Literature DB >> 32934940

Bibliometric analysis of global scientific research on Coronavirus (COVID-19).

Hojat Dehghanbanadaki1, Farhad Seif2, Yasmin Vahidi3, Farideh Razi4, Ehsan Hashemi5, Majid Khoshmirsafa6, Hossein Aazami7,8.   

Abstract

Background: Since the outbreak of the novel coronavirus disease from Wuhan, China, in early December 2019, many scientists focused on this infection to find a way to deal with it. Due to the dramatic scientific growth in this field, we conducted a scientometric study to gain a better understanding of the scientific literature on COVID-19.
Methods: We extracted all COVID-19 documents indexed in the Scopus from December 1, 2019, to April 1, 2020, without any language limitation and determined their bibliometric characteristics, including document type, open accessibility status, citation counting, H-index, top cited documents, the most productive countries, institutions and journals, international collaboration, the most frequent terms and keywords, journal bibliographic coupling and cocitations.
Results: A total of 923 documents on COVID-19 were retrieved, of which 418 were original articles. All documents had received 2551 citations with an average citation of 2.76 per document and an h-index of 23. China ranked first with 348 documents, followed by the United States (n = 160). The Lancet and BMJ Clinical Research Ed published the most documents (each with 74 documents) and 2 institutions (University of Hong Kong and Huazhong University of Science and Technology) ranked first in this regard. In addition, the present study analyzed the top 25 highly-cited documents (those that had received 70% of all citations).
Conclusion: This study highlighted the focused subjects on various aspects of COVID-19 literature such as pathogenesis, epidemiology, transmission, diagnosis, treatment, prevention, and its complications.
© 2020 Iran University of Medical Sciences.

Entities:  

Keywords:  Bibliometrics; COVID-19; Novel Coronavirus; SARS-CoV-2; Scientometrics

Year:  2020        PMID: 32934940      PMCID: PMC7481853          DOI: 10.34171/mjiri.34.51

Source DB:  PubMed          Journal:  Med J Islam Repub Iran        ISSN: 1016-1430


↑ What is “already known” in this topic:

In early December 2019, the novel coronavirus (COVID-19) causing a cluster of pneumonia of unknown etiology originated from Wuhan, China, and spread rapidly throughout the world. The WHO (World Health Organization) changed the status of COVID-19 outbreak from epidemic into pandemic on March 11, 2020.

→ What this article adds:

Since the emergence of COVID-19, the number of publications on this topic has dramatically grown. About 84% of COVID-19 documents are open-access. The focus of COVID-19 literature in terms of countries, journals, institutions, terms, and keywords which all were discussed in detail sets out the research hotspots and important topics in this field.

Introduction

In early December 2019, an outbreak of viral infection associated with pneumonia was initiated in Wuhan, Hubei Province, China (1, 2). Severe acute respiratory syndrome-Coronavirus 2 (SARS-CoV2) was identified as the cause of COVID-19, which was characterized by asymptomatic to severe infections in respiratory and gastrointestinal systems, kidneys, and heart (3). Since the outbreak of COVID-19 worldwide, the number of cases has risen dramatically. Due to the rapid spread of COVID-19, the WHO has announced it as an urgent public health concern (4). Thus, the present study aimed to conduct a bibliometric analysis on COVID-19 articles worldwide from December 1, 2019 to April 1, 2020 to achieve the following goals: (a) to analyze the highly-cited articles in this field, (b) to present top countries, institutions, and journals, (c) to map the co-occurrences and keywords related to COVID-19, (d) to map co-contributions’ network among countries, and (e) to map the bibliographic coupling and cocitation of journals for guiding other researchers about the direction of future COVID-19 articles.

