TY - JOUR
T1 - Real time monitoring of respiratory viral infections in cohort studies using a smartphone app
AU - Hancock, David G
AU - Kicic-Starcevich, Elizabeth
AU - Sondag, Thijs
AU - Rivers, Rael
AU - McGee, Kate
AU - Karpievitch, Yuliya V
AU - D'Vaz, Nina
AU - Agudelo-Romero, Patricia
AU - Caparros-Martin, Jose A
AU - Iosifidis, Thomas
AU - Kicic, Anthony
AU - Stick, Stephen M
N1 - © 2024 The Author(s).
PY - 2024/10/18
Y1 - 2024/10/18
N2 - 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 purpose-built AERIAL TempTracker smartphone app to assess real-time data collection and adherence monitoring and overall burden to participants, while identifying symptomatic respiratory illnesses in two birth cohort studies. We observed strong adherence with daily app usage over the six-month study period, with positive feedback from participant families. A total of 648 symptomatic respiratory illness events were identified with significant variability between individuals in the frequency, duration, and virus detected. Collectively, our data show that 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.
AB - 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 purpose-built AERIAL TempTracker smartphone app to assess real-time data collection and adherence monitoring and overall burden to participants, while identifying symptomatic respiratory illnesses in two birth cohort studies. We observed strong adherence with daily app usage over the six-month study period, with positive feedback from participant families. A total of 648 symptomatic respiratory illness events were identified with significant variability between individuals in the frequency, duration, and virus detected. Collectively, our data show that 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.
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001319889900001
U2 - 10.1016/j.isci.2024.110912
DO - 10.1016/j.isci.2024.110912
M3 - Article
C2 - 39346675
SN - 2589-0042
VL - 27
JO - Iscience
JF - Iscience
IS - 10
M1 - 110912
ER -