The coronavirus disease (COVID-19), caused by the SARS-CoV-2 virus, was declared a pandemic by the World Health Organization (WHO) in February 2020. Currently, there are no vaccines or treatments that have been approved after clinical trials. Social distancing measures, including travel bans, school closure, and quarantine applied to countries or regions are being used to limit the spread of the disease, and the demand on the healthcare infrastructure. The seclusion of groups and individuals has led to limited access to accurate information. To update the public, especially in South Africa, announcements are made by the minister of health daily. These announcements narrate the confirmed COVID-19 cases and include the age, gender, and travel history of people who have tested positive for the disease. Additionally, the South African National Institute for Communicable Diseases updates a daily infographic summarising the number of tests performed, confirmed cases, mortality rate, and the regions affected. However, the age of the patient and other nuanced data regarding the transmission is only shared in the daily announcements and not on the updated infographic. To disseminate this information, the Data Science for Social Impact research group at the University of Pretoria, South Africa, has worked on curating and applying publicly available data in a way that is computer readable so that information can be shared to the public – using both a data repository and a dashboard. Through collaborative practices, a variety of challenges related to publicly available data in South Africa came to the fore. These include shortcomings in the accessibility, integrity, and data management practices between governmental departments and the South African public. In this paper, solutions to these problems will be shared by using a publicly available data repository and dashboard as a case study.
CITATION STYLE
Marivate, V., & Combrink, H. M. (2020). Use of available data to inform the COVID-19 outbreak in South Africa: A case study. Data Science Journal, 19(1), 1–7. https://doi.org/10.5334/dsj-2020-019
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