DEVELOPING PREDICTIVE MODEL FOR POVERTY AND COVID-19 INCIDENCES IN NIGERIA

Abstract

Poverty is one of the greatest challenges facing the world today. This is because it is a major cause of ill-health by forcing people to live in dirty environments and a barrier to accessing health care, especially in the developing world. As a result of these, it was predicted that the outbreak of the COVID-19 pandemic will pose a devastating impact on households living beneath the economic, social, health and educational services thresholds. This impact will stem from the direct and indirect effects of the illness and the transmission control policies of governments. Consequently, this study assessed the COVID-19 preventive strategies adopted as well as the statistical relationship between the pre and post-lockdown household income poverty in Minna, Nigeria. The study similarly developed a predictive model for the nexus between poverty headcount ratio and the incidence of COVID-19 in Nigeria. Both the primary and secondary sources of data were employed for this study and the data were analysed using descriptive and inferential statistics (t-Test and regression techniques). The outcome showed that there exists a statistically significant difference between the pre-lockdown poverty rate and the post-lockdown poverty rate in Minna. The study also revealed that for each unit increase in poverty headcount ratio, the incidences of COVID-19 cases and its fatalities decreases by -42.5625 and -0.56077 units respectively. The study, therefore, recommended the domestication of the existing social intervention programmes of the Federal Government, by States Governments in order to enhance the standard of living of more households. It was also recommended that all stakeholders most partake in enlightenment and sensitization programmes on the need to adopt preventive measures to guard against the transmission of the virus.