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Use of mathematical modelling to assess the impact of vaccines on antibiotic resistance

机译:使用数学建模来评估疫苗对抗生素抗性的影响

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摘要

Antibiotic resistance is a major global threat to the provision of safe and effective health care. To control antibiotic resistance, vaccines have been proposed as an essential intervention, complementing improvements in diagnostic testing, antibiotic stewardship, and drug pipelines. The decision to introduce or amend vaccination programmes is routinely based on mathematical modelling. However, few mathematical models address the impact of vaccination on antibiotic resistance. We reviewed the literature using PubMed to identify all studies that used an original mathematical model to quantify the impact of a vaccine on antibiotic resistance transmission within a human population. We reviewed the models from the resulting studies in the context of a new framework to elucidate the pathways through which vaccination might impact antibiotic resistance. We identified eight mathematical modelling studies; the state of the literature highlighted important gaps in our understanding. Notably, studies are limited in the range of pathways represented, their geographical scope, and the vaccine-pathogen combinations assessed. Furthermore, to translate model predictions into public health decision making, more work is needed to understand how model structure and parameterisation affects model predictions and how to embed these predictions within economic frameworks.
机译:抗生素抗性是对提供安全和有效的医疗保健的主要威胁。为了控制抗生素抗性,已经提出了疫苗作为基本干预,补充诊断测试,抗生素管道和药物管道的改善。介绍或修改疫苗接种计划的决定是常规的基于数学建模。然而,很少有数学模型解决了疫苗接种对抗生素抗性的影响。我们使用PubMed来审查文献来识别所有使用原始数学模型来量化疫苗对人群中抗生素抗性传递的影响的研究。我们在新框架的背景下从所产生的研究中审查了模型,以阐明疫苗接种可能影响抗生素抗性的途径。我们确定了八种数学建模研究;文献的状态突出了我们理解的重要差距。值得注意的是,研究在代表的途径范围内有限,其地理范围和疫苗 - 病原体组合评估。此外,为了将模型预测转化为公共健康决策,需要更多的工作来了解模型结构和参数化如何影响模型预测以及如何在经济框架内嵌入这些预测。

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  • 来源
    《The Lancet infectious diseases》 |2018年第6期|共10页
  • 作者单位

    London Sch Hyg &

    Trop Med Fac Epidemiol &

    Populat Hlth Ctr Math Modelling Infect Dis London;

    London Sch Hyg &

    Trop Med Fac Epidemiol &

    Populat Hlth Ctr Math Modelling Infect Dis London;

    Hlth Fdn London England;

    London Sch Hyg &

    Trop Med Fac Epidemiol &

    Populat Hlth Ctr Math Modelling Infect Dis London;

    Publ Hlth England Natl Infect Serv Modelling &

    Econ Unit London England;

    London Sch Hyg &

    Trop Med Fac Epidemiol &

    Populat Hlth Ctr Math Modelling Infect Dis London;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 传染病;
  • 关键词

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