Enterovirus D68 outbreak detection through a syndromic disease epidemiology network
[Display omitted] •An algorithm to predict the presence enterovirus D68 among a commercial respiratory disease diagnostic test was developed.•The algorithm was used with test results exported to an epidemiology network for real-time monitoring and historical outbreak prediction.•Historical outbreak...
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| Published in: | Journal of clinical virology Vol. 124; p. 104262 |
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Netherlands
Elsevier B.V
01-03-2020
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | [Display omitted]
•An algorithm to predict the presence enterovirus D68 among a commercial respiratory disease diagnostic test was developed.•The algorithm was used with test results exported to an epidemiology network for real-time monitoring and historical outbreak prediction.•Historical outbreak predictions coincide with known periods of high EV-D68 circulation in 2014 and 2016.•The algorithm alerted clinical laboratories of the potential circulation of EV-D68 in 2018, prompting clinical testing for EV-D68 at one site.
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).
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.
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.
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.
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 |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1386-6532 1873-5967 |
| DOI: | 10.1016/j.jcv.2020.104262 |