JMIR Publications

ABSTRACT

Background:

Effective surveillance of seasonal influenza is crucial to understanding disease burden and impact. Traditional surveillance accounts for those who interact with the healthcare system. Understanding who is being captured by current surveillance methods can help further knowledge around influenza and identify areas of improvement.

Objective:

To examine influenza testing amongst a United States representative population to better understand who is testing over three seasons.

Methods:

Outbreaks Near Me is a participatory surveillance system that, in partnership with SurveyMonkey, conducted a weekly cross-sectional survey. Survey data from three influenza seasons was used, (2021-2022 flu season N = 335,964; 2022-2023 season N = 334,584; 2023-2024 season N = 267,940) with analysis conducted to examine influenza testing among different demographic groups. Descriptive proportions applying survey weights targeting U.S. census targets were produced to understand which demographics were testing for influenza. A weighted multivariate logistic regression was conducted for influenza testing by income, adjusting for other demographics and COVID-19 testing.

Results:

Generally, low levels of influenza testing were reported. Across all influenza seasons, those who had lower income tested for influenza at higher proportions. Lower household annual income was associated with higher odds of testing for influenza, while higher incomes were less likely to have been tested for influenza.

Conclusions:

: Individuals who fall within lower income brackets tested at higher proportions and had an increased likelihood of having tested for influenza in the past 30 days than their higher income counterparts. These trends suggest that populations that may historically have more barriers to care, have access to and are using influenza tests.