带延迟的乙型肝炎病毒动态模型

B. Chen-Charpentier
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摘要

乙型肝炎是由人类乙型肝炎病毒(HBV)引起的一种肝病。数学模型有助于进一步了解相关过程,并帮助做出预测。基本繁殖数 R0 是预测疾病是否会慢性化的指标。这是数学模型所能提供的最重要的信息。宿主内病毒过程涉及延迟。我们研究了两种无延迟和有延迟的宿主内乙型肝炎病毒感染模型。其中一个是标准模型,另一个是考虑了额外过程和两个延迟的新模型。我们分析了基本繁殖数量和替代阈值指数。R0 和替代指数的值随模型的不同而变化。所有这些指数都能预测感染是否会持续,但在感染开始时,它们给出的感染增长率并不相同。因此,模型的选择对于确定感染是否为慢性感染以及感染初期的增长速度非常重要。我们对这些指数进行分析,看看如何降低它们的值。我们研究了添加延迟的效果,以及阈值指数如何取决于延迟的加入方式。我们通过研究无病均衡的局部渐近稳定性或使用等效方法来实现这一点。我们的研究表明,对于某些模型,引入延迟并不会改变指数,但当引入延迟的方式不同时,指数就会发生变化。为了证实这些结果,我们还进行了数值模拟。最后,我们得出一些结论。
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A Model of Hepatitis B Viral Dynamics with Delays
Hepatitis B is a liver disease caused by the human hepatitis B virus (HBV). Mathematical models help further the understanding of the processes involved and help make predictions. The basic reproduction number, R0, is an index that predicts whether the disease will be chronic or not. This is the single most-important information that a mathematical model can give. Within-host virus processes involve delays. We study two within-host hepatitis B virus infection models without and with delay. One is a standard one, and the other considering additional processes and with two delays is new. We analyze the basic reproduction number and alternative threshold indices. The values of R0 and the alternative indices change depending on the model. All these indices predict whether the infection will persist or not, but they do not give the same rate of growth of the infection when it is starting. Therefore, the choice of the model is very important in establishing whether the infection is chronic or not and how fast it initially grows. We analyze these indices to see how to decrease their value. We study the effect of adding delays and how the threshold indices depend on how the delays are included. We do this by studying the local asymptotic stability of the disease-free equilibrium or by using an equivalent method. We show that, for some models, the indices do not change by introducing delays, but they change when the delays are introduced differently. Numerical simulations are presented to confirm the results. Finally, some conclusions are presented.
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