Combined Use of Statistical Process Control and Whole Genome Sequencing to Detect and Investigate Nontuberculous Mycobacterial Clusters and Outbreaks

结合使用统计过程控制和全基因组测序来检测和调查非结核分枝杆菌簇和爆发

• 批准号: 10283630
• 负责人: Arthur W Baker
• 金额: $ 18.88万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10283630
• 关键词: Affect; Clinical; Clostridium difficile; Complement; Coupled; Data; Detection; Development; Disease Outbreaks; Early Diagnosis; Effectiveness; Environment; Environmental Pollution; Exhibits; Foundations; Genomics; Goals; Health care facility; Healthcare; Heart Transplantation; Hospitals; Immunocompromised Host; Incidence; Infection; Infection Control; Intervention; Investigation; Lead; Lung Transplantation; Mentors; Methods; Microbiology; Molecular; Molecular Epidemiology; Morbidity - disease rate; Mycobacterium Infections; Outcome; Patients; Phylogenetic Analysis; Physicians; Population; Prevention; Process; Randomized Controlled Trials; Research Training; Risk; Scientist; Source; Statistical Computing; Surgical Wound Infection; Surveillance Methods; Techniques; Testing; Time Series Analysis; Transplant Recipients; Transplantation; Variant; Vulnerable Populations; Work; clinical sequencing; compare effectiveness; design; emerging pathogen; experience; follow-up; genome sequencing; healthcare-associated infections; improved; innovation; mortality; non-tuberculosis mycobacteria; novel; novel strategies; prevent; prospective; skills; whole genome

Project Summary/Abstract Nontuberculous mycobacteria (NTM) are emerging pathogens that cause substantial morbidity and mortality, especially among immunosuppressed patients. While NTM are increasingly implicated in healthcare facility- associated (HCFA) infections and outbreaks, no systematic method for NTM clinical surveillance exists. As a result, current infection control practices inconsistently detect clinically important increases in NTM rates, or NTM clusters, leading to delayed outbreak detection and mitigation. Furthermore, the presence of NTM in many healthcare environments increases the difficulty of determining whether a cluster of positive cultures for a given NTM represents polyclonal contamination from environmental sources or a true monoclonal outbreak. Therefore, U.S. hospitals need better approaches for early detection and characterization of HCFA NTM outbreaks. The combination of 1) systematic analytic techniques for early detection of HCFA NTM clusters and 2) molecular epidemiology to characterize the relevant NTM represents an innovative and powerful approach to mitigating and preventing NTM outbreaks in vulnerable populations. The overall objective of this proposal is to combine optimized statistical process control (SPC) methods with whole genome sequencing (WGS) as an integrated platform to improve detection and investigation of HCFA NTM clusters and outbreaks. We will use these two techniques within a hospital network to test the central hypothesis that optimized SPC methods combined with molecular epidemiology can detect and mitigate HCFA NTM clusters more quickly and effectively than standard infection control techniques and ultimately reduce morbidity from NTM outbreaks. We plan to test this hypothesis by pursuing the following three Specific Aims: 1) Develop an optimized SPC strategy for identification of clinically important increases in rates of HCFA NTM; 2) Compare the effectiveness of optimized SPC surveillance for HCFA NTM to traditional (non-SPC) surveillance methods; and 3) Utilize WGS to evaluate clonal relatedness of NTM clinical isolates associated with clinically important NTM clusters. Completion of these Aims will develop a novel strategy to identify important NTM clusters, improve understanding of NTM acquisition, and ultimately prevent HCFA NTM infection. This work has potential to change the way healthcare facilities perform NTM surveillance and prevent NTM infection, thereby reducing the risk of harm to hospitalized patients. The candidate’s short-term goals include enhancing his skillsets in time series analyses, genomic sequencing, and multicenter collaborative studies. His long-term goal is to become a successful, independent physician scientist, well suited to lead a team dedicated to the design and implementation of novel interventions aimed at preventing healthcare-associated infections in immunosuppressed patients. Several key factors will assist the candidate in achieving these goals, including close oversight from experienced co-mentors, a supportive and protective institutional environment, and completion of the proposed research and training plan.

项目摘要/摘要 非结核分枝杆菌(NTM)是一种新出现的病原体，可导致大量的发病率和死亡率， 尤其是在免疫抑制的患者中。虽然NTM越来越多地牵涉到医疗设施- 至于相关(HCFA)感染和暴发，目前尚无系统的方法用于非传染性支气管炎临床监测。作为一名 结果，目前的感染控制实践不一致地检测到临床上重要的NTM率或NTM的增加 聚集性，导致疫情检测和缓解的延迟。此外，NTM在许多地方的存在 医疗保健环境增加了确定一群积极的文化是否对给定的 NTM代表环境来源的多克隆污染或真正的单克隆性暴发。因此， 美国医院需要更好的方法来早期发现和表征HCFA非传染性支气管炎暴发。 早期检测HCFA NTM团簇的系统分析技术与分子技术的结合 流行病学描述相关的NTM代表了一种创新和有力的方法来减轻 并防止在脆弱人群中爆发NTM。这项提案的总体目标是将 以全基因组测序为一体的优化统计过程控制方法 平台，以改进对HCFA非传染性支气管炎聚集性和疫情的检测和调查。我们将使用这两个 医院网络内的技术来检验中心假设，即优化的SPC方法与 分子流行病学可以比标准方法更快、更有效地检测和缓解HCFA NTM聚集性 感染控制技术，并最终减少非传染性疾病暴发的发病率。我们计划检验这一假设 通过追求以下三个具体目标：1)开发优化的SPC策略，用于临床鉴定 HCFA-NTM比率的重要增加；2)比较优化的SPC监测的有效性 HCFA NTM与传统(非SPC)监测方法的相关性；以及3)利用WGS来评估克隆性 与临床重要的NTM聚集性相关的NTM临床分离株。完成这些目标将形成一种 确定重要的NTM集群的新战略，提高对NTM收购的理解，并最终 预防HCFA和NTM感染。这项工作有可能改变医疗机构执行NTM的方式 监测和预防NTM感染，从而减少对住院患者的伤害风险。 候选人的短期目标包括提高他在时间序列分析、基因组测序、 和多中心协作研究。他的长期目标是成为一名成功的、独立的医生 科学家，非常适合领导一个团队，致力于设计和实施旨在 预防免疫抑制患者的医疗保健相关感染。几个关键因素将有助于 实现这些目标的候选人，包括经验丰富的共同导师的密切监督，支持和 保护体制环境，完成拟议的研究和培训计划。