in diabetes prevalence as the results of the reference study were solved using RK4. Comparison with the Malaysian National Diabetes Registry Report 2023 showed that the genetic model performed well in predicting the exposed and infected populations, but both models overestimated the susceptible and treated populations.