Event-based surveillance (EBS) systems have been implemented globally to support early warning surveillance across human, animal, and environmental health in diverse settings, including at the community level, within health facilities, at border points of entry, and through media monitoring of internet-based sources. EBS systems should be evaluated periodically to ensure that they meet the objectives related to the early detection of health threats and to identify areas for improvement in the quality, efficiency, and usefulness of the systems. However, to date, there has been no comprehensive framework to guide the monitoring and evaluation of EBS systems; this absence of standardisation has hindered progress in the field. The Africa Centres for Disease Control and Prevention and US Centers for Disease Control and Prevention have collaborated to develop an EBS monitoring and evaluation indicator framework, adaptable to specific country contexts, that uses measures relating to input, activity, output, outcome, and impact to map the processes and expected results of EBS systems. Through the implementation and continued refinement of these indicators, countries can ensure the early detection of health threats and improve their ability to measure and describe the impacts of EBS systems, thus filling the current evidence gap regarding their effectiveness.

BACKGROUND: Flu Near You (FNY) is an online participatory syndromic surveillance system that collects health related information. In this manuscript, we summarized the health-care seeking behavior of FNY participants who reported influenza-like illness (ILI) symptoms. METHODS: We applied inverse probability weighting to calculate age-adjusted estimates of the percentage of FNY participants in the United States who sought health care for ILI symptoms during the 2015-16 through 2018-19 influenza season and compared seasonal trends across different demographic and regional subgroups, including age group, sex, census region, and place of care using adjusted Chi-square tests. RESULTS: The overall age-adjusted percentage of FNY participants who sought health care for ILI symptoms varied by season and ranged from 22.8% to 35.6%. Across all seasons, health care seeking was highest for the <18 and 65+ age groups, females had a greater percentage compared with males, and the South census region had the largest percentage while the West census region had the smallest percentage. CONCLUSIONS: The percentage of FNY participants who sought health care for ILI symptoms varied by season, geographical region, age group, and sex. FNY compliments existing surveillance systems and informs estimates of influenza-associated illness by adding important real-time insights into health-care seeking behavior.