Iranian Journal of Medical Microbiology

This descriptive-analytical research was performed with the Scientometrics approach and content analysis method along with co-word analysis, hierarchical clustering, strategic chart, co-authorship, and social network analysis. Co-word analysis utilized in the current study was one of the content analysis methods. In network analysis, centrality indices that show the location of a node relative to other nodes in scientific maps are used. The statistical population of the present study included all investigations on the COVID-19 vaccine in WOS in categories related to medicine and health domains during 019-2021.
For the accurate recognition and retrieval of related researches, diverse combinations and names of COVID-19, as well as the words and terms related to the vaccine were identified using a thesaurus and medical subject headings (MeSH). Next, applying Boolean operators, truncation, and the following multistage search approach, the studies in the consid-ered field were retrieved on 16 April 2021, including 6005 studies in text format in the world and 196 studies in text format in Iran:
((TS="COVID-19") OR (TS="coronavirus disease 2019") OR (TS="novel coronavirus") OR (TS="2019 ncov") OR (TS="coronavirus 2019") OR (TS="new coronavirus") OR (TS="Sars-Cov 2") OR (TS="nCoV-19")) AND (TS=Vaccin*)
It should be noted that Clarivate Analytics has determined the maximum download records as 500. Therefore, data extraction was performed in 14 steps. Following the retrieval of related records and data integration, data were analyzed by the Histcite, Bibexcel, Gephi, UCINET, and SPSS software according to the aims and questions of the research. The maps were drawn utilizing the VOSviewer software version 1.6.10. The subjective maps and analysis were carried out following the control and integration of keywords by thesaurus generation in the software as similar and identical keywords, and single and plural forms were merged and non-specialized keywords were removed.
Hierarchical clustering is applied for co-word anal-ysis, which can determine the clusters related to each keyword and indicate the relationships between them. As a result, hierarchical clustering was perfor-med using the SPSS software. In the hierarchical clust-ering method, similar to a tree, each small branch is a component of a larger branch and finally, all these are connected to the tree trunk hierarchically. In sum-mary, the following steps should be passed:
1. Each item should be regarded as a cluster.
2. Among all possible cluster pairs, the two clusters with lower ESS are selected.
3. The two selected clusters are combined.
4. Steps 2 and 3 are repeated until all items are in one cluster or the number of clusters reaches the considered number.
In order to execute and finalize the co-occurring analysis, first, some necessary items, including co-occurring matrix are prepared. Afterwards, the co-occurring matrix is converted to a relationship matrix. To prepare the matrix, keywords with the frequency of 2 and 26 were selected for studies from Iran and other countries, respectively. Finally, rectangular matrices of 69×69 and 70×70 were made for invest-igations in Iran and other countries, respectively. The diagonal cells of matrices were considered zero and these matrices were converted to relationship matri-ces. The clustering of concepts was completed by the SPSS software version 26.
In the next step, the strategic chart of subjective clusters was depicted. To this aim, the centrality and density of clusters were obtained by the UCINET software after forming separated matrices for the keywords of each cluster retrieved by a hierarchical chart. A strategic chart is a description of internal relations and correlations between distinct clusters. In this chart, the horizontal axis is commonly utilized to present centrality (the relationship between clusters) and the vertical axis is used to give density (the internal relations of each cluster). 

