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.

项目总结/摘要 非结核分枝杆菌（NTM）是引起大量发病率和死亡率的新兴病原体， 尤其是在免疫抑制的患者中。虽然NTM越来越多地涉及医疗保健设施- 由于HCFA相关感染和暴发，目前还没有系统的NTM临床监测方法。作为 结果，目前的感染控制实践并不能一致地检测到临床上重要的NTM率增加，或NTM 集群，导致延迟的爆发检测和缓解。此外，NTM的存在在许多 健康护理环境增加了确定给定的患者的阳性培养物的群集是否是阳性培养物的困难。 NTM代表来自环境来源的多克隆污染或真正的单克隆爆发。因此，我们认为， 美国医院需要更好的方法来早期发现和描述HCFA NTM爆发。 结合1）用于早期检测HCFA NTM簇的系统分析技术和2） 流行病学表征相关NTM代表了一种创新和强大的方法，以减轻 并防止NTM在脆弱人群中爆发。本提案的总体目标是将联合收割机 优化的统计过程控制（SPC）方法与全基因组测序（WGS）作为一个集成 该平台旨在改进HCFA NTM集群和疫情的检测和调查。我们将使用这两个 医院网络中的技术，以测试中心假设，优化SPC方法结合 分子流行病学可以比标准方法更快、更有效地检测和减轻HCFA NTM集群 感染控制技术，并最终降低NTM爆发的发病率。我们计划验证这个假设 通过追求以下三个具体目标：1）开发优化的SPC策略，用于识别临床 HCFA NTM率的重要增加; 2）比较优化SPC监测的有效性， HCFA NTM与传统（非SPC）监测方法的比较;以及3）利用WGS评估 与临床重要NTM簇相关的NTM临床分离株。这些目标的实现将使 新的战略，以确定重要的NTM集群，提高对NTM收购的理解，并最终 预防HCFA 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，从而降低对住院患者造成伤害的风险。 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， 和多中心合作研究。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，致力于设计和实施新的干预措施，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 候选人在实现这些目标，包括密切监督经验丰富的共同导师，支持和 保护性的体制环境，以及完成拟议的研究和培训计划。