Introduction: At the peak of Uganda’s first wave of SARS-CoV-2 in May 2020, one in three COVID-19 cases was linked to the haulage sector. This triggered a mandatory requirement for a negative PCR test result at all ports of entry and exit, resulting in significant delays as haulage drivers had to wait for 24-48 hours for results, which severely crippled the regional supply chain.

To support public health and economic recovery, we aim to develop and test a mobile phone-based digital contact tracing (DCT) tool that both augments conventional contact tracing and also increases its speed and efficiency.

Methods and analysis: To test the DCT tool, we will use a stratified sample of haulage driver journeys, stratified by route type (regional and local journeys).

We will include at least 653 200 on the network through Uganda. This allows us to capture variations in user demographics and socioeconomic characteristics that could influence the use and adoption of the DCT tool. The developed DCT tool will include a mobile application and web interface to collate and intelligently process data, whose output will support decision-making, resource allocation and feed mathematical models that predict epidemic waves.

The main expected result will be an open source-tested DCT tool tailored to haulage use in developing countries.

This study will inform the safe deployment of DCT technologies needed for combatting pandemics in low-income countries.

Ethics and dissemination: This work has received ethics approval from the School of Public Health Higher Degrees, Research and Ethics Committee at Makerere University and The Uganda National Council for Science and Technology. This work will be disseminated through peer-reviewed publications, our websites https://project-thea.org/ and Github for the open source code https://github.com/project-thea/.


This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

Cite as

Muwonge, A., Mpyangu, C., Nsangi, A., Mugerwa, I., Bronsvoort, B., Porphyre, T., Ssebaggala, E., Kiayias, A., Mwaka, E. & Joloba, M. 2022, 'Developing digital contact tracing tailored to haulage in East Africa to support COVID-19 surveillance: a protocol', BMJ Open, 12(9), article no: e058457. https://doi.org/10.1136/bmjopen-2021-058457

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Last updated: 07 September 2022
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