Background: Influenza surveillance provides national indicators of influenza season severity in the United States. Given the variability in influenza activity from season to season and geographically, real-time state-specific estimates of seasonal influenza severity may help states tailor their public health communications and resource allocation during influenza seasons. Nationally, the 201718 season was categorized as high severity; we developed disease severity thresholds to characterize the severity of the influenza season in Utah.
Methods: We applied the Moving Epidemic Method for a rapid mid-season assessment of weekly influenza season severity to 3 priority Utah indicators with at least 5 seasons of data: percent of outpatient visits for influenza-like illness, state-wide rate of reported influenza-associated hospitalizations, and percent positive influenza tests from the National Respiratory and Enteric Virus Surveillance System. This method calculates intensity thresholds (ITs) by determining the geometric mean and standard deviation of the 30 highest weekly values, distributed evenly across included seasons, and calculating one-sided confidence intervals. We established 3 ITs that corresponded to a 50% (IT50), 10% (IT90) and 2% (IT98) chance of exceedance during a given influenza season. For each surveillance indicator, we graphed the weekly data against the calculated severity thresholds.
Results: We preliminarily categorized the 201718 season as well as the 2014-15 season, as high severity because ≥2 priority indicators peaked above their IT90 (Figures 1-3). All other seasons in Utah (beginning in 201213) were categorized as moderate severity because ≥2 indicators peaked between IT50 and IT90.
Conclusion: The Utah seasonal severity assessment matched the national level assessment for all seasons. Understanding state-specific severity assessments during and after a season may help to inform states influenza preparedness activities.
M. M. Hughes,
G. M. Reed, None
M. Spencer, None
S. Garg, None
A. Dunn, None
M. Biggerstaff, None