Many of the respiratory pathogens show seasonal patterns and association with environmental factors. In this article, we conducted a cross-sectional analysis of the influence of environmental factors, including climate change along with development indicators on the differential global spread and fatality of COVID-19 during its early phase. We used the published COVID-19 data by the WHO for April. Global climate data we used are monthly averaged gridded datasets of Temperature, Humidity and Temperature Anomaly. We used the HDI to account for all other socioeconomic factors that can affect the disease spread and mortality and build a negative binomial regression model. The temperature has a negative association with COVID-19 mortality. However, HDI is shown to confound the effect of temperature on the reporting of the disease. Temperature anomaly, which is being regarded as a global warming indicator, is positively associated with the pandemic's spread and mortality. Viewing newer infectious diseases like SARS-CoV-2 in the perspective of climate change has a lot of public health implications, and it necessitates further research.