COVID-19 and Malaria Co-Infection: Do Stigmatization and Self-Medication Matter? A Case for Nigeria

22 Pages Posted: 5 Oct 2022

See all articles by Wisdom Avusuglo

Wisdom Avusuglo

Africa-Canada Artificial Intelligence and Data Innovation Consortium; Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics (LIAM), York University

Qing Han

Africa-Canada Artificial Intelligence and Data Innovation Consortium

Woldegebriel Assefa Woldegerima

York University; Africa-Canada Artificial Intelligence and Data Innovation Consortium

Ali Asgary

Africa-Canada Artificial Intelligence and Data Innovation Consortium

Jianhong Wu

York University - Laboratory for Industrial and Applied Mathematics; Africa-Canada Artificial Intelligence and Data Innovation Consortium

James Orbinski

Africa-Canada Artificial Intelligence and Data Innovation Consortium; York University - Medical Doctor, Full Professor and Director of the Dahdaleh Institute for Global Health Research

Nicola Luigi Bragazzi

University of Parma

Ali Ahmadi

Africa-Canada Artificial Intelligence and Data Innovation Consortium; K.N. Toosi University, Faculty of Computer Engineering

Jude Dzevela Kong

Africa-Canada Artificial Intelligence and Data Innovation Consortium

Abstract

The Global South is saddled with issues relating to self-medication and the use of complementary medicine, which is due to inadequate resources and patient’s health illiteracy. Documentation of COVID-19 related self-medication is observed in the literature, of which the phenomenon is partly fueled by the rapid spread of rumors in favour of self-medication on social media. Also, common in the Global South is the stigmatization of people with COVID-19. Because of the stigma attached to having COVID-19, most COVID-19 patients prefer to test instead for malaria, since malaria (which is very common in the Global South) and COVID-19 share several symptoms leading to misdiagnosis. Thus, appropriate COVID-19 dynamics prediction in the Global South should account for the role of the self-medicated population, the dynamics of malaria, and the impact of stigmatization. In this paper, we formulate and analyze a mathematical model for the co-dynamics of COVID-19 and malaria in Nigeria. The model is represented by a system of compartmental ODEs that take into account the self-medicated population and the impact of COVID-19 stigmatization. Our findings reveal that COVID-19 stigmatization and misdiagnosis contribute to self-medication, which, in turn, increases the prevalence of COVID-19. The basic and invasion reproduction numbers for these diseases and quantification of model parameters uncertainties and sensitivities are presented.

Note:

Funding Information: This research is funded by Canada’s International Development Research Centre (IDRC) and the Swedish International Development Cooperation Agency (SIDA) (Grant No. 109559-001). JDK acknowledges support from NSERC Discovery Grant (Grant No. RGPIN-2022-04559).

Declaration of Interests: The authors declare no conflict of interest.

Keywords: Epidemiology, COVID-19, Malaria, Self-medication

Suggested Citation

Avusuglo, Wisdom and Han, Qing and Woldegerima, Woldegebriel Assefa and Asgary, Ali and Wu, Jianhong and Orbinski, James and Bragazzi, Nicola Luigi and Ahmadi, Ali and Kong, Jude Dzevela, COVID-19 and Malaria Co-Infection: Do Stigmatization and Self-Medication Matter? A Case for Nigeria. Available at SSRN: https://ssrn.com/abstract=4220775

Wisdom Avusuglo

Africa-Canada Artificial Intelligence and Data Innovation Consortium ( email )

Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics (LIAM), York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Qing Han

Africa-Canada Artificial Intelligence and Data Innovation Consortium ( email )

Woldegebriel Assefa Woldegerima

York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Africa-Canada Artificial Intelligence and Data Innovation Consortium ( email )

Ali Asgary

Africa-Canada Artificial Intelligence and Data Innovation Consortium ( email )

Jianhong Wu

York University - Laboratory for Industrial and Applied Mathematics ( email )

Canada

Africa-Canada Artificial Intelligence and Data Innovation Consortium ( email )

James Orbinski

Africa-Canada Artificial Intelligence and Data Innovation Consortium ( email )

York University - Medical Doctor, Full Professor and Director of the Dahdaleh Institute for Global Health Research ( email )

Ontario, M3J 1P3
Canada

Nicola Luigi Bragazzi

University of Parma ( email )

Ali Ahmadi

Africa-Canada Artificial Intelligence and Data Innovation Consortium ( email )

K.N. Toosi University, Faculty of Computer Engineering ( email )

Tehran
Iran

Jude Dzevela Kong (Contact Author)

Africa-Canada Artificial Intelligence and Data Innovation Consortium ( email )

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