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: 10408865
• 负责人: Arthur W Baker
• 金额: $ 18.84万
• 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/10408865
• 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.

项目概要/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 越来越多地涉及医疗机构 - 相关（HCFA）感染和暴发，目前尚无系统的 NTM 临床监测方法。作为一个 结果，当前的感染控制实践并不一致地检测到临床上重要的 NTM 率增加，或 NTM 集群，导致疫情检测和缓解延迟。此外，NTM 存在于许多 医疗保健环境增加了确定给定的一组阳性培养物是否存在的难度。 NTM 代表来自环境来源的多克隆污染或真正的单克隆爆发。所以， 美国医院需要更好的方法来早期发现和表征 HCFA NTM 疫情。 1) 早期检测 HCFA NTM 簇的系统分析技术和 2) 分子生物学相结合 流行病学来描述相关 NTM 的特征代表了一种创新而有力的缓解方法 预防弱势群体中 NTM 的爆发。该提案的总体目标是结合 优化的统计过程控制（SPC）方法与全基因组测序（WGS）作为集成 平台，以改进 HCFA NTM 集群和疫情的检测和调查。我们将使用这两个 医院网络内的技术来测试优化 SPC 方法与 分子流行病学可以比标准更快更有效地检测和减轻 HCFA NTM 簇 感染控制技术并最终降低 NTM 爆发的发病率。我们计划检验这个假设 通过追求以下三个具体目标： 1) 制定优化的 SPC 策略来识别临床 HCFA NTM 比率显着增加； 2) 比较优化 SPC 监控的有效性 HCFA NTM 到传统（非 SPC）监测方法； 3) 利用全基因组测序（WGS）评估克隆相关性 NTM 临床分离株与临床上重要的 NTM 簇相关。完成这些目标将发展出 识别重要 NTM 簇、提高对 NTM 获取的理解的新颖策略，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 监测并预防 NTM 感染，从而降低住院患者受到伤害的风险。 候选人的短期目标包括增强时间序列分析、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医生 科学家，非常适合领导一个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 候选人实现这些目标，包括经验丰富的共同导师的密切监督，支持和 保护性制度环境，并完成拟议的研究和培训计划。