A mathematical model for transmission dynamics of COVID-19 in Nigeria and its post effects

Résumé

This study presents a mathematical model formulated through a system of differential equations to analyze the dynamics of COVID-19 in Nigeria and its post effects. The total population (N), is divided into six compartments: susceptible (S), vaccinated (V), exposed (E), infected (I), deceased (D), and recovered (R). Our primary objective is to conduct a comprehensive mathematical analysis of the disease and elucidate its post-effects. Qualitative analyses such as identification of invariant regions, positivity of solutions, and stability analyses are performed. The basic reproduction number is obtained using the next-generation matrix,
and its epidemiological significance such as threshold for epidemic spread, intervention decision and estimation of herd immunity are discussed. Sensitivity analysis is conducted to determine the most influential parameters and numerical simulation is carryout using MATLAB which revealed the model behavior in real-life. Post-effects of COVID-19 in Nigeria which include increased in poverty levels, reduced income, job losses, strain in healthcare system, educational disruption are identified. Our findings underscore the importance of implementing targeted public health interventions to mitigate the socio-economic impact of the pandemic, strengthen the healthcare system's resilience, and address the educational disruptions. Recommendations
include prioritizing vaccination efforts to achieve herd immunity, enhancing healthcare infrastructure and capacity, implementing social protection measures to support vulnerable populations, and adopting innovative approaches to facilitate remote learning and educational recovery.