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Introduction: Self-medication, as a global phenomenon, remains a pressing issue that requires attention worldwide, in particular, the Global South. It has been a hindrance to infectious disease control as it, in most cases dampens interventions put forth by health authorities. It is imperative, therefore, that disease dynamics relating to self-medication are incorporated into mathematical models used to inform infectious disease-related public health interventions and policy. COVID-19-associated self-medication is well documented, and its implications for disease prevention and control are alarming. We investigated the impact of self-medication across different age groups on the transmission dynamics of the disease; the interplay of vaccination and self-medication on the spread of the disease; and the age group with the most tendency for self-medication. We used Gauteng Province, South Africa, as a case study. Methods: We employed ordinary differential equations (ODEs), formulated within an age-structured compartmental disease modelling framework. Model parameters were estimated using a Markov Chain Monte Carlo (MCMC) estimation scheme. Uncertainty and sensitivity analysis were carried out on model parameters. Results: The model implied estimates indicates that self-medication is predominant among Age group 15-64 (83.13%), followed by Age group 65+ (44.17%). Age group 0-14 records 33.82%. The mean value of the basic reproduction number, first epidemic peak, and first epidemic peak time are 3.19838, 821536, and 214.988, respectively. Conclusion: Self-medicationplays a crucial role in combating COVID-19, and that regardless of the levelof effectiveness of instituted vaccination programs, it must be put in check. Appropriate campaign against COVID-19 related self-medication is justified. It is also worth noting that campaigns should target the active population (ages 14-64)

It is imperative that resources are channelled towards programs that are efficient and cost effective in combating the spread of COVID-19, the disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This study proposed and analyzed control strategies for that purpose. We developed a mathematical disease model within an optimal control framework that allows us to investigate the best approach for curbing COVID-19 epidemic. We address the following research question: what is the role of community compliance as a measure for COVID-19 control? Analyzing the impact of community compliance of recommended guidelines by health authorities—examples, social distancing, face mask use, and sanitizing—coupled with efforts by health authorities in areas of vaccine provision and effective quarantine—showed that the best intervention in addition to implementing vaccination programs and effective quarantine measures, is the active incorporation of individuals’ collective behaviours, and that resources should also be directed towards community campaigns on the importance of face mask use, social distancing, and frequent sanitizing, and any other collective activities. We also demonstrated that collective behavioral response of individuals influences the disease dynamics; implying that recommended health policy should be contextualized.