Automated Real-Time Collection of Pathogen-Specific Diagnostic Data: Syndromic Infectious Disease Epidemiology (Preprint)

• DOI: 10.2196/preprints.9876
• Publication Date: 2018-03-09T15:44:56Z
• Authors: Lindsay Meyers; Christine C Ginoc...; Aimie N Faucett; Frederick S Nolte; Per H Gesteland; Amy Leber; Diane Janowiak; Virginia Donovan; Jennifer Dien Bard; Silvia Spitzer; Kathleen A Stellr...; Hossein Salimnia; Rangaraj Selvarangan; Stefan Juretschko; Judy A Daly; Jeremy C Wallentine; Kristy Lindsey; Franklin Moore; Sharon L Reed; Maria Aguero-Rose...; Paul D Fey; Gregory A Storch; Steve J Melnick; Christine C Robinson; Jennifer F Meredith; Camille V Cook; Robert K Nelson; Jay D Jones; Samuel V Scarpino; Benjamin M Althouse; Kirk M Ririe; Bradley A Malin; Mark A Poritz
• Keywords: Preparedness

<sec> <title>BACKGROUND</title> Health care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness response. Early detection outbreaks is improved by systems that are comprehensive specific with respect to the pathogen but rapid in reporting data. It has proven difficult implement these requirements a large scale while maintaining patient privacy. </sec> <title>OBJECTIVE</title> The aim this study was demonstrate automated export, aggregation, analysis disease diagnostic test results from clinical laboratories across United States manner protects confidentiality. We hypothesized such system could aid seasonal occurrence respiratory pathogens may have advantages regard scope ease compared existing surveillance systems. <title>METHODS</title> describe system, BioFire Syndromic Trends, syndrome-based pathogen-specific. Deidentified FilmArray multiplex molecular sent directly cloud database. Summaries data displayed near real time Trends website. studied dataset prevalence, seasonality, coinfections 20 detected over 362,000 samples acquired as standard-of-care testing last 4 years States. <title>RESULTS</title> majority show influenza-like rhinovirus fall spring peaks, adenovirus bacterial constant year. can also be considered an ecological framework; viruses bacteria parasites host (the human patient). Interestingly, rate codetections, average 7.94% (28,741/362,101), matches predictions based relative abundance organisms present. <title>CONCLUSIONS</title> preserves privacy removing or obfuscating identifiers still collecting much useful information about viral they harbor. Test uploaded database within few hours completion delays up 10 days other diagnostic-based This work shows barriers establishing epidemiology no longer scientific technical rather administrative, involving questions ownership. demonstrated here overcome. first look at resulting stream suggests will able provide high-resolution circulating new outbreaks.