A Spatial SEIR Model for COVID-19 in South Africa

Authors

  • Inger Fabris-Rotelli Department of Statistics, University of Pretoria https://orcid.org/0000-0002-2192-4873
  • Jenny Holloway Council for Scientific Research South Africa
  • Zaid Kimmie Foundation for Human Rights, South Africa
  • Sally Archibald School of Animal, Plant and Environmental Sciences, University of Witwatersrand
  • Pravesh Debba Council for Scientific Research South Africa https://orcid.org/0000-0003-4870-988X
  • Raeesa Manjoo-Docrat Department of Statistics and Actuarial Science, University of Witwatersrand https://orcid.org/0000-0003-2039-0440
  • Alize le Roux Council for Scientific Research, South Africa https://orcid.org/0000-0002-9214-5076
  • Nontembeko Dudeni-Tlhone Council for Scientific Research, South Africa https://orcid.org/0000-0002-8853-3121
  • Charl Janse van Rensburg Biostatistics Research Unit, South African Medical Research Council
  • Renate Thiede Department of Statistics, University of Pretoria https://orcid.org/0000-0003-0934-5374
  • Nada Abdelatif Biostatistics Research Unit, South African Medical Research Council
  • Sibusisiwe Makhanya IBM, South Africa
  • Arminn Potgieter Department of Statistics, University of Pretoria https://orcid.org/0000-0001-6649-9690

DOI:

https://doi.org/10.52933/jdssv.v2i7.46

Keywords:

COVID-19, SEIR model, spatial, excess deaths, South Africa, hospitilisations

Abstract

The virus SARS-CoV-2 has resulted in numerous modelling approaches arising rapidly to understand the spread of the disease COVID-19 and to plan for future interventions. Herein, we present an SEIR model with a spatial spread component as well as four infectious compartments to account for the variety of symptom levels and transmission rate. The model takes into account the pattern of spatial vulnerability in South Africa through a vulnerability index that is based on socioeconomic and health susceptibility characteristics. Another spatially relevant factor in this context is level of mobility throughout. The thesis of this study is that without the contextual spatial spread modelling, the heterogeneity in COVID-19 prevalence in the South African setting would not be captured. The model is illustrated on South African COVID-19 case counts and hospitalisations.

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Published

2022-11-28

How to Cite

Fabris-Rotelli, I., Holloway, J., Kimmie, Z., Archibald, S., Debba, P., Manjoo-Docrat, R., le Roux, A., Dudeni-Tlhone, N., Janse van Rensburg, C., Thiede, R., Abdelatif, N., Makhanya, S., & Potgieter, A. (2022). A Spatial SEIR Model for COVID-19 in South Africa. Journal of Data Science, Statistics, and Visualisation, 2(7), 14–45. https://doi.org/10.52933/jdssv.v2i7.46

Issue

Vol. 2 No. 7 (2022): Special Issue on COVID-19 Visualisation and Modeling

Section

Modeling and visualization of covid-19 data