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Modelling the Potential Impact of Stigma on the Transmission Dynamics of COVID-19 in South Africa

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  • Siphokazi Princess Gatyeni

    (Mathematics and Applied Mathematics Department, University of Johannesburg, Johannesburg 2092, South Africa)

  • Faraimunashe Chirove

    (Mathematics and Applied Mathematics Department, University of Johannesburg, Johannesburg 2092, South Africa)

  • Farai Nyabadza

    (Mathematics and Applied Mathematics Department, University of Johannesburg, Johannesburg 2092, South Africa)

Abstract

The COVID-19 pandemic continues to be a problem in South Africa. Individuals affected and infected by the disease suffer from stigma resulting in increased COVID-19 infections. In this paper, we developed a mathematical model to assess the effects of stigma on COVID-19 in South Africa, using low, moderate, and high stigma regimes in the population. The mathematical model was analysed and the basic reproduction number, R 0 , of the COVID-19 model with stigma was determined. The model was then fitted to data of the four COVID-19 waves for the new daily infected cases, and the estimated parameter values from different waves are presented. The effects of stigma on COVID-19 waves were examined using the four stigma regimes (high, moderate, low, and stigma-free regimes). Our results revealed that stigma is instrumental in the increase in the number of COVID-19 infections. It is also a significant contributor to sustaining COVID-19 in the population and probably in other infectious diseases such as HIV/AIDS and sexually transmitted diseases. The results obtained can influence policy directions with respect to stigma and its impact on the transmission dynamics of diseases.

Suggested Citation

  • Siphokazi Princess Gatyeni & Faraimunashe Chirove & Farai Nyabadza, 2022. "Modelling the Potential Impact of Stigma on the Transmission Dynamics of COVID-19 in South Africa," Mathematics, MDPI, vol. 10(18), pages 1-23, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:18:p:3253-:d:909174
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    References listed on IDEAS

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    1. Ullah, Saif & Khan, Muhammad Altaf, 2020. "Modeling the impact of non-pharmaceutical interventions on the dynamics of novel coronavirus with optimal control analysis with a case study," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    2. Sintunavarat, Wutiphol & Turab, Ali, 2022. "Mathematical analysis of an extended SEIR model of COVID-19 using the ABC-fractional operator," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 198(C), pages 65-84.
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