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Exploring the drivers and barriers to uptake for digital contact tracing
Andrew Tzer-Yeu Chen1, Kimberly Widia Thio1
1Koi Tū: The Centre for Informed Futures, The University of Auckland, New Zealand.
Social Sciences & Humanities Open
|October 13, 2021
Summary
Digital contact tracing tools for Covid-19 have low participation. The MAST framework (motivation, access, skills, trust) identifies barriers to uptake, offering policy suggestions for improvement.
Area of Science:
- Public Health
- Digital Health
- Health Policy
Background:
- Digital contact tracing (DCT) was implemented globally to curb Covid-19 transmission.
- Low participation rates have significantly limited the effectiveness of DCT interventions.
- Understanding user adoption barriers is crucial for optimizing public health digital tools.
Purpose of the Study:
- To analyze global DCT systems and their uptake rates.
- To identify key drivers and barriers influencing participation in DCT.
- To propose policy recommendations for enhancing DCT uptake.
Main Methods:
- Comparative analysis of various international DCT systems based on technology, data architecture, and mandates.
- Application of the MAST framework (Motivation, Access, Skills, Trust) to assess participation factors.
- Review of existing DCT system examples and policy implications.
Main Results:
- Significant variations in uptake rates exist across different DCT systems.
- The MAST framework effectively characterizes individual and societal factors influencing DCT adoption.
- Specific technological, data, and policy elements correlate with higher or lower participation.
Conclusions:
- Addressing motivation, access, skills, and trust is essential for improving DCT uptake.
- Policy interventions can be designed to mitigate identified barriers.
- Further empirical research is needed to validate specific intervention strategies for DCT systems.
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