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利用数学模型评估抗生素群体给药对社区内部及社区之间抗菌药物耐药性的影响。

Uses of mathematical modeling to estimate the impact of mass drug administration of antibiotics on antimicrobial resistance within and between communities.

作者信息

Olesen Scott W

机构信息

Department of Immunology and Infectious Diseases, Harvard Chan School, Boston, MA, USA.

出版信息

Infect Dis Poverty. 2022 Jun 30;11(1):75. doi: 10.1186/s40249-022-00997-7.

DOI:10.1186/s40249-022-00997-7
PMID:35773748
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9245243/
Abstract

BACKGROUND

Antibiotics are a key part of modern healthcare, but their use has downsides, including selecting for antibiotic resistance, both in the individuals treated with antibiotics and in the community at large. When evaluating the benefits and costs of mass administration of azithromycin to reduce childhood mortality, effects of antibiotic use on antibiotic resistance are important but difficult to measure, especially when evaluating resistance that "spills over" from antibiotic-treated individuals to other members of their community. The aim of this scoping review was to identify how the existing literature on antibiotic resistance modeling could be better leveraged to understand the effect of mass drug administration (MDA) on antibiotic resistance.

MAIN TEXT

Mathematical models of antibiotic use and resistance may be useful for estimating the expected effects of different MDA implementations on different populations, as well as aiding interpretation of existing data and guiding future experimental design. Here, strengths and limitations of models of antibiotic resistance are reviewed, and possible applications of those models in the context of mass drug administration with azithromycin are discussed.

CONCLUSIONS

Statistical models of antibiotic use and resistance may provide robust and relevant estimates of the possible effects of MDA on resistance. Mechanistic models of resistance, while able to more precisely estimate the effects of different implementations of MDA on resistance, may require more data from MDA trials to be accurately parameterized.

摘要

背景

抗生素是现代医疗保健的关键组成部分,但其使用存在弊端,包括在接受抗生素治疗的个体以及整个社区中引发抗生素耐药性。在评估大规模使用阿奇霉素以降低儿童死亡率的益处和成本时,抗生素使用对抗生素耐药性的影响很重要但难以衡量,尤其是在评估从接受抗生素治疗的个体“溢出”到其社区其他成员的耐药性时。本综述的目的是确定如何更好地利用现有关于抗生素耐药性建模的文献来理解大规模药物管理(MDA)对抗生素耐药性的影响。

正文

抗生素使用和耐药性的数学模型可能有助于估计不同的大规模药物管理实施方式对不同人群的预期影响,以及辅助解释现有数据并指导未来的实验设计。在此,我们回顾了抗生素耐药性模型的优势和局限性,并讨论了这些模型在大规模使用阿奇霉素的背景下的可能应用。

结论

抗生素使用和耐药性的统计模型可能为大规模药物管理对耐药性的可能影响提供可靠且相关的估计。耐药性的机制模型虽然能够更精确地估计不同的大规模药物管理实施方式对耐药性的影响,但可能需要更多来自大规模药物管理试验的数据才能准确地进行参数化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e9a/9245243/a0cff1ef1d7b/40249_2022_997_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e9a/9245243/11a3e67ada9e/40249_2022_997_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e9a/9245243/7fc9fafe5417/40249_2022_997_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e9a/9245243/a0cff1ef1d7b/40249_2022_997_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e9a/9245243/11a3e67ada9e/40249_2022_997_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e9a/9245243/7fc9fafe5417/40249_2022_997_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e9a/9245243/a0cff1ef1d7b/40249_2022_997_Fig3_HTML.jpg

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