ArticleSocial sciences & humanities open2021
Exploring the drivers and barriers to uptake for digital contact tracing.
Article in Social sciences & humanities open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Agentic AI as a coordination paradigm in digital health and agri-food systems.Patterns (New York, N.Y.) · 2026Review
- Characteristics Influencing Support for the National Health Service COVID-19 App in England and Wales: Findings From a Longitudinal Survey.Journal of medical Internet research · 2026Article
- The Use of Contact Tracing Technologies for Infection Prevention and Control Purposes in Nosocomial Settings: A Systematic Literature Review.Infectious disease reports · 2024Review
- Population and contact tracer uptake of New Zealand's QR-code-based digital contact tracing app for COVID-19.Epidemiology and infection · 2024Article
- Determinants of Dutch public health professionals' intention to use digital contact tracing support tools: A cross-sectional online questionnaire study.PLOS digital health · 2024Article
- An open-source digital contact tracing system tailored to haulage.Frontiers in digital health · 2023Article
- The German COVID-19 Digital Contact Tracing App: A Socioeconomic Evaluation.International journal of environmental research and public health · 2022Article
- COVID-19 contact-tracing smartphone application usage-The New Zealand COVID Tracer experience.Telecommunications policy · 2022Article
- What Went Wrong with the IMMUNI Contact-Tracing App in Italy? A Cross-Sectional Survey on the Attitudes and Experiences among Healthcare University Students.Life (Basel, Switzerland) · 2022Article
- Individual-Level Evaluation of the Exposure Notification Cascade in the SwissCovid Digital Proximity Tracing App: Observational Study.JMIR public health and surveillance · 2022Observational
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital contact tracing has been deployed as a public health intervention to help suppress the spread of Covid-19 in many jurisdictions. However, most governments have struggled with low uptake and participation rates, limiting the effectiveness of the tool. This paper characterises a number of systems developed around the world, comparing the uptake rates for systems with different technology, data architectures, and mandates. The paper then introduces the MAST framework (motivation, access, skills, and trust), adapted from the digital inclusion literature, to explore the drivers and barriers that influence people's decisions to participate or not in digital contact tracing systems. Finally, the paper discusses some suggestions for policymakers on how to influence those drivers and barriers in order to improve uptake rates. Examples from existing digital contact tracing systems are presented throughout, although more empirical experimentation is required to support more concrete conclusions on effective interventions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.