Raza Ali, Awrejcewicz Jan, Rafiq Muhammad, Mohsin Muhammad
Department of Mathematics, Govt. Maulana Zafar Ali Khan Graduate College Wazirabad, Punjab Higher Education Department (PHED), Lahore 54000, Pakistan.
Department of Automation, Biomechanics and Mechatronics, Lodz University of Technology, 1/15 Stefanowskiego St., 90-924 Lodz, Poland.
Entropy (Basel). 2021 Nov 27;23(12):1588. doi: 10.3390/e23121588.
Nipah virus (NiV) is a zoonotic virus (transmitted from animals to humans), which can also be transmitted through contaminated food or directly between people. According to a World Health Organization (WHO) report, the transmission of Nipah virus infection varies from animals to humans or humans to humans. The case fatality rate is estimated at 40% to 75%. The most infected regions include Cambodia, Ghana, Indonesia, Madagascar, the Philippines, and Thailand. The Nipah virus model is categorized into four parts: susceptible (S), exposed (E), infected (I), and recovered (R). The structural properties such as dynamical consistency, positivity, and boundedness are the considerable requirements of models in these fields. However, existing numerical methods like Euler-Maruyama and Stochastic Runge-Kutta fail to explain the main features of the biological problems. The proposed stochastic non-standard finite difference (NSFD) employs standard and non-standard approaches in the numerical solution of the model, with positivity and boundedness as the characteristic determinants for efficiency and low-cost approximations. While the results from the existing standard stochastic methods converge conditionally or diverge in the long run, the solution by the stochastic NSFD method is stable and convergent over all time steps. The stochastic NSFD is an efficient, cost-effective method that accommodates all the desired feasible properties.
尼帕病毒(NiV)是一种人畜共患病毒(从动物传播给人类),也可通过受污染的食物传播或在人与人之间直接传播。根据世界卫生组织(WHO)的一份报告,尼帕病毒感染的传播方式因动物传人或人传人而异。病死率估计在40%至75%之间。受感染最严重的地区包括柬埔寨、加纳、印度尼西亚、马达加斯加、菲律宾和泰国。尼帕病毒模型分为四个部分:易感者(S)、暴露者(E)、感染者(I)和康复者(R)。动力学一致性、正性和有界性等结构特性是这些领域模型的重要要求。然而,现有的数值方法,如欧拉-丸山方法和随机龙格-库塔方法,无法解释生物学问题的主要特征。所提出的随机非标准有限差分法(NSFD)在模型的数值解中采用了标准和非标准方法,以正性和有界性作为效率和低成本近似的特征决定因素。虽然现有标准随机方法的结果有条件收敛或最终发散,但随机NSFD方法的解在所有时间步上都是稳定且收敛的。随机NSFD是一种高效、经济有效的方法,具有所有所需的可行特性。