Dynamical modeling of hospital transmission and antibiotic resistance evolution in a multidrug resistant nosocomial pathogen
多重耐药医院病原体的医院传播和抗生素耐药性进化的动态模型
基本信息
- 批准号:10089393
- 负责人:
- 金额:$ 62.39万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-02-01 至 2024-01-31
- 项目状态:已结题
- 来源:
- 关键词:AccountingAdmission activityAntibiotic ResistanceAntibiotic-resistant organismAntibioticsBacteriaBioinformaticsBiological AssayClinicalCollectionCommunitiesComputerized Medical RecordCustomDaptomycinDataEnterococcus faeciumEpidemiologyEvolutionGeneral HospitalsGeneticGoalsHospitalsInfection preventionInterventionKnowledgeLinezolidLocationMarkov ChainsMedical RecordsMethodsMicrobiologyModelingModern MedicineMovementMulti-Drug ResistanceNosocomial InfectionsOrganismPatientsPatternPharmaceutical PreparationsPhenotypePhylogenetic AnalysisPrevention MeasuresPrevention strategyProcessProtocols documentationRecoveryRefractoryResistanceRisk FactorsRoleSamplingSignal TransductionSourceStructureSystemTechniquesTestingWorkbasedata integrationdesignelectronic dataepidemiological modelgenetic analysisimprovednovelpathogenportabilitypredictive modelingsurveillance datatheoriestherapy designtooltransmission processtrendwhole genome
项目摘要
PROJECT SUMMARY/ABSTRACT
Enterococcus faecium is a leading cause of hospital acquired infections that has proven refractory to infection
prevention measures and has evolved increasing levels of antibiotic resistance over the last 40 years. How
resistance evolves and spreads in this pathogen is uncertain because transmission and selection are hidden
processes: transmission occurs silently between asymptomatically colonized patients, which obscures the
signal of selection observed from clinical isolates.
The proposed work will develop and deploy powerful new statistical inference techniques to assimilate
data from electronic medical records, microbiological samples, and whole genome sequences into explicit,
mechanistic models of transmission and antibiotic resistance evolution in E. faecium. The work is made
possible by unique features of the study system: we have documented ongoing transmission and resis-
tance evolution in the pathogen E. faecium and possess both a nearly perfect record of patient movement
and antibiotic exposure and a large collection of patient samples from a thorough and active surveillance
protocol.
The specific aims of the proposal are: (I) To develop and fit a detailed E. faecium transmission model to
medical record data to precisely quantify: (i) transmission rates, (ii) recovery rates, (iii) the rate of evo-
lution of resistance, (iv) drivers of these rates, including contact precautions and antibiotic exposure, and
(v) potential interactions between resistance and transmissibility. (II) Bioinformatic approaches that utilize
whole genome sequences for c. 600 E. faecium isolates/yr and electronic medical records will be used to es-
timate size, structure, and location of transmission chains and characterize patterns of resistance evolution
across the resulting transmission network. (III) Hypotheses based on the transition model from Aim I will
be directly tested by using the genetic data from Aim II.
The methods developed herein will be applicable to a broad array of pathogens and clinical settings, and
will facilitate the rational design of strategies to slow or even reverse the evolution of antibiotic resistance.
In particular, the models and protocols will be portable to hospitals generally, where they will be useful for
designing interventions.
项目摘要/摘要
粪肠球菌是医院获得性感染的主要原因,已被证明是对感染无效的。
预防措施,并在过去40年中演变出越来越多的抗生素耐药性。多么
这种病原菌的抗药性进化和传播是不确定的,因为传递和选择是隐藏的
传播过程:在无症状的被殖民的患者之间静默传播,这掩盖了
从临床分离株观察到的选择信号。
拟议的工作将开发和部署强大的新统计推断技术,以吸收
将电子病历、微生物样本和全基因组序列中的数据转换为显式,
粪肠球菌传播和耐药性进化的机制模型。作品完成了
可能通过研究系统的独特功能:我们记录了正在进行的传播和耐药性-
粪肠球菌和两者几乎完美地记录了患者的活动
和抗生素暴露以及从彻底和积极的监测中收集的大量患者样本
协议。
这项建议的具体目的是:(I)开发和fi一个详细的粪肠球菌传播模型,以
病历数据以精确量化:(I)传播率,(Ii)恢复率,(Iii)Evo-
消除耐药性;(4)这些比率的驱动因素,包括接触预防措施和抗生素暴露;以及
(V)抗性和传播性之间的潜在相互作用。(2)利用生物信息学方法
约600株粪肠球菌分离株/年的全基因组序列和电子病历将用于ES-
传输链的确切大小、结构和位置,并表征抗性进化的模式
通过由此产生的传输网络。(3)基于AIM一的过渡模式的假设将
通过使用AIM II的遗传数据直接进行测试。
这里开发的方法将适用于广泛的病原体和临床环境,以及
将有助于合理设计减缓甚至逆转抗生素耐药性演变的策略。
特别是,这些模型和协议将可移植到一般医院,在那里它们将用于
设计干预措施。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Robert J Woods其他文献
Computational carbohydrate chemistry: what theoretical methods can tell us
- DOI:
10.1023/a:1006984709892 - 发表时间:
1998-01-01 - 期刊:
- 影响因子:3.100
- 作者:
Robert J Woods - 通讯作者:
Robert J Woods
Robert J Woods的其他文献
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{{ truncateString('Robert J Woods', 18)}}的其他基金
Dynamical modeling of hospital transmission and antibiotic resistance evolution in a multidrug resistant nosocomial pathogen
多重耐药医院病原体的医院传播和抗生素耐药性进化的动态模型
- 批准号:
10561643 - 财政年份:2019
- 资助金额:
$ 62.39万 - 项目类别:
Population Dynamics of Rotavirus: A Combined Theoretical, Bioinformatic and Laboratory Based Approach
轮状病毒的种群动态:理论、生物信息学和实验室相结合的方法
- 批准号:
9905480 - 财政年份:2016
- 资助金额:
$ 62.39万 - 项目类别: