Modeling and Forecasting the Third wave of Covid-19 Incidence Rate in Nigeria Using Vector Autoregressive Model Approach

https://doi.org/10.46481/jnsps.2022.431

Authors

  • Gabriel O. Odekina Department of Mathematics, Covenant University Ota, Ogun, Nigeria
  • Adedayo F. Adedotun Department of Mathematics, Covenant University Ota, Ogun, Nigeria
  • Ogbu F. Imaga Department of Mathematics, Covenant University Ota, Ogun, Nigeria

Keywords:

Covid-19, Vector Autoregressive model, Akaike Information Criterion, Final Prediction Error, Hannan Quinn Information Criterion

Abstract

Modeling the onset of a pandemic is important for forming inferences and putting measures in place. In this study, we used the Vector autoregressive model to model and forecast the number of confirmed covid-19 cases and deaths in Nigeria, taking into account the relationship that exists between both multivariate variables. Before using the Vector Autoregressive model, a co-integration test was performed. An autocorrelation test and a heteroscedasticity test were also performed, and it was discovered that there is no autocorrelation at lags 3 and 4, as well as no heteroscedasticity. According to the findings of the study, the number of covid-19 cases and deaths is on the rise. To forecast the number of cases and deaths, a Vector Autoregressive model with lag 4 was used. The projection likewise shows a steady increase in the number of deaths over time, but a minor drop in the number of confirmed Covid-19 cases.

Dimensions

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Published

2022-02-27

How to Cite

Odekina, G. O., Adedotun, A. F., & Imaga, O. F. (2022). Modeling and Forecasting the Third wave of Covid-19 Incidence Rate in Nigeria Using Vector Autoregressive Model Approach. Journal of the Nigerian Society of Physical Sciences, 4(1), 117–122. https://doi.org/10.46481/jnsps.2022.431

Issue

Section

Original Research