BACKGROUND In 2014, enterovirus D68 (EV-D68) was responsible for an outbreak of severe respiratory illness in children, with 1,153 EV-D68 cases reported across 49 states. Despite this, there is no commercial assay for its detection in routine clinical care. BioFire® Syndromic Trends (Trend) is an epidemiological network that collects, in near real-time, deidentified. BioFire test results worldwide, including data from the BioFire® Respiratory Panel (RP). OBJECTIVES Using the RP version 1.7 (which was not explicitly designed to differentiate EV-D68 from other picornaviruses), we formulate a model, Pathogen Extended Resolution (PER), to distinguish EV-D68 from other human rhinoviruses/enteroviruses (RV/EV) tested for in the panel. Using PER in conjunction with Trend, we survey for historical evidence of EVD68 positivity and demonstrate a method for prospective real-time outbreak monitoring within the network. STUDY DESIGN PER incorporates real-time polymerase chain reaction metrics from the RPRV/EV assays. Six institutions in the United States and Europe contributed to the model creation, providing data from 1,619 samples spanning two years, confirmed by EV-D68 gold-standard molecular methods. We estimate outbreak periods by applying PER to over 600,000 historical Trend RP tests since 2014. Additionally, we used PER as a prospective monitoring tool during the 2018 outbreak. RESULTS The final PER algorithm demonstrated an overall sensitivity and specificity of 87.1% and 86.1%, respectively, among the gold-standard dataset. During the 2018 outbreak monitoring period, PER alerted the research network of EV-D68 emergence in July. One of the first sites to experience a significant increase, Nationwide Children's Hospital, confirmed the outbreak and implemented EV-D68 testing at the institution in response. Applying PER to the historical Trend dataset to determine rates among RP tests, we find three potential outbreaks with predicted regional EV-D68 rates as high as 37% in 2014, 16% in 2016, and 29% in 2018. CONCLUSIONS Using PER within the Trend network was shown to both accurately predict outbreaks of EV-D68 and to provide timely notifications of its circulation to participating clinical laboratories.

中文翻译：

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通过综合征疾病流行病学网络检测肠道病毒D68爆发。

背景技术2014年，肠道病毒D68（EV-D68）引起了儿童严重呼吸系统疾病的爆发，在49个州中报告了1153例EV-D68病例。尽管如此，在常规临床护理中尚无商业化的检测方法可用于检测。BioFire®Syndromic Trends（趋势）是一种流行病学网络，几乎实时地收集身份不明的信息。全球范围内的BioFire测试结果，包括BioFire®呼吸小组（RP）的数据。目的使用RP版本1.7（未明确设计以区分EV-D68与其他小核糖核酸病毒），我们制定了病原扩展分辨率（PER）模型，以将EV-D68与其他人类鼻病毒/肠病毒（RV / EV）区分在面板中进行了测试。将PER与趋势结合使用，我们调查了EVD68阳性的历史证据，并演示了一种在网络内进行前瞻性实时爆发监测的方法。Study DESIGN PER结合了RPRV / EV分析的实时聚合酶链反应指标。美国和欧洲的六个机构为模型的创建做出了贡献，通过EV-D68金标准分子方法证实了该模型提供了两年中1,619个样品的数据。自2014年以来，我们通过对超过600,000项历史趋势RP测试应用PER来估算暴发期。此外，我们在2018年暴发期间将PER用作前瞻性监测工具。结果最终的PER算法在金标准数据集中显示出分别为87.1％和86.1％的总体敏感性和特异性。在2018年爆发监测期间，PER在7月通知了EV-D68出现的研究网络。全国儿童医院是最早经历显着增加的地点之一，证实了疫情并在该机构实施了EV-D68测试。将PER应用于历史趋势数据集以确定RP测试之间的比率，我们发现了三个潜在的爆发，预测的区域EV-D68比率在2014年分别高达37％，2016年为16％和2018年为29％。结果表明，趋势网络既可以准确预测EV-D68的爆发，又可以及时向参与的临床实验室提供其流通情况的通知。