Investigating the impact of CO₂ emissions on the COVID-19 pandemic by generalized linear mixed model approach with inverse Gaussian and gamma distributions

Abstract Carbon dioxide (CO 2 ) rate within the atmosphere has been rising for decades due to human activities especially usage of fuel types such as coal, cement, flaring, gas, oil, etc. Especially in 2020, COVID-19 pandemic caused major economic, production, and energy crises all around world. As a result this situation, there was sharp decrease global CO emissions depending on used during pandemic. The aim study explore effects “CO types” “percentage deaths total cases” attributed using generalized linear model mixed (GLMM) approaches with inverse Gaussian gamma distributions, also obtain statistical inferences about 169 World Health Organization member countries that will disclose impact response variable is taken cases pandemic” calculated “(total deaths/total confirmed until December 31, 2020)*100.” explanatory variables are “production-based from different types,” measured tonnes per person, which “coal, oil.” study, according goodness-of-fit test statistics, “GLMM approach distribution” called “gamma regression model” determined most appropriate investigating main findings 1 t belonging “cement, oil” person cause increase by 2.8919, 2.6151, 2.5116, 2.5774, 2.5640%, respectively.