COVID-19 contact-tracing apps: predicted uptake in the Netherlands based on a discrete choice experiment

Background: Smartphone-based contact-tracing apps can contribute to significantly reducing COVID-19 transmission rates and thereby support countries emerging from lockdowns as restrictions are gradually eased. Objective: The primary objective of our study was 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 (DCE) 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 (MIXL) model specification. Individual-level uptake probabilities were calculated based on the individual-level preference estimates and subsequently aggregated into 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 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 (i.e. 75+ vs. 15-34 years old), 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 the elderly, who are least inclined to install and use a COVID-19 contact-tracing app.