Evaluation of the Performance of World Countries' Health Systems in the Face of COVID-19 in Respect of Vaccination Role

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Extended Abstract
Background
Since the outbreak of the COVID-19 pandemic, many countries have participated in the fight against the disease. The disease was so rapidly transmitted that in just four months since its outbreak in Wuhan, China, about 120 million people worldwide had been infected, and about 2.7 million had died. The outbreak has substantially damaged countries at different levels such as social, economic, environmental, and psychological. The illness not only forces a person to temporarily leave the society, but also imposes significant costs on the country, such as the costs of treatment, lost labor, and the potential for the disease to spread. Therefore, there is a need to review and evaluate the performance of the countries in dealing with this disease. Accordingly, this study aimed to evaluate the performance of countries in the face of COVID-19 by considering the role of vaccination, so that practical strategies and suggestions can be offered to assist low-performance nations in improving their performance.
Methods
This research developed a three-phase method to evaluate the performance of the countries in the face of COVID-19. In the first phase, we clustered the countries using the k-means algorithm. In the second phase, the Data Envelopment Analysis (DEA) model was implemented once on the clusters and then on all the countries without considering the clusters. Finally, in the third phase, after the presentation of the concept of resilience in the COVID-19 era, an Analytic Hierarchy Process (AHP) model was implemented with three criteria, including the results of DEA model without considering the clusters, the results of DEA model considering the clusters and the resilience, and presented the ranking of the countries' performance in the face of COVID-19.Based on the prior studies and analyses, the input parameters included the total number of coronavirus deaths, the percentage of extreme poverty in the community, the cardiovascular disease (CVD) death rate, the percentage of diabetes prevalence, the percentage of female smokers, the percentage of male smokers, stringency index, and the total number of patients with COVID-19, while the total number of vaccinations, the total number of COVID-19 tests, population, the number of hospital beds, and GDP were selected as output parameters.The three-phase procedure was applied to 88 nations after excluding those with missing data.
Results
In phase 1 of the proposed three-phase method, 31 countries assigned to the first cluster, 37 countries to the second cluster and 20 countries to the third cluster using 3 clusters and applying the k-means algorithm. In the second phase, the DEA model was applied twice, once on the clusters and once on all the countries without considering the clusters. Also, based on the results, several countries were recognized as efficient. Therefore, the pandemic resilience index was introduced for improving and obtaining a better ranking of the countries. In the third phase, the AHP model was implemented in which the importance of the “result of the DEA model implemented on clusters” was three times that of the “result of the DEA model implemented on countries”, because it was expected that implementing the DEA model on the countries with the same performance level would yield more accurate results. In this matrix, the importance of “resilience” was twice as high as the “result of DEA model implemented on countries” and finally, the importance of “result of DEA model on clusters” and “resilience” were considered as the same. Based on the results, 15 performance scores were obtained for the countries, with China, Fiji, Seychelles, Kyrgyzstan, and Tanzania ranking best and Bangladesh, Nepal, Georgia, and Pakistan ranking lowest.
Conclusion
Based on the results, 15 performance rankings were obtained for the countries where Iran and 11 other countries were in sixth place, indicating Iran’s average performance. In general, 26 countries performed below the average AHP rate of all countries. In this regard, the strategies of higher-ranking countries may be used as a benchmark to improve the performance of lower-ranking countries. Accordingly, lower-performing countries should improve their performance by adopting policies similar to those of higher-performing countries in terms of general strategies, economic strategies, resource management strategies, training programs in the coronavirus era, and case reporting and monitoring.
Practical Implications of Research
Nations' responses to COVID-19 vary depending on several criteria, including efficiency and resilience. Those countries with weaker efficiency and resilience scored worst. Accordingly, the countries with lower performance should follow the policies of the higher performance ranking countries in terms of general strategies, economic strategies, resource management strategies, training programs in the coronavirus era, and case reporting and monitoring.
Ethical Considerations
At all stages of the design, execution, analysis, and compilation of the data in this study, which is based on a dissertation for a Master of Science in Industrial Engineering at Sharif University of Technology, all ethical criteria related with scientific research have been met.
Conflict of Interest
The authors declare that they have no conflict of interest in publishing this paper.
Acknowledgments
This work is based on the dissertation of M.Sc. of Industrial Engineering at Sharif University of Technology, which was authorized on September 25, 2020, and the authors would like to express their thanks and appreciation to everyone who helped them complete this study.