Constructing protective mechanism by analysis of vaccine impact based on hybrid model of dynamic DEA and cluster tendency

COVID-19 was announced as a public health emergency of international concerns by WHO in January 2020 and many global scientists started to develop vaccines to stop the spread of COVID-19. This study aims to analyze the effectiveness of vaccination to confirmed cases and deaths. This paper analyzed the impact of vaccines on COVID-19 from 17 selected countries and considered the impact of vaccines in epidemic prevention for evaluating the efficiency of epidemic prevention by establishing three scenarios. Firstly, we used the undesirable output model to analyze the impact of the number of confirmed cases and death as undesirable output to assess the policy effect. Then, we considered the vaccination rate as a carryover and used dynamic Data Envelopment Analysis to evaluate efficiency. Finally, the mortality variable was excluded to examine the impact of vaccines on mortality. 17 countries were classified via clustering analysis into three group based on elbow point plot. There are two countries ranked the best performance based on dynamic Data Envelopment Analysis in each group. It indicated that the countries with the same characteristics can improve their performance in preventing pandemic by learning the countries with similar characteristics. The vaccine administration is the main strategy for epidemic prevention. Furthermore, preventive measures are essential. In the post-epidemic era, government should reduce the mortality rate and main the medical system to ensure public welfare.