Research and implementation of a whole-genome sequencing surveillance system for outbreak detection
Research and implementation of a whole-genome sequencing surveillance system for outbreak detection
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DOI：
10.1017/ash.2022.211
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发表时间：
2022-05-16
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背景：传统的感染预防（IP）方法的爆发检测往往依赖于局限于单一位置的地理时间聚类。我们最近开发了医疗相关传播增强检测系统（EDS-HAT），该系统结合了全基因组测序（WGS）监测和电子健康记录（EHR）的机器学习。我们的回顾性研究结果显示，使用EDS-HAT可以真实的实时避免潜在的传输并节省成本。在这里，我们描述的过程和EDS-HAT实时实施的初步结果。方法：实时全基因组测序监测于2021年11月1日开始。采集了住院≥3天或在前30天内有近期医疗暴露的选定细菌病原体阳性患者培养物。如果在除艰难梭菌（≤2个SNP）外的所有微生物中发现≤15个单核苷酸多态性（SNP），则认为分离株具有遗传相关性。研究和IP团队对集群进行了手动调查，IP团队进行了干预。收集了关于收集、分析、通知和干预日期的数据。结果：截至2022年1月11日，已有413株分离株进行了全基因组测序。其中，18株独特的患者分离株与≥1株其他分离株遗传相关，包括7个聚类（范围，2-6例患者）。值得注意的发现包括可能与共用支气管镜相关的铜绿假单胞菌群，与尸检血培养实践相关的粘质沙雷氏菌假爆发，以及共用移植单位的万古霉素耐药屎肠球菌群。仅有1个2株肺炎克雷伯菌群的传播途径未知。从患者培养日期到IP通知的中位周转时间为19天（范围13-28天），寒假期间出现明显延迟。结论：实时WGS可以识别小集群，包括潜在的可中断的传输路径。快速的周转时间、临床和基因组实验室之间的协调以及强大的IP团队是实施WGS监测计划的关键因素。实时WGS监测有可能降低医院成本，改善患者安全并挽救生命。资金：无披露：无
Background: Traditional infection prevention (IP) methods for outbreak detection often rely on geotemporal clustering confined to single locations. We recently developed the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), which combines whole-genome sequencing (WGS) surveillance and machine learning of the electronic health record (EHR). Our retrospective research findings show potential transmissions averted and cost savings using EDS-HAT in real time. Here, we describe the process and initial findings from EDS-HAT real-time implementation. Methods: Real-time whole-genome sequencing surveillance began on November 1, 2021. Patient cultures positive for select bacterial pathogens who were hospitalized for ≥3 days or had a recent healthcare exposure in the prior 30-days were collected. Isolates were deemed genetically related if ≤15 single-nucleotide polymorphisms (SNPs) were identified for all organisms except Clostridioides difficile (≤2 SNPs). Clusters were manually investigated by both research and IP teams, and interventions were performed by the IP team. Data on collection, analysis, notification, and intervention dates were gathered. Results: As of January 11, 2022, 413 isolates had undergone whole-genome sequencing. Among them, 18 unique patient isolates were genetically related to ≥1 other isolate, comprising 7 clusters (range, 2–6 patients). Notable findings include a Pseudomonas aeruginosa cluster possibly related to a shared bronchoscope, a pseudo-outbreak of Serratia marcescens related to autopsy blood culture practice, and a cluster of vancomycin-resistant Enterococcus faecium on a shared transplant unit. Only 1 cluster of 2 isolates of Klebsiella pneumoniae had no known possible transmission routes. The median turnaround time from patient’s culture date to IP notification was 19 days (range, 13–28), with noted delays over the winter holiday. Concusions: Real-time WGS can identify small clusters including potentially interruptible transmission routes. Rapid turnaround time, coordination between clinical and genomic laboratories, and a robust IP team are key factors in implementing a WGS surveillance program. Real-time WGS surveillance has the potential to reduce costs for hospitals, improve patient safety, and save lives. Funding: None Disclosures: None