Treatment failure and the threshold of disease extinction

IF 8.8 3区医学 Q1 Medicine

Infectious Disease Modelling Pub Date : 2024-12-17 DOI:10.1016/j.idm.2024.12.007

Pichaya Voottipruex , Nichaphat Patanarapeelert , Klot Patanarapeelert

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Abstract

Antibiotic treatment failure related to carriers poses a serious problem to physicians and epidemiologists. Due to the sparsity of data, assessing the role in infection dynamics is difficult. In this study, we examined the possibility that a particular therapeutic effectiveness will be regarded as the disease extinction threshold through the mathematical modelling approach. Including the treatment state in the generic epidemic model with carrier allows us to describe the role of carriers in the treatment failure. The parameterized extinction thresholds were derived via the basic reproduction number for deterministic model, and via the Jury stability criterion for the stochastic model. Existence conditions for the stochastic threshold were derived without the exact formula of the spectral radius of the expectation matrix. The results show that the transmissibility of carrier is necessary for the extinction threshold via treatment failure. The expected extinction threshold may occur subject to the certain range of the transmission potential of the symptomatic infection. This existence conditions are independent of the rate at which the carriers undergo treatment and can be used to support a control strategy.

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治疗失败与疾病消失的阈值。

与携带者相关的抗生素治疗失败对医生和流行病学家来说是一个严重的问题。由于数据的稀疏性，评估在感染动力学中的作用是困难的。在这项研究中，我们通过数学建模方法检查了将特定治疗效果视为疾病消失阈值的可能性。在带有携带者的通用流行病模型中加入治疗状态，使我们能够描述携带者在治疗失败中的作用。通过确定性模型的基本再现数和随机模型的Jury稳定性判据，分别推导出参数化的消光阈值。在没有期望矩阵谱半径精确公式的情况下，导出了随机阈值的存在条件。结果表明，载体的透射率对于处理失败的消光阈值是必要的。在有症状感染的传播潜力的一定范围内，可能出现预期的灭绝阈值。这种存在条件与携带者接受治疗的速率无关，可用于支持控制策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Infectious Disease Modelling Mathematics-Applied Mathematics

CiteScore

17.00

自引率

3.40%

发文量

审稿时长

17 weeks

期刊介绍： Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.