Real Time Monitoring of Respiratory Viral Infections in Cohort Studies Using a Smartphone App

Abstract

Background and Objectives Cohort studies investigating respiratory disease pathogenesis aim to pair mechanistic investigations with longitudinal virus detection but are limited by the burden of methods tracking illness over time. In this study, we explored the utility of a smartphone app to robustly identify symptomatic respiratory illnesses, while reducing burden and facilitating real-time data collection and adherence monitoring. Methods The AERIAL TempTracker smartphone app was assessed in the AERIAL and COCOON birth cohort studies. Participants recorded daily temperatures and associated symptoms/medications in TempTracker for 6 months, with daily use adherence measured over this period. Regular participant feedback was collected at quarterly study visits. Symptomatic respiratory illnesses meeting study criteria prompted an automated app alert and collection of a nose/throat swab for testing of eight respiratory viruses. Results In total, 32,764 daily TempTracker entries from 348 AERIAL participants and 30,542 entries from 361 COCOON participants were recorded. This corresponded to an adherence median of 67.0% (range 1.9$[ndash]100%) and 55.4% (range 1.1–100%) of each participants study period, respectively. Feedback was positive, with 75.5% of responding families reporting no barriers to use. A total of 648 symptomatic respiratory illness events from 249/709 participants were identified with significant variability between individuals in the frequency (0–16 events per participant), duration (1–13 days), and virus detected (rhinovirus in 42.7%). Conclusions A smartphone app provides a reliable method to capture the longitudinal virus data in cohort studies which facilitates the understanding of early life infections in chronic respiratory disease development.