Author: Lindsay Meyers; Christine C. Ginocchio; Aimie N. Faucett; Frederick S. Nolte; Per H. Gesteland; Amy Leber; Diane Janowiak; Virginia Donovan; Jennifer Dien Bard; Silvia Spitzer; Kathleen A. Stellrecht; Hossein Salimnia; Rangaraj Selvarangan; Stefan Juretschko; Judy A. Daly; Jeremy C. Wallentine; Kristy Lindsey; Franklin Moore; Sharon L. Reed; Maria Aguero-Rosenfeld; 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
Title: Automated collection of pathogen-specific diagnostic data for real-time syndromic epidemiological studies Document date: 2017_7_31
ID: iisqysqm_5
Snippet: With more than 344,000 patient results for the FilmArray RP test alone, the Trend database has 125 many of the properties associated with "big data" as it applies to infectious disease [57] . After describing how the dataset can be cleaned of non-patient tests, we make some observations on the seasonality of the different respiratory pathogens and we apply the ecological concept of "species diversity" [58] to observe a correlation between the abu.....
Document: With more than 344,000 patient results for the FilmArray RP test alone, the Trend database has 125 many of the properties associated with "big data" as it applies to infectious disease [57] . After describing how the dataset can be cleaned of non-patient tests, we make some observations on the seasonality of the different respiratory pathogens and we apply the ecological concept of "species diversity" [58] to observe a correlation between the abundance of each pathogen and the rate at which co-detections (more than one positive result per test) occur. 130 All rights reserved. No reuse allowed without permission.
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