Coronavirus COVID-19 (2019-nCoV) Data Repository for South Africa

Coronavirus COVID-19 (2019-nCoV) Data Repository for South Africa created, maintained and hosted by Data Science for Social Impact research group, led by Dr. Vukosi Marivate, at the University of Pretoria.

Disclaimer: We have worked to keep the data as accurate as possible. We collate the COVID 19 reporting data from NICD and DoH. We only update that data once there is an official report or statement. For the other data, we work to keep the data as accurate as possible. If you find errors. Make a pull request.

If you use this repo for any research/development/innovation, please contact us (see contacts below)

See our blog posts:

• Why we built this and how we are working,
• How this is a call to action across the African continent
• A few weeks in, Data Science thoughts on COVID-19 in South Africa

If you are interested in the Africa-wide effort: Go to https://github.com/dsfsi/covid19africa

For information on daily updates on the repo, go to https://twitter.com/vukosi/status/1239184086633242630?s=20

Licenses

Code | Data

Data Available [/data]

Please note that these reports are the daily reports as released by the National Department of Health or the NICD. The new cases reported are based on new positive test reports released. However, there may be significant lag from when the patient was tested. As an example in epidemiological Week 1 of 2021 (3-9 Jan) approximately 33k new cases were reported on the daily announcement. However, the NICD Testing Summary Report for Week 3 of 2021 (which also reports the two previous weeks) shows that the number of positive tests was 43635 for Week 1 of 2021. The difference is due to the lag in testing being done -- some of the 33k cases reported on the daily announcments were actually from prior weeks while a large number of people were tested between 3-9 January, but the cases were only reported from the 10th onwards. Care needs to be taken in doing some analyses to take this into account.

Active

Deprecated

NOTE: Since around 24 March 2020, we have not gotten individual case data from DoH or NICD. For now if you need provincial counts use the provincial_cumulative_timeline. For individual cases up to 25 March 2020, use the confirmed_cases.

* NICD no longer gives individual case data. Please use provincial_cumulative_timeline from 26 March 2020 onwards.

Dashboard

• Google Data Studio Dashboard URL link

Data Sources:

• NICD - South Africa URL
• Department of Health - South Africa Main Site, Twitter
• South African Government Media Statements URL
• National Department of Health Data Dictionary URL
• MedPages URL
• Statistics South Africa URL

Contributing

Options

• I want to help, but don't have an idea: You can take a look at the issues to see which one you might be interested in tackling.
• I have an idea or new feature: Create a new issue first, assign it to yourself and then fork the repo.

Adopting a file

Once you have chosen how you are going to contribute, you must list which files you will be working on by adding your name to the adopt-a-file csv file. Edit covid19za_volunteer_adopted_file.

Submitting Changes [Pull Request]

• See https://opensource.com/article/19/7/create-pull-request-github

Resources [Get some ideas]

• Data Science Africa COVID-19 Response
• IndabaX South Africa: Vukosi Marivate - Using data science to inform the COVID-19 outbreak in Africa
• Stanford <> CS472 Data science and AI for COVID-19

Contributors

Made with contributors-img.

• See https://github.com/dsfsi/covid19za/graphs/contributors

Contact

• Vukosi Marivate - [email protected], @vukosi

Citing the dataset

On a visualisation/notebook/webapp:

Data Science for Social Impact Research Group @ University of Pretoria, Coronavirus COVID-19 (2019-nCoV) Data Repository for South Africa. Available on: https://github.com/dsfsi/covid19za.

In a publication

Data Science Journal

@article{marivate2020use, Author = {Vukosi Marivate and Herkulaas MvE Combrink}, Journal = {Data Science Journal}, Number = {1}, Pages = {1-7}, Title = {Use of Available Data To Inform The COVID-19 Outbreak in South Africa: A Case Study.}, Volume = {19}, Year = {2020}, url = {https://doi.org/10.5334/dsj-2020-019} }

and Dataset

@dataset{marivate_vukosi_2020_3819126, author = {Marivate, Vukosi and Arbi, Riaz and Combrink, Herkulaas and de Waal, Alta and Dryza, Henkho and Egersdorfer, Derrick and Garnett, Shaun and Gordon, Brent and Greyling, Lizel and Lebogo, Ofentswe and Mackie, Dave and Merry, Bruce and Mkhondwane, S'busiso and Mokoatle, Mpho and Moodley, Shivan and Mtsweni, Jabu and Mtsweni, Nompumelelo and Myburgh, Paul and Richter, Jannik and Rikhotso, Vuthlari and Rosen, Simon and Sefara, Joseph and van der Walt, Anelda and van Heerden, Schalk and Welsh, Jay and Hazelhurst, Scott and Petersen, Chad and Mbuvha, Rendani and Dhlamini, Nelisiwe and James, Vaibhavi}, title = {{Coronavirus disease (COVID-19) case data - South Africa}}, month = mar, year = 2020, publisher = {Zenodo}, doi = {10.5281/zenodo.3819126}, url = {https://doi.org/10.5281/zenodo.3819126} }

Showcase

Web Projects

Some of COVID-19 Data for South Africa (data in this repo) is currently being used by other independent projects shown in the table below :

Scholarly Work

See Google Scholar

Support

We want to acknowledge support from these organisations

• International Astronomical Union - Astronomy for Development
• Google Cloud Platform