Key result
A stochastic nonstandard finite difference method was developed to model poliovirus transmission dynamics, preserving dynamical features like positivity, boundedness, and dynamical consistency.
Why the study?
Poliovirus continues to affect developing nations, and existing computational methods fail to capture the actual dynamical behavior of the disease such as positivity and boundedness.
A novel stochastic nonstandard finite difference method for modeling poliovirus epidemics demonstrates improved stability and dynamical consistency compared to traditional computational methods.
Most developing countries such as Afghanistan, Pakistan, India, Bangladesh, and many more are still fighting against poliovirus. According to the World Health Organization, approximately eighteen million people have been infected with poliovirus in the last two decades. In Asia, still, some countries are suffering from the virus. The stochastic behavior of the poliovirus through the transition probabilities and non-parametric perturbation with fundamental properties are studied. Some basic properties of the deterministic model are studied, equilibria, local stability around the stead states, and reproduction number. Euler Maruyama, stochastic Euler, and stochastic Runge-Kutta study the behavior of complex stochastic differential equations. The main target of this study is to develop a nonstandard computational method that restores dynamical features like positivity, boundedness, and dynamical consistency. Unfortunately, the existing methods failed to fix the actual behavior of the disease. The comparison of the proposed approach with existing methods is investigated.
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Raza et al. (2022) studied Poliovirus. Stochastic nonstandard finite difference method was evaluated. A stochastic nonstandard finite difference method was developed to model poliovirus transmission dynamics, preserving dynamical features like positivity, boundedness, and dynamical consistency.
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