摘要：Several studies have attempted to uncover the impact of weather parameters on the coronavirus (COVID-19) pandemic during the initial stage of its outbreak. However, they reported contradicting findings due to limited data available at an earlier stage of the outbreak. Therefore, in this study, we investigate the impact of regional temperature on the pandemic in 34 different locations of the globe by defining two main objectives. The first objective is focused on pattern analysis of an earlier stage of the pandemic. The conducted analysis suggests that the spread of the COVID-19 outbreak during its initial stage was slower in the regions experiencing extreme temperatures. The second objective is about understanding the impact of temperature on new cases (NC) and new deaths (ND) of COVID-19 reported per day by using linear regression (LR) as a statistical tool. For most of the locations, under simple LR analysis, a significant inverse relationship has been observed between average temperature and NC or ND. However, a few locations, including Pakistan, India, Singapore, Bahrain, and Qatar, have shown a significant positive relationship between average temperature and NC with a 99.9% confidence level. Furthermore, Pakistan, Thailand, Bahrain, and Qatar have shown a significant positive relationship between average temperature and ND with a 95% confidence level. Although most of these locations experienced temperatures with a mean greater than 22 °C and standard deviation greater than 5 °C, excluding India, the number of total COVID-19 cases reported in these locations is small. Moreover, the results of multiple LR analysis reveal a significant inverse relationship between average temperature and NC or ND with a 95% confidence level.
