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Am J Epidemiol . A Time-Series Approach for Estimating Emergency Department Visits Attributable to Seasonal Influenza: Results from Six U.S. Cities,

tetano

Editor, Senior Moderator
Am J Epidemiol


. 2025 Mar 5:kwaf045.
doi: 10.1093/aje/kwaf045. Online ahead of print. A Time-Series Approach for Estimating Emergency Department Visits Attributable to Seasonal Influenza: Results from Six U.S. Cities, 2005-06 to 2016-17 Seasons

Xucheng Fred Huang[SUP] 1 [/SUP], A Danielle Iuliano[SUP] 2 [/SUP], Stefanie Ebelt[SUP] 1 [/SUP], Carrie Reed[SUP] 2 [/SUP], Howard H Chang[SUP] 1 3 [/SUP]



Affiliations
Abstract

Emergency department (ED) visits during influenza seasons represent a critical yet less examined indicator of the acute burden of influenza. This study investigates the burden of influenza-associated ED visits in six U.S. cities during influenza seasons from 2005-06 to 2016-17. Using a time-series design, we estimated associations between daily ED visits and weekly influenza activity data from the Influenza Hospitalization Surveillance Network (FluSurv-NET). A counterfactual approach was then used to calculate attributable expected ED. Highest influenza-associated rates were observed among the youngest (0-4 years) and oldest (65+ years) age groups. Combining estimates across seasons, the influenza-associated ED visit rate for respiratory diseases was almost six times larger compared to the subset of ED visits that resulted in hospitalization: 364 per 100,000 population (95% CI: 294-435) for total ED visits versus 58 per 100,000 population (95% CI: 45-71) for hospitalization. This difference was particularly large for the 0-4 year age group: 911 per 100,000 population (95% CI: 558-1,263) for total ED visits versus 43 per 100,000 population (95% CI: 15-71) for hospitalization. This study highlights the substantial burden of influenza on emergency healthcare services and the importance of integrating such data into public health planning and influenza management strategies.

Keywords: Desease Burden; Emergencey Department Visits; FluSurv-NET; Influenza; Respiratory Diseases; Statistical Modeling; Time-series analysis.

 
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