TY  - EJOU
AU  - Shafique, Umar 
AU  - Raza, Ali 
AU  - Baleanu, Dumitru 
AU  - Nasir, Khadija 
AU  - Naveed, Muhammad 
AU  - Siddique, Abu Bakar 
AU  - Fadhal, Emad 

TI  - Computational Modeling of Streptococcus Suis Dynamics via Stochastic Delay Differential Equations
T2  - Computer Modeling in Engineering \& Sciences

PY  - 2025
VL  - 143
IS  - 1
SN  - 1526-1506

AB  - Streptococcus suis (S. suis) is a major disease impacting pig farming globally. It can also be transferred to humans by eating raw pork. A comprehensive study was recently carried out to determine the indices through multiple geographic regions in China. Methods: The well-posed theorems were employed to conduct a thorough analysis of the model’s feasible features, including positivity, boundedness equilibria, reproduction number, and parameter sensitivity. Stochastic Euler, Runge Kutta, and Euler Maruyama are some of the numerical techniques used to replicate the behavior of the streptococcus suis infection in the pig population. However, the dynamic qualities of the suggested model cannot be restored using these techniques. Results: For the stochastic delay differential equations of the model, the non-standard finite difference approach in the sense of stochasticity is developed to avoid several problems such as negativity, unboundedness, inconsistency, and instability of the findings. Results from traditional stochastic methods either converge conditionally or diverge over time. The stochastic non-negative step size convergence nonstandard finite difference (NSFD) method unconditionally converges to the model’s true states. Conclusions: This study improves our understanding of the dynamics of streptococcus suis infection using versions of stochastic with delay approaches and opens up new avenues for the study of cognitive processes and neuronal analysis. The plotted interaction behaviour and new solution comparison profiles.
KW  - Streptococcus suis disease model; stochastic delay differential equations (SDDEs); existence and uniqueness; Lyapunov function; stability results; reproduction number; computational methods

DO  - 10.32604/cmes.2025.061635