Gertz Autumn, Sopko Juliana B, Remmel Christopher, Rader Benjamin, Brownstein John S
Boston Children's Hospital, 300 Longwood Ave, Boston, MA, 02215, United States, 1 6173556000.
Harvard Medical School, Boston, MA, United States.
JMIR Public Health Surveill. 2025 Aug 26;11:e76459. doi: 10.2196/76459.
Effective surveillance of seasonal influenza is crucial to understanding disease burden and impact. Traditional surveillance accounts for those who interact with the health care system, including those who are testing for diseases like influenza. However, care seeking and testing are not as common with influenza and can lead to bias. Better understanding who is being captured by current surveillance methods can help further knowledge around influenza and identify areas of improvement in surveillance, disease mitigation, and intervention efforts.
This study aimed to examine who is testing for influenza amongst a United States representative survey population, across three seasons influenza seasons spanning 2021 to 2024.
Outbreaks near me (ONM) is a participatory surveillance system that, in partnership with SurveyMonkey, conducted a web-based, weekly cross-sectional survey. ONM Survey data from three influenza seasons was used in this study: 2021-2022, 2022-2023, and 2023-2024. Tested for influenza was defined as a "yes" response to "In the past 30 days, have you been tested for influenza (flu)?" Descriptive proportions applying survey weights reflecting US census targets were produced to understand which demographic groups were testing for influenza. A weighted multivariate logistic regression was conducted for influenza testing by income, adjusting for other demographics and COVID-19 testing. Descriptive proportions and multivariate regressions were conducted by influenza season.
In total, 940,172 responses were collected, with similar amounts in 2021-2022 (n=335,964) and 2022-2023 (n=334,584), and slightly less in 2023-2024 (n=269,624). Generally, low levels of influenza testing were reported in each season at 4.2%, 9.1%, and 8.9%, respectively. Weighted proportions of those who tested for influenza only and no other diseases (like COVID-19) were even lower (0.4%, 971/335,964; 1.5%, 4,382/334,584; and 2.0%, 4579/269,624; respectively). Broadly, those who had lower income tested for influenza at progressively higher proportions. A similar trend was observed season to season with education level as well. Across the 3 observed influenza seasons, lower household annual income (under US $15,000) was associated with higher odds of testing for influenza (2021-2022: adjusted odds ratio [AOR] 1.41, 95% CI 1.34-1.48; 2022-2023: AOR 1.42, 95% CI 1.35-1.49; 2023-2024: AOR 1.25, 95% CI 1.18-1.34), while those with higher incomes (over US $150,000) were less likely to have been tested for influenza (2021-2022: AOR 0.64, 95% CI 0.55-0.86; 2022-2023: AOR 0.82, 95% CI 0.73-0.91; 2023-2024: AOR 0.66, 95% CI 0.56-0.76).
Within this study population, individuals who fall within lower-income brackets tested for influenza more than their higher-income counterparts. In all 3 seasons spanning 2021-2024, lower income was associated with higher proportions of influenza testing and an increased likelihood of having tested for influenza in the past 30 days. These trends suggest that populations that may experience more barriers to care are not only accessing influenza testing but doing so differently than groups that historically access care.
有效的季节性流感监测对于了解疾病负担和影响至关重要。传统监测涵盖了那些与医疗保健系统有接触的人,包括那些接受流感等疾病检测的人。然而,因流感而寻求医疗和进行检测的情况并不常见,且可能导致偏差。更好地了解当前监测方法所涵盖的人群,有助于进一步认识流感,并确定监测、疾病缓解和干预措施方面的改进领域。
本研究旨在调查在2021年至2024年的三个流感季节中,美国代表性调查人群中进行流感检测的是哪些人。
“我附近的疫情”(ONM)是一个参与性监测系统,它与SurveyMonkey合作,开展了一项基于网络的每周横断面调查。本研究使用了来自三个流感季节的ONM调查数据:2021 - 2022年、2022 - 2023年和2023 - 2024年。接受流感检测被定义为对“在过去30天内,你是否接受过流感检测?”的回答为“是”。通过应用反映美国人口普查目标的调查权重得出描述性比例,以了解哪些人口群体在进行流感检测。针对收入情况对流感检测进行加权多变量逻辑回归分析,并对其他人口统计学特征和新冠病毒检测进行调整。描述性比例和多变量回归分析按流感季节进行。
总共收集了940,172份回复,2021 - 2022年(n = 335,964)和2022 - 2023年(n = 334,584)的数量相似,2023 - 2024年(n = 269,624)略少。总体而言,每个季节报告的流感检测水平较低,分别为4.2%、9.1%和8.9%。仅进行流感检测而未进行其他疾病(如新冠病毒)检测的加权比例甚至更低(分别为0.4%,971/335,964;1.5%,4,382/334,584;和2.0%,4579/269,624)。总体而言,收入较低的人群进行流感检测的比例逐渐升高。在教育水平方面,各季节也观察到类似趋势。在观察到的三个流感季节中,家庭年收入较低(低于15,000美元)与进行流感检测的几率较高相关(2021 - 2022年:调整后的优势比[AOR]为1.41,95%置信区间为1.34 - 1.48;2022 - 2023年:AOR为1.42,95%置信区间为1.35 - 1.49;2023 - 2024年:AOR为1.25,95%置信区间为1.18 - 1.34),而收入较高(超过150,000美元)的人群进行流感检测的可能性较小(2021 - 2022年:AOR为0.64,95%置信区间为0.55 - 0.86;2022 - 2023年:AOR为0.82,95%置信区间为0.73 - 0.91;2023 - 2024年:AOR为0.66,95%置信区间为0.56 - 0.76)。
在本研究人群中,低收入人群进行流感检测的次数多于高收入人群。在2021 - 2024年的所有三个季节中,低收入与较高比例的流感检测以及在过去30天内进行流感检测的可能性增加相关。这些趋势表明,可能在获得医疗服务方面面临更多障碍的人群不仅在进行流感检测,而且其检测方式与历来获得医疗服务的群体不同。