Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study

• Published in: Journal of medical Internet research Vol. 25; no. 1; p. e41050
• Main Authors: Hunter, Victoria, Shapiro, Allison, Chawla, Devika, Drawnel, Faye, Ramirez, Ernesto, Phillips, Elizabeth, Tadesse-Bell, Sara, Foschini, Luca, Ukachukwu, Vincent
• Format: Journal Article
• Language: English
• Published: Canada Gunther Eysenbach MD MPH, Associate Professor 23.03.2023; JMIR Publications
• Subjects: Clinical outcomes; Cohort analysis; Cohort Studies; Cost of Illness; Datasets; Enrollments; Fever; Health behavior; Health care; Heart rate; Help seeking behavior; Hospitalization; Humans; Illnesses; Infections; Influenza; Influenza, Human - diagnosis; Influenza, Human - epidemiology; Morbidity; Original Paper; Patient Reported Outcome Measures; Physiology; Respiratory diseases; Resting; Self report; Sensors; Sleep; Symptoms; Tests; Wearable Electronic Devices; United States > US; influenza; wearable sensor; influenza-like illness; person-generated health care data
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/41050

The burden of influenza-like illness (ILI) is typically estimated via hospitalizations and deaths. However, ILI-associated morbidity that does not require hospitalization remains poorly characterized. The main objective of this study was to characterize ILI burden using commercial wearable sensor data and investigate the extent to which these data correlate with self-reported illness severity and duration. Furthermore, we aimed to determine whether ILI-associated changes in wearable sensor data differed between care-seeking and non-care-seeking populations as well as between those with confirmed influenza infection and those with ILI symptoms only. This study comprised participants enrolled in either the FluStudy2020 or the Home Testing of Respiratory Illness (HTRI) study; both studies were similar in design and conducted between December 2019 and October 2020 in the United States. The participants self-reported ILI-related symptoms and health care-seeking behaviors via daily, biweekly, and monthly surveys. Wearable sensor data were recorded for 120 and 150 days for FluStudy2020 and HTRI, respectively. The following features were assessed: total daily steps, active time (time spent with >50 steps per minute), sleep duration, sleep efficiency, and resting heart rate. ILI-related changes in wearable sensor data were compared between the participants who sought health care and those who did not and between the participants who tested positive for influenza and those with symptoms only. Correlative analyses were performed between wearable sensor data and patient-reported outcomes. After combining the FluStudy2020 and HTRI data sets, the final ILI population comprised 2435 participants. Compared with healthy days (baseline), the participants with ILI exhibited significantly reduced total daily steps, active time, and sleep efficiency as well as increased sleep duration and resting heart rate. Deviations from baseline typically began before symptom onset and were greater in the participants who sought health care than in those who did not and greater in the participants who tested positive for influenza than in those with symptoms only. During an ILI event, changes in wearable sensor data consistently varied with those in patient-reported outcomes. Our results underscore the potential of wearable sensors to discriminate not only between individuals with and without influenza infections but also between care-seeking and non-care-seeking populations, which may have future application in health care resource planning. Clinicaltrials.gov NCT04245800; https://clinicaltrials.gov/ct2/show/NCT04245800.