Exploring the Drivers and Barriers to Uptake for Digital Contact Tracing

TL;DR

This paper analyzes global digital contact tracing systems, identifying key drivers and barriers to user participation, and proposes a framework to enhance uptake through policy interventions, emphasizing the need for further empirical validation.

Contribution

It introduces the MAST framework for understanding participation in digital contact tracing and compares different system architectures and mandates to identify factors affecting uptake.

Findings

Uptake rates vary significantly across systems and technologies.

Trust and access are critical drivers for participation.

Policy measures can influence user engagement.

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 what works.