Introduction: Since December 2019, the whole world severely affected due to COVID-19 which impact all sectors of daily life ranging from social, economic, education health, medical, travel, games and leisure. Due to COVID-19 whole world facing an adverse crisis of all nature covering almost all areas of including social, economic, travelling, educations and even health. This study presents a detailed analysis related to the role of the total number of days to reach maximum daily cases of COVID-19 cases. Objective: To investigate the impact of temperature and the total number of days to reach the highest daily cases and mortality rate in the top ten affected worldly countries. Methods: A detailed analysis of the impact of temperature and the role of the total number of days to reach the peak in selected countries. The available data from WHO is used to analyze the impact of temperature and the total number of days in worldly top ten affected countries in the COVID-19 first wave. The number of days was counted between the date when the highest number of daily cases were witnessed and the date the first case was reported. Results: Percentage ratio analysis of total deaths till the day highest daily cases reported for each country both with total population and with accumulated cases up to the day of the highest number of cases. It is evident from Figure 7 (a) that the highest mortality rate is 0.1 percent of the population which is very low compared with total deaths of 3% reported so far worldwide 3-4. Moreover, the mortality rate with accumulated cases is found in 1 to 5 percent except for Peru which is 12 percent. Conclusion: In this research, the work period is considered in terms of the number of days for all regions for peak and found that an average (178.10__ampersandsignplusmn;10.92) days took to reach the highest number of COVID-19 cases. Moreover, for most regions inversely proportional trend is observed between the highest number of daily cases and the total number of days to reach the peak. However, it is found that temperature is not correlated with the increase or decrease of daily cases and the number of days to attain peak.