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An open-source digital contact tracing system tailored to haulage
Adrian Muwonge1,2, Bryan A Wee1, Ibrahimm Mugerwa3
1Digital One Health Laboratory, The Roslin Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom.
Frontiers in Digital Health
|August 4, 2023
Summary
THEA-GS, a digital contact tracing tool, demonstrated a 90x speed improvement over manual methods for infectious disease outbreaks in Uganda. User adoption requires building trust and awareness of its public health benefits.
Area of Science:
- Public Health
- Epidemiology
- Digital Health
Background:
- Digital contact tracing offers speed and automation advantages over manual methods.
- Comprehensive evaluations of digital tools' functionality, efficiency, and acceptance are often lacking.
- The haulage industry represents a high-risk group for infectious disease transmission.
Purpose of the Study:
- To evaluate the functionality of THEA-GS, an open-source digital contact tracing tool.
- To provide insights into the implementation and adoption of THEA-GS in a low- and middle-income country context.
- To assess the speed and efficiency of digital contact tracing compared to manual methods.
Main Methods:
- THEA-GS utilizes a smartphone app for location tracking and server programs for data analysis.
- The tool analyzes GPS data, stop durations, and community associations to identify transmission hotspots.
- Integration with national infrastructure allows for comparison of diagnostic results and contact structures.
Main Results:
- THEA-GS demonstrated a significant speed improvement, being approximately 90 times faster than manual contact tracing (MCT).
- Average notification times for cases and contacts were reduced to approximately 70 and 80 minutes, respectively.
- Challenges in adoption were primarily linked to user awareness of the tool's purpose and public health benefits.
Conclusions:
- THEA-GS shows robust functionality for place-based digital contact tracing in managing infectious disease outbreaks.
- Social acceptance and adoption are critically dependent on establishing user trust and clear communication of benefits.
- Further evaluation of utility, acceptance, and accuracy is needed, but preliminary results are promising for high-risk groups like haulage drivers.
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