Analysis of ILI-Related Changes in Fitbit Data
Before the analysis, wearable sensor data were assessed for quality and completeness in 3 steps. First, minute-level streams were assessed for their physiological plausibility. Second, participant days (day-level aggregates of minute-level streams) were assessed for wear time and data availability, excluding missing minutes with null or physiologically implausible values from wear-time estimates. Third, the participants’ Fitbit data density was assessed, excluding days with insufficient wear time or unavailable data from consideration. Only the participants who met the data density criteria were eligible for inclusion in the analyses of the relevant data stream.In the first step, physiologically implausible values were removed. Minutes with >400 steps were removed from the steps stream. Minutes with <30 beats per minute (bpm) or >220 bpm were removed from the HR stream. In the second step, HR data were considered valid on days with available Fitbit-estimated daily RHR and at least 10 hours of HR wear time (the sum of the minutes with nonzero, nonmissing HR values), consistent with the standard wear-time criteria [Before enforcing the data quality criteria, there were 2848 potential participants with at least 1 day of Fitbit data. In total, 14.5% (413/2848) of participants did not meet the data density criteria for any of the 3 channels; the remaining 85.5% (2435/2848) of participants comprised the final ILI analysis population. Overall, 2329 (95.6%) participants had 297,239 participant-days with valid Fitbit steps data (92.5% of 321,480 possible days [{1400 FluStudy2020 participants with valid steps data × 150 study days} + {929 HTRI participants × 120 study days}]); 2316 (95.1%) participants had 290,116 participant-days with valid Fitbit sleep data (90.7% of 319,740 possible days); and 2206 (90.6%) participants had 280,501 participant-days with valid Fitbit HR data (92.2% of 302,790 possible days).Five day-level aggregate features hypothesized to be relevant to ILI were computed from the minute-level Fitbit data: total daily steps (ie, the total number of steps taken in a day), the proportion of the day that the participant spent being physically active (≥50 steps per minute), daily RHR (ie, Fitbit-estimated HR while at rest), total sleep duration (ie, Fitbit-estimated total length of time the participant spent sleeping), and sleep efficiency (ie, Fitbit-estimated proportion of the main sleep interval spent asleep [minutes asleep / total time spent in bed − minutes spent in bed after waking up], which range from 0 to 100). In the time to return to baseline (TTRB) analysis, day-to-day changes in RHR (RHR δ) were also included to reduce the impact of autocorrelation of RHR measurements. The day-level features were winsorized, clipping extreme values to the 99.95th percentile value (taken across all participant-days).