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利用数学模型评估疫苗对抗生素耐药性的影响。

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

机构信息

Centre for the Mathematical Modelling of Infectious Diseases and Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.

Centre for the Mathematical Modelling of Infectious Diseases and Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.

出版信息

Lancet Infect Dis. 2018 Jun;18(6):e204-e213. doi: 10.1016/S1473-3099(17)30478-4. Epub 2017 Nov 13.

DOI:10.1016/S1473-3099(17)30478-4
PMID:29146178
Abstract

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.

摘要

抗生素耐药性是全球范围内安全有效医疗保健服务的主要威胁。为了控制抗生素耐药性,疫苗已被提议作为一种重要的干预措施,与改进诊断检测、抗生素管理和药物研发渠道相辅相成。引入或修改疫苗接种计划的决策通常基于数学模型。然而,很少有数学模型能够解决疫苗接种对抗生素耐药性的影响。我们使用 PubMed 检索文献,以确定所有使用原始数学模型来量化疫苗对人群中抗生素耐药性传播影响的研究。我们根据一个新框架来审查这些研究中的模型,以阐明疫苗接种可能影响抗生素耐药性的途径。我们确定了八项数学建模研究;文献的现状突出了我们理解中的重要差距。值得注意的是,研究在代表的途径、地理范围以及评估的疫苗-病原体组合方面受到限制。此外,为了将模型预测转化为公共卫生决策,需要做更多的工作来了解模型结构和参数化如何影响模型预测,以及如何将这些预测嵌入经济框架中。

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