Abstract
Pandemics pose significant threats to social, economic, and public health. The novel coronavirus (COVID-19), which emerged in late 2019, quickly became a global public health crisis due to its high contagion and pathogenicity. Using data from the World Health Organization (WHO), this study applied the Logistic model to analyze the spread patterns of COVID-19 in 16 countries with over 10 million infections from 2020 to 2023. The findings reveal that as of December 31, 2023, global infections exceeded 772 million with over seven million deaths. The USA and China had the highest infection numbers, while Brazil had the highest mortality rate. The study identified three main outbreak patterns: initial, late, and gradual development, reflecting different stages of the pandemic. Countries with earlier outbreaks, such as India, Brazil, the USA, and Argentina, generally had higher mortality rates, while those with later outbreaks, such as China, Pakistan, Japan, and Australia, had lower mortality rates. Significant differences were observed in the duration and speed of the spread, with China showing the shortest average duration and Russia the longest. The Logistic model's parameter k values revealed policy adjustments, with Australia, Vietnam, and China showing significant changes over time, while the USA, France, and Russia showed less impact on epidemic control. These results provide an important perspective for understanding global pandemic transmission patterns and assessing the effectiveness of quarantine strategies across countries. They also provide a scientific basis for future public health policy and pandemic response development, helping countries to develop more targeted prevention and control strategies according to the characteristics of virus transmission, rationally allocate medical resources, and reduce social harm.