An open-source digital contact tracing system tailored to haulage

Frontiers in Digital Health

Digital Health

Aggelos Kiayias¹  Emmanuel Robert Ssebaggala²  Christine M. Mpyangu³  Erisa Mwaka⁴  Barend M. de C. Bronsvoort⁵  Bryan A. Wee⁵  Adrian Muwonge⁶  Ibrahimm Mugerwa⁷  Emma Nabunya⁸  Moses Joloba⁸ 

[1] Blockchain Technology Laboratory, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom;Bodastage Solutions, Kampala, Uganda;College of Humanities and Social Sciences, Makerere University, Kampala, Uganda;Department of Anatomy, College of Health Sciences, Makerere University, Kampala, Uganda;Digital One Health Laboratory, The Roslin Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom;Digital One Health Laboratory, The Roslin Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom;Blockchain Technology Laboratory, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom;Ministry of Health, Kampala, Uganda;School of Biomedical Sciences, College of Health Sciences, Makerere University, Kampala, Uganda;

关键词: targeted digital;    contact tracing;    COVID-19;    global south;    LMIC;    open-source;   

DOI  :  10.3389/fdgth.2023.1199635

 received in 2023-04-03, accepted in 2023-07-06,  发布年份 2023

来源: Frontiers

【 摘 要 】

Digital contact tracing presents numerous advantages compared to manual contact tracing methods, especially in terms of enhanced speed and automation. Nevertheless, a lack of comprehensive evaluation regarding functionality, efficiency, benefits, and acceptance within communities remains. Here we primarily focus on the functionality of THEA-GS, an open-source digital contact tracing tool developed through consultation with stakeholders. Additionally, we provide insights from its implementation on a limited sample of haulage drivers in Uganda, serving as a representative case for a low- and middle-income country. THEA-GS comprises two primary components: (a) a smartphone application, and (b) a suite of server-programs responsible for data processing and analysis, including databases and a web-based interface featuring dashboards. In essence, the mobile application records the timestamped location of haulage drivers within the road network and identifies possible transmission hotspots by analyzing factors such as the duration of stops and the communities associated with them. The tool can be integrated with national infrastructure to compare drivers’ diagnostic results and contact structure, thereby generating individual and community risk assessments relative to the road network. During the Omicron-variant wave of the COVID-19 pandemic, a total of 3,270 haulage drivers were enrolled between October 2021 and October 2022. Around 75% of these drivers utilized THEA-GS for approximately two months. Based on an analysis of 3,800 test results, which included 48 positive cases, 125 contacts, and 40 million time-stamped GPS points, THEA-GS shows a significant speed improvement, being approximately 90 times faster than MCT. For instance, the average time from sample collection to notifying a case and their contacts was approximately 70 and 80 min, respectively. The adoption of this tool encountered challenges, mainly due to drivers’ awareness of its purpose and benefits for public health. THEA-GS is a place-based digital contact tracing tool specifically designed to assist National Public Health Institutions in managing infectious disease outbreaks involving the haulage industry as a high-risk group. While its utility, acceptance, and accuracy have not been fully evaluated, our preliminary tests conducted in Uganda indicate the tool’s functionality is robust, but social acceptance and adoption are heavily reliant on establishing trust among users.

【 授权许可】

Unknown   
© 2023 Muwonge, Wee, Mugerwa, Nabunya, Mpyangu, Bronsvoort, Ssebaggala, Kiayias, Mwaka and Joloba.