Exploring the drivers and barriers to uptake for digital contact tracing
Bibliographic Data
| ID | 22205261 |
|---|---|
| Authors | Andrew Tzer-Yeu Chen (0000-0002-6239-8443, University of Auckland, corresponding author), Kimberly Widia Thio, Kimberly Thio (University of Auckland) |
| Year | 2021 |
| Volume | 4 |
| Issue | 1 |
| Pages | 100212 |
| Publication date | 2021-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Sciences & Humanities Open (JOURNAL) |
| Journal identifiers | ISSN: 2590-2911 • E-ISSN: 2590-2911 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ssaho.2021.100212 |
| PMID | 34642660 |
| OpenAlex | W3136821457 |
| Language | EN |
| Citations received | 4 |
| References cited | 66 |
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
Business · Computer security · Contact tracing · Internet privacy · Limiting · Political science · Public relations · Tracing · Computer Science · COVID-19 Digital Contact Tracing · Engineering · Medicine · Privacy-Preserving Technologies in Data · Privacy, Security, and Data Protection · Psychology · Social Psychology
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| Unique citing works | 4 |
|---|---|
| Citations per year | 1 |
| Citation span | 2022 - 2024 (3) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |