Models and muddles in the COVID-19 pandemic

Authors

  • Farai Nyabadza 1.Department of Mathematics and Applied Mathematics, University of Johannesburg, Johannesburg, South Africa; 2.Data Science Across Disciplines Research Group, Institute for the Future of Knowledge, University of Johannesburg, Johannesburg, South Africa https://orcid.org/0000-0003-3468-5581
  • Alex Broadbent Institute for the Future of Knowledge, University of Johannesburg, Johannesburg, South Africa https://orcid.org/0000-0001-5120-6584
  • Charis Harley 1.Data Science Across Disciplines Research Group, Institute for the Future of Knowledge, University of Johannesburg, Johannesburg, South Africa; 2.Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa https://orcid.org/0000-0001-6935-5131
  • Abejide Ade-Ibijola 1.Data Science Across Disciplines Research Group, Institute for the Future of Knowledge, University of Johannesburg, Johannesburg, South Africa; 2.Department of Applied Information Systems, College of Business and Economics, University of Johannesburg, Johannesburg, South Africa https://orcid.org/0000-0001-9507-0455
  • Ebrahim Momoniat 1.Department of Mathematics and Applied Mathematics, University of Johannesburg, Johannesburg, South Africa; 2.Data Science Across Disciplines Research Group, Institute for the Future of Knowledge, University of Johannesburg, Johannesburg, South Africa https://orcid.org/0000-0001-7762-2690

DOI:

https://doi.org/10.17159/sajs.2021/9506

Keywords:

mathematical models, epidemiology, infectious diseases, public health, COVID-19

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Published

2021-09-29

How to Cite

Nyabadza, F., Broadbent, A., Harley, C., Ade-Ibijola, A., & Momoniat, E. (2021). Models and muddles in the COVID-19 pandemic. South African Journal of Science, 117(9/10). https://doi.org/10.17159/sajs.2021/9506

Issue

Vol. 117 No. 9/10 (2021)

Section

Commentary

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