@Article{info:doi/10.2196/20741,
author="Jonker, Marcel
and de Bekker-Grob, Esther
and Veldwijk, Jorien
and Goossens, Lucas
and Bour, Sterre
and Rutten-Van M{\"o}lken, Maureen",
title="COVID-19 Contact Tracing Apps: Predicted Uptake in the Netherlands Based on a Discrete Choice Experiment",
journal="JMIR Mhealth Uhealth",
year="2020",
month="Oct",
day="9",
volume="8",
number="10",
pages="e20741",
keywords="COVID-19; discrete choice experiment; contact tracing; participatory epidemiology; participatory surveillance; app; uptake; prediction; smartphone; transmission; privacy; mobile phone",
abstract="Background: Smartphone-based contact tracing apps can contribute to reducing COVID-19 transmission rates and thereby support countries emerging from lockdowns as restrictions are gradually eased. Objective: The primary objective of our study is to determine the potential uptake of a contact tracing app in the Dutch population, depending on the characteristics of the app. Methods: A discrete choice experiment was conducted in a nationally representative sample of 900 Dutch respondents. Simulated maximum likelihood methods were used to estimate population average and individual-level preferences using a mixed logit model specification. Individual-level uptake probabilities were calculated based on the individual-level preference estimates and subsequently aggregated into the sample as well as subgroup-specific contact tracing app adoption rates. Results: The predicted app adoption rates ranged from 59.3{\%} to 65.7{\%} for the worst and best possible contact tracing app, respectively. The most realistic contact tracing app had a predicted adoption of 64.1{\%}. The predicted adoption rates strongly varied by age group. For example, the adoption rates of the most realistic app ranged from 45.6{\%} to 79.4{\%} for people in the oldest and youngest age groups (ie, ≥75 years vs 15-34 years), respectively. Educational attainment, the presence of serious underlying health conditions, and the respondents' stance on COVID-19 infection risks were also correlated with the predicted adoption rates but to a lesser extent. Conclusions: A secure and privacy-respecting contact tracing app with the most realistic characteristics can obtain an adoption rate as high as 64{\%} in the Netherlands. This exceeds the target uptake of 60{\%} that has been formulated by the Dutch government. The main challenge will be to increase the uptake among older adults, who are least inclined to install and use a COVID-19 contact tracing app. ",
issn="2291-5222",
doi="10.2196/20741",
url="https://mhealth.jmir.org/2020/10/e20741",
url="https://doi.org/10.2196/20741",
url="http://www.ncbi.nlm.nih.gov/pubmed/32795998"
}