TY - JOUR
T1 - Exploring the impact of air pollution on COVID-19 admitted cases
T2 - Evidence from vector error correction model (VECM) approach in explaining the relationship between air pollutants towards COVID-19 cases in Kuwait
AU - Alsaber, Ahmad R.
AU - Setiya, Parul
AU - Al-Sultan, Ahmad T.
AU - Pan, Jiazhu
PY - 2022/7/31
Y1 - 2022/7/31
N2 - 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.
AB - 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.
KW - air pollution
KW - Covid-19
KW - cointegration
KW - long-run relationship
KW - Kuwait
U2 - 10.1007/s42081-022-00165-z
DO - 10.1007/s42081-022-00165-z
M3 - Article
VL - 5
SP - 379
EP - 406
IS - 1
ER -