Feasibility of using a mobile App to monitor and report COVID-19 related symptoms and people’s movements in Uganda
Background
Feasibility of mobile Apps to monitor diseases has not been well documented particularly in developing countries. We developed and studied the feasibility of using a mobile App to collect daily data on COVID-19 symptoms and people’s movements.
Methods
We used an open source software “KoBo Toolbox” to develop the App and installed it on low cost smart mobile phones. We named this App “Wetaase” (“protect yourself”). The App was tested on 30 selected households from 3 densely populated areas of Kampala, Uganda, and followed them for 3 months. One trained member per household captured the data in the App for each enrolled member and uploaded it to a virtual server on a daily basis. The App is embedded with an algorithm that flags participants who report fever and any other COVID-19 related symptom.
Results
A total of 101 participants were enrolled; 61% female; median age 23 (interquartile range (IQR): 17–36) years. Usage of the App was 78% (95% confidence interval (CI): 77.0%–78.8%). It increased from 40% on day 1 to a peak of 81% on day 45 and then declined to 59% on day 90. Usage of the App did not significantly vary by site, sex or age. Only 57/6617 (0.86%) records included a report of at least one of the 17 listed COVID-19 related symptoms. The most reported symptom was flu/runny nose (21%) followed by sneezing (15%), with the rest ranging between 2% and 7%. Reports on movements away from home were 45% with 74% going to markets or shops. The participants liked the “Wetaase” App and recommended it for use as an alert system for COVID-19.
Conclusion
Usage of the “Wetaase” App was high (78%) and it was similar across the three study sites, sex and age groups. Reporting of symptoms related to COVID-19 was low. Movements were mainly to markets and shops. Users reported that the App was easy to use and recommended its scale up. We recommend that this App be assessed at a large scale for feasibility, usability and acceptability as an additional tool for increasing alerts on COVID-19 in Uganda and similar settings.
Top-30
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Journal of the American Medical Informatics Association : JAMIA
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BMC Public Health
1 publication, 12.5%
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The Lancet
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Elsevier
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Oxford University Press
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Springer Nature
1 publication, 12.5%
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SPRIDA
1 publication, 12.5%
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JMIR Publications
1 publication, 12.5%
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Taylor & Francis
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- We do not take into account publications without a DOI.
- Statistics recalculated weekly.