Cargando…

Real-time gastrointestinal infection surveillance through a cloud-based network of clinical laboratories

Acute gastrointestinal infection (AGI) represents a significant public health concern. To control and treat AGI, it is critical to quickly and accurately identify its causes. The use of novel multiplex molecular assays for pathogen detection and identification provides a unique opportunity to improv...

Descripción completa

Detalles Bibliográficos
Autores principales: Ruzante, Juliana M., Olin, Katherine, Munoz, Breda, Nawrocki, Jeff, Selvarangan, Rangaraj, Meyers, Lindsay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087049/
https://www.ncbi.nlm.nih.gov/pubmed/33930062
http://dx.doi.org/10.1371/journal.pone.0250767
_version_ 1783686608845799424
author Ruzante, Juliana M.
Olin, Katherine
Munoz, Breda
Nawrocki, Jeff
Selvarangan, Rangaraj
Meyers, Lindsay
author_facet Ruzante, Juliana M.
Olin, Katherine
Munoz, Breda
Nawrocki, Jeff
Selvarangan, Rangaraj
Meyers, Lindsay
author_sort Ruzante, Juliana M.
collection PubMed
description Acute gastrointestinal infection (AGI) represents a significant public health concern. To control and treat AGI, it is critical to quickly and accurately identify its causes. The use of novel multiplex molecular assays for pathogen detection and identification provides a unique opportunity to improve pathogen detection, and better understand risk factors and burden associated with AGI in the community. In this study, de-identified results from BioFire(®) FilmArray(®) Gastrointestinal (GI) Panel were obtained from January 01, 2016 to October 31, 2018 through BioFire(®) Syndromic Trends (Trend), a cloud database. Data was analyzed to describe the occurrence of pathogens causing AGI across United States sites and the relative rankings of pathogens monitored by FoodNet, a CDC surveillance system were compared. During the period of the study, the number of tests performed increased 10-fold and overall, 42.6% were positive for one or more pathogens. Seventy percent of the detections were bacteria, 25% viruses, and 4% parasites. Clostridium difficile, enteropathogenic Escherichia coli (EPEC) and norovirus were the most frequently detected pathogens. Seasonality was observed for several pathogens including astrovirus, rotavirus, and norovirus, EPEC, and Campylobacter. The co-detection rate was 10.2%. Enterotoxigenic E. coli (ETEC), Plesiomonas shigelloides, enteroaggregative E. coli (EAEC), and Entamoeba histolytica were detected with another pathogen over 60% of the time, while less than 30% of C. difficile and Cyclospora cayetanensis were detected with another pathogen. Positive correlations among co-detections were found between Shigella/Enteroinvasive E. coli with E. histolytica, and ETEC with EAEC. Overall, the relative ranking of detections for the eight GI pathogens monitored by FoodNet and BioFire Trend were similar for five of them. AGI data from BioFire Trend is available in near real-time and represents a rich data source for the study of disease burden and GI pathogen circulation in the community, especially for those pathogens not often targeted by surveillance.
format Online
Article
Text
id pubmed-8087049
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-80870492021-05-06 Real-time gastrointestinal infection surveillance through a cloud-based network of clinical laboratories Ruzante, Juliana M. Olin, Katherine Munoz, Breda Nawrocki, Jeff Selvarangan, Rangaraj Meyers, Lindsay PLoS One Research Article Acute gastrointestinal infection (AGI) represents a significant public health concern. To control and treat AGI, it is critical to quickly and accurately identify its causes. The use of novel multiplex molecular assays for pathogen detection and identification provides a unique opportunity to improve pathogen detection, and better understand risk factors and burden associated with AGI in the community. In this study, de-identified results from BioFire(®) FilmArray(®) Gastrointestinal (GI) Panel were obtained from January 01, 2016 to October 31, 2018 through BioFire(®) Syndromic Trends (Trend), a cloud database. Data was analyzed to describe the occurrence of pathogens causing AGI across United States sites and the relative rankings of pathogens monitored by FoodNet, a CDC surveillance system were compared. During the period of the study, the number of tests performed increased 10-fold and overall, 42.6% were positive for one or more pathogens. Seventy percent of the detections were bacteria, 25% viruses, and 4% parasites. Clostridium difficile, enteropathogenic Escherichia coli (EPEC) and norovirus were the most frequently detected pathogens. Seasonality was observed for several pathogens including astrovirus, rotavirus, and norovirus, EPEC, and Campylobacter. The co-detection rate was 10.2%. Enterotoxigenic E. coli (ETEC), Plesiomonas shigelloides, enteroaggregative E. coli (EAEC), and Entamoeba histolytica were detected with another pathogen over 60% of the time, while less than 30% of C. difficile and Cyclospora cayetanensis were detected with another pathogen. Positive correlations among co-detections were found between Shigella/Enteroinvasive E. coli with E. histolytica, and ETEC with EAEC. Overall, the relative ranking of detections for the eight GI pathogens monitored by FoodNet and BioFire Trend were similar for five of them. AGI data from BioFire Trend is available in near real-time and represents a rich data source for the study of disease burden and GI pathogen circulation in the community, especially for those pathogens not often targeted by surveillance. Public Library of Science 2021-04-30 /pmc/articles/PMC8087049/ /pubmed/33930062 http://dx.doi.org/10.1371/journal.pone.0250767 Text en © 2021 Ruzante et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ruzante, Juliana M.
Olin, Katherine
Munoz, Breda
Nawrocki, Jeff
Selvarangan, Rangaraj
Meyers, Lindsay
Real-time gastrointestinal infection surveillance through a cloud-based network of clinical laboratories
title Real-time gastrointestinal infection surveillance through a cloud-based network of clinical laboratories
title_full Real-time gastrointestinal infection surveillance through a cloud-based network of clinical laboratories
title_fullStr Real-time gastrointestinal infection surveillance through a cloud-based network of clinical laboratories
title_full_unstemmed Real-time gastrointestinal infection surveillance through a cloud-based network of clinical laboratories
title_short Real-time gastrointestinal infection surveillance through a cloud-based network of clinical laboratories
title_sort real-time gastrointestinal infection surveillance through a cloud-based network of clinical laboratories
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087049/
https://www.ncbi.nlm.nih.gov/pubmed/33930062
http://dx.doi.org/10.1371/journal.pone.0250767
work_keys_str_mv AT ruzantejulianam realtimegastrointestinalinfectionsurveillancethroughacloudbasednetworkofclinicallaboratories
AT olinkatherine realtimegastrointestinalinfectionsurveillancethroughacloudbasednetworkofclinicallaboratories
AT munozbreda realtimegastrointestinalinfectionsurveillancethroughacloudbasednetworkofclinicallaboratories
AT nawrockijeff realtimegastrointestinalinfectionsurveillancethroughacloudbasednetworkofclinicallaboratories
AT selvaranganrangaraj realtimegastrointestinalinfectionsurveillancethroughacloudbasednetworkofclinicallaboratories
AT meyerslindsay realtimegastrointestinalinfectionsurveillancethroughacloudbasednetworkofclinicallaboratories