The effect of vaccine on COVID-19 spread by function-on-scalar regression model: a case study of Africa.

Abstract

Aim: This paper aimed to study the effect of the vaccine on the reproduction rate of coronavirus in Africa from January 2021 to November 2021.

Subject and methods: Functional data analysis (FDA), a relatively new area in statistics, can describe, analyze, and predict data collected over time, space, or other continuum measures in many countries every day and is increasingly common across scientific domains. For our data, the first step of functional data is smoothing. We used the B-spline method to smooth our data. Then, we apply the function-on-scalar and Bayes function-on-scalar models to fit our data.

Results: Our results indicate a statistically significant relationship between the vaccine and the rate of virus reproduction and spread. When the vaccination rate falls, the reproduction rate also decreases. Furthermore, we found that the effect of latitude and the region on the reproduction rate depends on the region. We discovered that in Middle Africa, from the beginning of the year until the end of the summer, the impact is negative, implying that the virus spread due to a decrease in the vaccination rates.

Conclusion: The study found that vaccination rates significantly impact the virus's reproduction rate.