COVID-19 Contact Tracing Apps: Predicted Uptake in the Netherlands Based on a Discrete Choice Experiment

• Published in: JMIR mHealth and uHealth Vol. 8; no. 10; p. e20741
• Main Authors: Jonker, Marcel, de Bekker-Grob, Esther, Veldwijk, Jorien, Goossens, Lucas, Bour, Sterre, Rutten-Van Mölken, Maureen
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 09-10-2020
• Subjects: Adolescent; Adult; Aged; Choice Behavior; Contact tracing; Contact Tracing - methods; Coronavirus Infections - epidemiology; Coronaviruses; COVID-19; Data collection; Disease transmission; Female; Humans; Male; Middle Aged; Mobile Applications - statistics & numerical data; Monetary incentives; Netherlands - epidemiology; Original Paper; Pandemics; Pneumonia, Viral - epidemiology; Population; Preferences; Privacy; Public health; Quarantine; Smartphones; Social distancing; Software; Young Adult; Netherlands; COVID-19; app; discrete choice experiment; participatory epidemiology; smartphone; transmission; contact tracing; uptake; mobile phone; prediction; privacy; participatory surveillance
• ISSN: 2291-5222; 2291-5222
• DOI: 10.2196/20741

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.
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.
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.
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.
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.