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High-throughput Detection Method for Influenza Virus

High-throughput Detection Method for Influenza Virus

Published on: February 4, 2012

County-Level Influenza-Attributable Emergency Department Visits and Their Spatial Correlates in the United States:

Xucheng Fred Huang¹, Joshua L Warren², Shuqi Lin²

¹Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States.

JMIR Public Health and Surveillance

|December 30, 2025

Abstract

Background:

The burden of seasonal influenza on emergency department (ED) visits is poorly quantified due to case ascertainment and data availability challenges. This study estimates county-level respiratory ED visits attributable to influenza using time-series models and examines spatial heterogeneity in county-level burden in 3 states.

Objective:

This study aimed to estimate the county-level respiratory ED visits attributable to influenza using time-series models and examine spatial heterogeneity in county-level burden in 3 states.

Methods:

We used daily hospital discharge records to measure community-level influenza activity in California (2005-2018), Georgia (2010-2018), and New York (2005-2018). County-level respiratory ED visit rates attributable to influenza were estimated by quasi-Poisson time-series models, adjusting for temporal trends and environmental factors. Bayesian spatial models were used to assess associations with county-level socioeconomic status, environmental exposures, and chronic health condition prevalence.

Results:

Influenza-attributable respiratory ED visit rates per 100,000 population were 226 (95% CI 206-246) in New York, 232 (95% CI 206-259) in California, and 547 (95% CI 506-589) in Georgia. A 10% increase in county-level poverty and uninsured rates was associated with higher influenza burden, increasing influenza-attributable respiratory ED visit rates by 160 (95% credible interval [CrI] 127-196) and 217 (95% CrI 168-265), respectively. Long-term PM_2.5 (fine particulate matter ≤2.5 µm), humidity, and temperature also exhibited positive associations. Chronic conditions also increased ED visit rates by 1476/100,000 (95% CrI 1167-1778), 588/100,000 (95% CrI 400-747), and 488/100,000 (95% CrI 402-574) per 10% increase in stroke, chronic obstructive pulmonary disease, and diabetes prevalence, respectively. These associations weakened after adjusting for socioeconomic status.

Conclusions:

Influenza-attributable respiratory ED visit rates exhibit significant spatial heterogeneity that is associated with county-level socioeconomic factors, environmental exposures, and chronic disease prevalence.

Keywords:

air pollution bayesian statistics environmental disparities environmental epidemiology infectious diseases influenza diseases spatial statistics

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