Retrospective Study of the Impact of Sensitization on COVID-19 Pandemic in Rivers State, Nigeria

Abstract

This study examines the impact of sensitization on COVID-19 dynamics in Rivers State, Nigeria, utilizing a mathematical model and data from the Nigeria Centre for Disease Control (NCDC). Parameter estimation involves meticulous fitting, refining key parameters like βc, cm, α1, α2, α3, α4, and the reproduction number Rc. The study employs a genetic algorithm for precise parameter estimation, ensuring the model aligns closely with observed COVID-19 data. Estimated values for βc, cm, α1, α2, α3, α4, and Rc provide a robust foundation for accurate simulations, enhancing the reliability of the model and facilitating a deeper understanding of the population dynamics of COVID-19 in human population. Uncertainty and sensitivity analyses highlight crucial parameters, emphasizing the relative infectiousness of asymptomatic individuals (ηs), face mask efficacy (ϵm), and sensitization effectiveness (ϵs, cm). Numerical simulations reveal that a combined strategy of sensitization and face mask use can significantly curtail the disease progression. Targeting susceptible and exposed individuals in sensitization efforts proves most beneficial, aligning with sensitivity analysis results. Notably, the combination of sensitization and face mask use results in a remarkable 98% reduction in cumulative cases. Sensitization emphasizing various preventive measures, when doubled, shows a 99% reduction. These findings suggest that a comprehensive sensitization approach can profoundly impact COVID-19 control. Policymakers can leverage these insights to optimize sensitization
programs, emphasizing the role of preventive measures beyond face mask use, ultimately guiding effective public health strategies in Rivers State and beyond.