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耐药结核病的数学模型缺乏细菌异质性:系统性审查

Naomi M Fuller^1,2,3,4, Christopher F McQuaid^1,2,3,4, Martin J Harker^1,2,3,4

¹Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.

|April 10, 2024

概括

对耐药结核病 (DR-TB) 的数学模型往往忽视了细菌异质性. 纳入这种复杂性对于准确的预测和有效的公共卫生战略对抗抗菌素耐药性 (AMR) 至关重要.

科学领域:

流行病学和公共卫生.
数学建模的数学建模
微生物学微生物学

背景情况:

耐药结核病 (DR-TB) 构成了严重的全球健康威胁,阻碍了控制工作.
数学模型是通报公共卫生政策管理抗菌素耐药性 (AMR) 和结核病的重要工具.
模型中的细菌异质性可能会影响耐药性流行率的预测,并影响决策.

研究的目的:

系统地审查耐药菌根菌的数学模型,包括 Mycobacterium tuberculosis.
分析将细菌异质性纳入这些模型的方法.
确定现有的DR-TB模型的特征,并评估异质性表示的程度.

主要方法:

在五个数据库中按照PRISMA指南进行系统的文献审查.
纳入标准:耐药菌根菌的机械或模拟模型.
对模型特征的分析,对异质性的定义和表示方法.

主要成果:

确定了195项模拟DR-mycobacteria的研究,主要是M.结核病干预措施的动态传播模型.
只有23个模型 (8个宿主之间) 包含了细菌异质性,其中大多数专注于多种抗生素耐药性.
异质性通常由具有相同耐药性特征的细菌 (61%) 的不同适应性值表示.

结论:

对于DR-mycobacterium存在大量的数学模型,有助于政策和抵抗动态研究.
目前的大多数模型缺乏细菌异质性,可能导致错过了进化见解.
未来的建模工作应优先考虑细菌异质性的纳入,以获得更强大的预测和有效的结核病控制策略.

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