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Published on: January 26, 2019
Evaluating Analytic Approaches to Determining Respiratory Syncytial Virus Seasonality-United States, 2014-2024
Sophia Chkonia1,2, Sarah Hamid1, Erica Billig Rose1
1Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, USA.
Background:
Respiratory syncytial virus (RSV) is a major cause of hospitalizations among infants and older adults in the United States. Determining RSV seasonality, which varies geographically, is essential to the timely administration of prevention products. We described how a laboratory percent positivity threshold (3% threshold) performs compared to the retrospective slope 10 (RS10) and 10-fold baseline (10FB) methods in defining RSV epidemics across regions.
Methods:
We analyzed RSV laboratory testing data submitted by consistent reporters to the National Respiratory and Enteric Virus Surveillance System during July 2014-June 2024. We compared the timing of epidemics, season duration, and percent of annual detections captured within the epidemic period determined from the 3% threshold, RS10, and 10FB methods.
Results:
The epidemic onset weeks determined by the 3% threshold were typically later than those identified by RS10 and varied by region when compared to 10FB. Epidemic duration was shortest with the 3% threshold and longest with RS10. RS10 captured the highest percentage of detections and varied least annually. The 3% threshold and 10FB demonstrated similar percentages of detections before the COVID-19 pandemic, but detections decreased with 10FB postpandemic.
Conclusions:
RS10 demonstrated high coverage of annual RSV detections and identified earlier onsets but can only be applied retrospectively. 10FB did not consistently identify season onset earlier across regions. Similar evaluation results across the three methods suggest that the 3% threshold was not impacted in determining RSV seasonality postpandemic and is a preferred US method due to its simplicity and application in near real-time.
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