随机 CTMC 模型比确定性模型对理解无症状携带者淋巴丝虫病动态的意义

IF 1.2 Q2 MATHEMATICS, APPLIED
M. A. Stephano, J. I. Irunde, Maranya M. Mayengo, Dmitry Kuznetsov
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引用次数: 0

摘要

淋巴丝虫病是对人体免疫力造成慢性和不可逆损害的主要原因。本文介绍了有关淋巴丝虫病动态的确定性和连续时间马尔可夫链(CTMC)随机模型。为了考虑动态过程中的随机性和不确定性,CTMC 模型是基于确定性模型的可能事件建立的。确定性模型的输出结果表明,当次要临界感染数低于 1 时,疾病灭绝是可行的,而当次要临界感染数低于 1 时,疾病持续存在是可能的。此外,还发现了无症状携带者的重要作用。结果表明,当感染来自无症状、急性感染或传染性蚊子时,持续存在的可能性更大。因此,CTMC 随机模型在捕捉不同尺度的变异性、随机性、相关概率和有效性方面至关重要,而过于简单化和固有的不可预测性可能在确定性模型中无法体现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Significance of Stochastic CTMC Over Deterministic Model in Understanding the Dynamics of Lymphatic Filariasis With Asymptomatic Carriers
Lymphatic filariasis is a leading cause of chronic and irreversible damage to human immunity. This paper presents deterministic and continuous-time Markov chain (CTMC) stochastic models regarding lymphatic filariasis dynamics. To account for randomness and uncertainties in dynamics, the CTMC model was formulated based on deterministic model possible events. A deterministic model’s outputs suggest that disease extinction is feasible when the secondary threshold infection number is below one, while persistence becomes likely when the opposite holds true. Furthermore, the significant contribution of asymptomatic carriers was identified. Results indicate that persistence is more likely to occur when the infection results from asymptomatic, acutely infected, or infectious mosquitoes. Consequently, the CTMC stochastic model is essential in capturing variabilities, randomness, associated probabilities, and validity across different scales, whereas oversimplification and unpredictability of inherent may not be featured in a deterministic model.
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来源期刊
Journal of Applied Mathematics
Journal of Applied Mathematics MATHEMATICS, APPLIED-
CiteScore
2.70
自引率
0.00%
发文量
58
审稿时长
3.2 months
期刊介绍: Journal of Applied Mathematics is a refereed journal devoted to the publication of original research papers and review articles in all areas of applied, computational, and industrial mathematics.
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