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Exploring the drivers and barriers to uptake for digital contact tracing.
Chen, Andrew Tzer-Yeu; Thio, Kimberly Widia.
  • Chen AT; Koi Tu: The Centre for Informed Futures, The University of Auckland, New Zealand.
  • Thio KW; Koi Tu: The Centre for Informed Futures, The University of Auckland, New Zealand.
Soc Sci Humanit Open ; 4(1): 100212, 2021.
Article in English | MEDLINE | ID: covidwho-1466907
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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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Soc Sci Humanit Open Year: 2021 Document Type: Article Affiliation country: J.ssaho.2021.100212

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Soc Sci Humanit Open Year: 2021 Document Type: Article Affiliation country: J.ssaho.2021.100212