Our results demonstrated that during 2019-2021, 6005 studies by 29473 authors affiliated to 7988 scientific institutes from 147 countries were indexed in the WOS. Iran with 196 related studies by 1583 authors affiliated to 635 universities and scientific institutes with the cooperation of 76 countries has the tenth-ranked among the involved countries. Investi-gations in the world have been identified to have diverse designs. According to Table 1, more than 80% of publications were in journals and other studies were recorded in the “others” group.  
Furthermore, data analysis revealed that the domin-ant language for science production in this domain is English and covers 97.2% of the studies. In addition to English, research in this field has been published in 14 other languages, the most important of which are German (0.8%), Spanish (0.7%), and French (0.3%). On the other hand, the evaluation of studies in Iran demonstrated that all were published in English and four designs of “evaluation, article, editor’s note, and letter to the editor”. Harvard Medical School and the University of Oxford in the world and Shahid Beheshti University of Medical Sciences and Tehran University f Medical Sciences in Iran had the highest cooperation. K. Dhama and E. mahase in the world and N Rezaei and ATB Abadi in Iran had the most studies. United States department of health human services provided the best financial support of researches in this field in the world and Tehran University of Medical Sciences provided the best support in Iran.
Co-word clustering of the studies in the world and Iran on COVID-19 vaccine using the VOSviewer led to the formation of seven clusters. Four out of these seven identified clusters (yellow, green, red, and purple) entailed diverse concepts and words, namely “Infection, Pneumonia, Pandemic, Spike protein, SARS, Protein, Transmission, Chloroquine, Convales-cent plasma, and ACE 2”. Therefore, these clusters were in a central and remarkable position because of repeated and common keywords with the most important interests of researchers of this domain in the world being in this cluster. Three of the seven clusters identified in Iran studies (blue, red, and purple) encompassed keywords “Spike protein, SARS, Infection, Pneumonia, Pandemic, Treatment, Conva-lescent plasma, ACE 2, and Cytokine storm” had a central and considerable position.
Hierarchical clustering in investigations in the world resulted in the formation of three clusters, including vaccine development approach, medical prevention, and immunotherapy. Among the three identified clusters related to world studies, the clusters vaccine development strategy and medical prevention were developed. On the other hand, the immunotherapy cluster is an emergent cluster with less important clusters that attract less attention. The hierarchical clustering in studies in Iran led to four clusters, namely immunotherapy, diagnosis and treatment cycle, medi-cal prevention, and immunology.
Among four identified clusters, “diagnosis and treatment cycle” and “immunology” clusters were developed but not central clusters. On the other hand, the immunotherapy cluster is emergent with less important subjects. The medical prevention cluster is central but not developed. In other words, this cluster is not mature yet.
Scientific collaboration in the country at the level of world and Iran studies led to five clusters. Although the USA, India, and China had most investigations, most links were for England and the USA, as shown in Figure 3. Moreover, clusters green and blue are of a central role because remarkable nations are in these clusters. It is noteworthy that Iran, China, Canada, and Saudi Arabia are in the same cluster. Iran cooperated with 76 countries in this field. In addition, Iran had the most cooperation with the USA and India in this domain.
Furthermore, the results of the current study revealed that 17 and 10 clusters resulted from scientific collaboration at the level of institutes in the world and Iran, respectively. According to Figure 5, most studies and links were related to the University of Oxford and Harvard Medical School. Clusters orange, green, and pink were in a central and impor-tant position because active institutes were in these clusters. In terms of citation, the three institutes Nati-onal Institute of Allergy and Infectious Diseases, Fred Hutchinson Cancer Research Center, and Pasteur Insti-tute were in the third ranks.
In the domain of Iran studies, although Tehran University of Medical Sciences and Shahid Beheshti University of Medical Sciences equally had the most studies and relationships, Shahid Beheshti University of Medical Sciences received the highest citations. As could be seen in Figure 6, clusters yellow and pink are regarded among important and central clusters due to possessing active Iranian institutes. Moreover, 10 and 8 clusters were formed by scientific collaboration at the level of researchers in studies in the world and Iran, respectively.
In the network of the cooperation of world researchers, although K. Dhama and E. Mahase had the most investigations and S. Ralph had the most studies and links. Regarding citations, S. Jason with seven investigations was in the first rank. Clusters brown and red were the important and central clusters in the cooperation of researchers due to the best researchers being in these clusters. According to the findings, K. Dhama, R. Tiwari, and P. Kumar had the best ranks in terms of centrality among world researchers.
In terms of closeness centrality, G. Iacobucci, E. Mahase, and Y. Liu had the best ranks. In addition, Y. Liu, S. Khan, and C. Atyeo were ranked 1-3 in bet-weenness centrality. In the cooperation network of researchers in Iran, Nima Rezaei received the most citations. Amin Talebi and Farid Rahimi made more relations, compared to other researchers, and formed a cluster with two nodes. However, other clusters had one member. Among Iran researchers, Mansournia, Soltani, and Rezaei had the highest centrality, and Akbari, Nabavi, and Ghaffari had the highest closeness centrality. Furthermore, Mansournia, Baradaran, and Eftekhari had the highest betweenness centrality.
Concerning the remarkable countries in the production and publication of studies, the results of the present investigation were in line with the findings of Surulinathi et al. (27) and Ahmad et al. (29). In addition, our results in terms of active researchers and institutes in this field were consistent with the findings of Ahmad et al. (29) and Ay et al. (30). In terms of the location of published studies and active institutes in the COVID-19 vaccine domain, the findings of the current investigation were congruent with the research of Ahmad et al. (29). Immunology, internal medicine, and experimental medical studies had the highest share in COVID-19 studies, especially in Iran. The latter finding is also consistent with the study performed by Ay et al. (30).

Considering the high prevalence of COVID-19 and increased mortality throughout the world, research on the COVID-19 vaccine in different aspects has become the priority of governments, scientific centers, and researchers in the world. Analysis and comparison of studies in the world and Iran in the field of COVID-19 vaccine in terms of subject and scientific collaboration lead to a better understanding of involved groups aimed to elevate investigations quantitatively and qualitatively followed by COVID-19 control in the shortest possible time. In other words, subjective analysis of studies and scientific collaboration can clarify the common subjects, in addition to identifying the existing limitations and activists. Consequently, the present situation is understood, and scientific, managerial, and executive policies are enhanced. As a result, novel research pathways might emerge.
Considering the importance of the COVID-19 vaccine and the published studies in this field, practical steps could be taken to further benefit in line with the international science borders. Some of these steps may entail identifying distinct aspects, proce-dures, tools, and technologies in the field of the COVI-D-19 vaccine based on the recognized words and con-cepts. Afterwards, planning and preparation could be completed using these steps in related execution and research projects. Based on the current study, the foll-owing recommendations could be made for future studies:
Subjective analysis of studies in this field in other indexing databases, such as Scopus and Google Scholar to evaluate research in this domain in the world and Iran comprehensively.
Analysis of the content, concepts, and words of scientific documents related to COVID-19 vaccine in scientific databases in Persian in Iran and comparison of the structure of studies in Iran and the world.
Analysis of the content, concepts, and words of scientific documents in obtained domains and clusters from Iran and the world to identify the existing limitations.

We would like to extend our gratitude to Dr. Alireza Norouzi who guided the authors of the present study.

Conflicts of Interest

The authors did not report any conflict of interest.