Exploring the impact of air pollution on COVID-19 admitted cases: Evidence from vector error correction model (VECM) approach in explaining the relationship between air pollutants towards COVID-19 cases in Kuwait

In urban areas, air pollution is one of the most serious global environmental issues. Using time-series approaches, this study looked into the validity of the relationship between air pollution and COVID-19 hospitalization. This time series research was carried out in the state of Kuwait. Stationarity test, cointegration test, Granger causality and stability test, test on multivariate time-series using the Vector Error Correction Model (VECM) technique. The findings reveal that the concentration rate of air pollutants (O₃, SO₂, NO₂, CO, and PM10) has an effect on COVID-19 admitted cases via Granger-cause. The Granger causation test shows that the concentration rate of air pollutants (O₃, PM10, NO₂, temperature and wind speed) influences and predicts the COVID-19 admitted cases. The findings suggest that sulfur dioxide (SO₂), NO₂, temperature and wind speed induce an increase in COVID-19 admitted cases in the short term according to VECM analysis. The evidence of a positive long-run association between COVID-19 admitted cases and environmental air pollution might be shown in the cointegration test and the VECM. There is an affirmation that the usage of air pollutants (O₃, SO₂, NO₂, CO, and PM10) has a significant impact on COVID-19 admitted cases prediction and its explained about 24% of increasing COVID-19 admitted cases in Kuwait.