Assessment of bidirectional impact of stigmatization induced self-medication on COVID-19 and malaria transmissions
Wisdom S Avusuglo1, Qing Han2, Woldegebriel Assefa Woldegerima3
1Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), York University, Canada; Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Canada; Global South Artificial Intelligence for Pandemic and Epidemic Preparedness and Response Network (AI4PEP), Canada.
Abstract:
The continual social and economic impact of infectious diseases on nations has maintained sustained attention on their control and treatment, of which self-medication has been one of the means employed by some individuals. Self-medication complicates the attempt of their control and treatment as it conflicts with some of the measures implemented by health authorities. Added to these complications is the stigmatization of individuals with some diseases in some jurisdictions. This study investigates the co-infection of COVID-19 and malaria and its related deaths and further highlights how self-medication and stigmatization add to the complexities of the fight against these two diseases using Nigeria as a study case. Using a mathematical model on COVID-19 and malaria co-infection, we address the question: to what degree does the impact of the interaction between COVID-19 and malaria amplify infections and deaths induced by both diseases via self-medication and stigmatization? We demonstrate that COVID-19 related self-medication due to misdiagnoses contributes substantially to the prevalence of disease. The control reproduction numbers for these diseases and quantification of model parameters uncertainties and sensitivities are presented.
