Evaluation of the Performance of world Countries' Health Systems in the Face of Covid-19 in Respect of Vaccination Role

Background. Since the beginning of the Covid-19 epidemic, many countries have been involved in fighting the disease. The outbreak of this disease has caused irrecoverable damages to countries in various aspects such as human resources, economic situation, and social welfare. The purpose of this study was to evaluate the performance of world countries in the face of covid-19 in respect of the role of vaccination and to propose applicable approaches for countries with lower performance. Methods. In this research, a three-phase method was developed to evaluate the performance of 88 countries in the face of Covid-19. In the first phase, the countries were clustered, using the k-means algorithm. In the second phase, the data envelopment analysis model was implemented once on the clusters and then on all the countries without considering the clusters. In the third phase, after presentation of the concept of resilience in the Covid-19 era, an Analytic Hierarchy Process was implemented with three criteria, including the results of data envelopment analysis model without considering the clusters, the results of data envelopment analysis model considering the clusters and resilience, and then the ranking of the countries' performance in the face of Covid-19 was provided. Results. Based on the results, 15 performance scores were obtained for the countries in the face of Covid-19, among which China, Fiji, Seychelles, Kyrgyzstan and Tanzania had the highest rankings and Bangladesh, Nepal, Georgia and Pakistan had the lowest performance levels. Iran is in the sixth place and in the average performance position of the countries. Conclusion. Based on the findings of this study, the countries with low performance level in the face of Covid-19 need to apply various strategies in different areas in order to improve their performance level. These strategies include planning and approval of joint programs to control and prevent the spread of disease, applying quarantine policy and restrictions on communities, planning and implementation of appropriate strategies regarding the export and import of drugs and medical equipment, allocating appropriate funds to research projects on Covid-19, banning the export of drugs effective in the treatment of Covid-19, and providing accurate and up-to-date information for raising people’s awareness. Background Since the beginning of the Covid-19 pandemic, many countries have been involved in fighting 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 of this disease has caused a lot of damage to the society and the economy of the countries, which can be examined at different levels such as social, economic, environmental and psychological damages. The illness not only causes a person to temporarily leave the society, but also imposes a lot of costs on the country, such as the costs of treatment, lost labor, spreading the disease caused by the sick person, and so on. Therefore, there is a need to review and evaluate the performance of the countries in dealing with this disease. Accordingly, the purpose of this study was to evaluate the performance of countries in the face of Covid-19 by considering the role of vaccination, so that applicable strategies and suggestions can be provided to help the countries with lower performance to improve their performance. MethodsIn this research, a three-phase method was developed to evaluate the performance of the countries in the face of Covid-19. In the first phase, the countries were clustered 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, and in the third phase, after 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 data envelopment analysis model without considering the clusters, the results of data envelopment analysis model considering the clusters and the resilience, and then the ranking of the countries' performance in the face of Covid-19 was provided.Based on the studies and analyses, the total number of corona deaths, the percentage of extreme poverty in the community, the CVD death rate, the percentage of the diabetes prevalence, the percentage of female smokers, the percentage of male smokers, stringency index, and the total number of patients with Covid-19 were selected as input parameters, while the total number of vaccinations, the total number of corona tests, population, the number of hospital beds, and GDP were selected as output parameters.After removing the countries with missing data, 88 countries remained which were analyzed in the three-phase method. Results In the phase 1 of the proposed three-phase method, considering 3 clusters and applying the k-means algorithm, 31 countries are in the first cluster, 37 countries are in the second cluster and 20 countries are in the third cluster. In the second phased, the DEA model was implemented once on the clusters and again on all the countries without considering the clusters and the efficiency of the countries was obtained, based on the results of which a number of 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 data envelopment analysis model implemented on clusters" was three times the "result of the data envelopment analysis model implemented on countries", because it was expected that if similar countries are considered together and the DEA model is implemented on them, it would lead to more accurate results. In this matrix, the importance of "resilience" was twice as high as the "result of data envelopment analysis model implemented on countries" and finally, the importance of "result of data envelopment analysis model on clusters" and "resilience" were considered as the same. Based on the results, 15 performance scores were obtained for the countries, among which China, Fiji, Seychelles, Kyrgyzstan and Tanzania had the highest rankings and Bangladesh, Nepal, Georgia and Pakistan had the lowest performance levels. Conclusion Based on the results, 15 performance rankings were obtained for the countries, where Iran along with 11 other countries were in the sixth place, which indicated the average performance of Iran. In general, 26 countries performed below the average AHP rate of all countries. In this regard, the strategies of the countries with better performance can be used as a benchmark in order to improve the performance of the lower-ranking countries. Accordingly, the countries with lower performance should improve their performances by emulating the policies of higher performance 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 Considering various factors such as efficiency and resilience, countries have different performance in the face of Covid-19, and lower efficiency and resilience has led to poorer performance of the countries. 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, in order to improve their performance status. Ethical Considerations This paper is taken from the dissertation of M.Sc. of Industrial Engineering at Sharif University of Technology and all the ethical principles related to scientific research have been met in all stages of design, implementation, analysis and compilation of the results. Conflict of Interest The authors declare that they have no conflict of interest in publishing this paper. Acknowledgments This paper is taken from the dissertation of M.Sc. of Industrial Engineering of Sharif University of Technology, approved on September 25, 2020, and in this regard, the authors express their gratitude and appreciation to all those who participated in completing this research.