Suppr超能文献

病原体种群结构可以解释医院疫情爆发的原因。

Pathogen population structure can explain hospital outbreaks.

机构信息

Ecology, Evolution and Environmental Biology Department, Columbia University, New York, NY, 10027, USA.

Department of Biomedical Informatics, Columbia University Medical Center, New York, NY, 10032, USA.

出版信息

ISME J. 2018 Dec;12(12):2835-2843. doi: 10.1038/s41396-018-0235-5. Epub 2018 Jul 25.

Abstract

Hospitalized patients are at risk for increased length of stay, illness, or death due to hospital acquired infections. The majority of hospital transmission models describe dynamics on the level of the host rather than on the level of the pathogens themselves. Accordingly, epidemiologists often cannot complete transmission chains without direct evidence of either host-host contact or a large reservoir population. Here, we propose an ecology-based model to explain the transmission of pathogens in hospitals. The model is based upon metapopulation biology, which describes a group of interacting localized populations and island biogeography, which provides a basis for how pathogens may be moving between locales. Computational simulation trials are used to assess the applicability of the model. Results indicate that pathogens survive for extended periods without the need for large reservoirs by living in localized ephemeral populations while continuously transmitting pathogens to new seed populations. Computational simulations show small populations spending significant portions of time at sizes too small to be detected by most surveillance protocols and that the number and type of these ephemeral populations enable the overall pathogen population to be sustained. By modeling hospital pathogens as a metapopulation, many observations characteristic of hospital acquired infection outbreaks for which there has previously been no sufficient biological explanation, including how and why empirically successful interventions work, can now be accounted for using population dynamic hypotheses. Epidemiological links between temporally isolated outbreaks are explained via pathogen population dynamics and potential outbreak intervention targets are identified.

摘要

住院患者由于医院获得性感染而面临住院时间延长、病情加重或死亡的风险。大多数医院传播模型描述的是宿主层面的动态,而不是病原体本身的动态。因此,流行病学家通常无法在没有宿主-宿主接触或大量储主人群的直接证据的情况下完成传播链。在这里,我们提出了一个基于生态学的模型来解释医院病原体的传播。该模型基于集合种群生物学,它描述了一组相互作用的局部种群,以及岛屿生物地理学,为病原体在不同地点之间的传播提供了基础。通过计算模拟试验来评估模型的适用性。结果表明,病原体通过生活在局部短暂的种群中,在不需要大型储主的情况下可以长时间存活,并不断向新的种子种群传播病原体。计算模拟表明,小种群在大小上花费大量时间,小到大多数监测方案都无法检测到,而这些短暂种群的数量和类型使整个病原体种群得以维持。通过将医院病原体建模为集合种群,可以解释许多以前没有充分生物学解释的医院获得性感染爆发的特征观察结果,包括为什么经验上成功的干预措施有效,以及如何解释,现在可以使用种群动态假设来解释。通过病原体种群动态解释了时间上孤立的爆发之间的流行病学联系,并确定了潜在的爆发干预目标。

相似文献

1
Pathogen population structure can explain hospital outbreaks.
ISME J. 2018 Dec;12(12):2835-2843. doi: 10.1038/s41396-018-0235-5. Epub 2018 Jul 25.
2
Measuring distance through dense weighted networks: The case of hospital-associated pathogens.
PLoS Comput Biol. 2017 Aug 3;13(8):e1005622. doi: 10.1371/journal.pcbi.1005622. eCollection 2017 Aug.
3
When and why direct transmission models can be used for environmentally persistent pathogens.
PLoS Comput Biol. 2021 Dec 1;17(12):e1009652. doi: 10.1371/journal.pcbi.1009652. eCollection 2021 Dec.
4
A hybrid simulation model approach to examine bacterial genome sequencing during a hospital outbreak.
BMC Infect Dis. 2020 Jan 23;20(1):72. doi: 10.1186/s12879-019-4743-3.
6
Bayesian inference of hospital-acquired infectious diseases and control measures given imperfect surveillance data.
Biostatistics. 2007 Apr;8(2):383-401. doi: 10.1093/biostatistics/kxl017. Epub 2006 Aug 22.
7
Utility of R0 as a predictor of disease invasion in structured populations.
J R Soc Interface. 2007 Apr 22;4(13):315-24. doi: 10.1098/rsif.2006.0185.
10
Characterising the Transmission Dynamics of Acinetobacter baumannii in Intensive Care Units Using Hidden Markov Models.
PLoS One. 2015 Jul 1;10(7):e0132037. doi: 10.1371/journal.pone.0132037. eCollection 2015.

本文引用的文献

1
Bacterial colonization and succession in a newly opened hospital.
Sci Transl Med. 2017 May 24;9(391). doi: 10.1126/scitranslmed.aah6500.
2
Prevalence and pattern of antibiotic resistance of isolated from door handles and other points of contact in public hospitals in Ghana.
Antimicrob Resist Infect Control. 2017 May 10;6:44. doi: 10.1186/s13756-017-0203-2. eCollection 2017.
5
Carbapenemase-Producing Klebsiella pneumoniae, a Key Pathogen Set for Global Nosocomial Dominance.
Antimicrob Agents Chemother. 2015 Oct;59(10):5873-84. doi: 10.1128/AAC.01019-15. Epub 2015 Jul 13.
10

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验