Improving Accuracy of Influenza-Associated Hospitalization Rate Estimates - Volume 21, Number 9—September 2015 - Emerging Infectious Disease journal - CDC
Volume 21, Number 9—September 2015
Emerging Infections Program
Emerging Infections Program
Improving Accuracy of Influenza-Associated Hospitalization Rate Estimates
In the United States, surveillance for influenza-associated hospitalizations relies on laboratory-confirmed diagnostic testing (1–3). Influenza testing modalities have expanded from traditional viral culture to include rapid influenza diagnostic tests (RIDTs) and molecular assays, such as reverse transcription PCR (RT-PCR) (4,5). RIDTs are point-of-care tests that provide results within 30 minutes; however, with reported sensitivities of 10%–80%, negative test results can be unreliable (6–9). RT-PCR exceeds viral culture in sensitivity for detecting influenza, but its widespread use is limited by cost and complexity of the assay (10,11).
Researchers have examined rates of influenza-associated hospitalization during different influenza seasons (1,2,12,13). However, comparing rates between seasons can be inaccurate without accounting for changes in the sensitivity of diagnostic testing used. In particular, after the 2009 influenza A(H1N1) pandemic, hospitals and state public health laboratories expanded diagnostic capabilities with high-sensitivity molecular assays to better detect influenza viruses and other respiratory pathogens (5). Particularly for nationally based surveillance, the use of different testing platforms by health care facilities and the variability in sensitivity of these diagnostic tests could lead to underestimation of rates of influenza-associated hospitalization and limit comparisons of severity across influenza seasons (3,4,6,7).
Dr. Millman is a physician and an Epidemic Intelligence Service Officer assigned to the Influenza Division, CDC. His research interests include influenza, emerging infections surveillance, and advanced molecular diagnostics.
We thank the following persons for their contributions at CDC and the FluSurv-NET sites: Alejandro Perez, Michelle Leon, Hallie Randel, Maria Rosales, Darcy Fazio, John Palumbo, Kimberly Yousey-Hindes, Olivia Almendares, Delmar Little, Kyle Openo, May Monroe; Dave Boxurd, Craig Morin, Sara Vetter, Minnesota Team Flu, Meghan Fuschino, Nancy Spina, Kirsten St. George, Gary Hollick, Maria Gaitan; Matthew Laidler, Patricia Newman, Katie Dyer, and Karen Leib.
FluSurv-NET is a collaboration of state health departments, academic institutions, and local partners and is funded by CDC. This publication was supported in part by cooperative agreement nos. CDC-RFA-CK12-1202 and 5U38HM000414.
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Suggested citation for this article: Millman AJ, Reed C, Daily Kirley P, Aragon D, Meek J, Farley MM, et al. Improving accuracy of influenza-associated hospitalization rate estimates. Emerg Infect Dis. 2015 Aug [date cited]. http://dx.doi.org/10.3201/eid2109.141665