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

Gabriel O. Odekina; Adedayo F. Adedotun; Ogbu F. Imaga

doi:10.46481/jnsps.2022.431

Authors

Gabriel O. Odekina
Department of Mathematics, Covenant University Ota, Ogun, Nigeria
Adedayo F. Adedotun
[email protected]

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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