Methods

Data retrieval

In this bibliometric study, we extracted all COVID-19 disease documents indexed in the Scopus from December 1, 2019, to April 1, 2020, without considering any language limitation. We searched the following queries in the Scopus database: (sars2) OR (sars-2) OR ("SARS 2") OR ("novel corona virus pneumonia") OR ("new human coronavirus") OR ("2019 novel coronavirus") OR ("2019 novel coronavirus infection") OR ("novel coronavirus") OR ("new coronavirus") OR ("severe acute respiratory syndrome coronavirus 2") OR ("sudden acute respiratory syndrome coronavirus 2") OR ("China coronavirus") OR ("Wuhan coronavirus") OR ("Wuhan seafood market pneumonia virus") OR (covid-19) OR ("COVID19 virus") OR ("Coronavirus disease 2019") OR TITLE-ABS ("coronavirus disease-19") OR ("Coronavirus disease 2019 virus") OR ("SARS-CoV-2") OR ("2019-nCoV") OR ("2019-nCoV disease") OR ("2019-nCoV infection"). Through this search strategy, 923 documents related to COVID19 were retrieved and different bibliometric aspects of all of these documents were investigated, which included document type, open accessibility of documents, citation counting, average citations per document, H-index, top cited documents, document distribution around the world, the most productive countries, institutions and journals, collaboration between countries, the most frequent terms in the titles and abstracts, the most applying keywords, bibliographic coupling, and cocitations of journals.

Data analysis

Following the completion of data extraction, we exported all data into Microsoft Excel for statistical analysis and ranking various bibliometric indices, including top cited documents, top countries, institutions, and journals. We used GunnMap 2 (http://lert.co.nz/map/) to illustrate the worldwide distribution of documents and VOSviewer software (version 1.6.13) (5) to visualize the connection between terms, keywords, countries, and the rainbow density map of bibliographic coupling and journal cocitation. The bibliographic coupling of journals in the literature of COVID-19 reveals how many COVID-19 articles of 2 journals had been bibliography coupled. In other words, when 2 articles cite the same document in their bibliographies, they are bibliographically coupled; thus, the journal cocitation analysis indicates the number of COVID-19 articles cocited in 2 given journals (6).

Results

Through searching in the Scopus database, we extracted 923 documents written about COVID-19 from its emergence to April 1, 2020. Almost half (n = 418) of the retrieved documents were original articles and the remaining were 151 letters, 134 notes, 116 editorials, 75 reviews, 14 errata, 14 short surveys, and 1 data paper. Among all documents, 775 (83.96%) were open access. The total citations to all documents were 2551 times with average citations per document of 2.76 and h-index of 23. The total number of citations of original articles and reviews (n = 493) was 1895, with an average citation of 3.84 per document and h-index of 19. The global distribution of COVID-19 documents is depicted in Figure 1. In addition, Table 1 lists the first top 10 countries in the number of COVID-19 documents as well as the number of their COVID-19 confirmed cases. China accounted for the most productive country with 348 scientific documents around the world and the number of its published documents was more than twice that of the second-ranked country, the United States, with 160 documents. The other top countries with the most documents were the United Kingdom (n = 80), Italy (n = 47), Canada (n = 44), Hong Kong (n = 35), Germany (n = 34), France (n = 33), Switzerland (n = 31), Australia (n = 26), and South Korea (n = 26). On the other hand, top 10 countries based on the number of their COVID-19 confirmed cases were the United States (n =163 199 cases), Italy (n = 105 792), Spain (n = 94 417), China (n = 82 638), Germany (n = 67 366), France (n = 51 477), Iran (n = 47 593), the United Kingdom (n = 25 154), Switzerland (n = 16 108), and Turkey (n =13 531).
Fig. 1
Table 1

Top 10 countries in the number of COVID-19 documents and the number of COVID-19 confirmed cases up to April 1, 2020

RankCountryNumber of publicationsRankCountryConfirmed casesDeaths
1China3481United States1631992850
2United States1602Italy10579212430
3United Kingdom803Spain944178189
4Italy474China826383321
5Canada445Germany67366732
6Hong Kong356France514773514
7Germany347Iran475933036
8France338United Kingdom251541789
9Switzerland319Switzerland16108373
10Australia2610Turkey13531214
10South Korea26
The global distribution of COVID-19 scientific documents indexed in Scopus for country. The color of each country represents the number of its publications on COVID-19 In addition, to illustrate the international collaboration between all 125 countries that published COVID-19 documents, we considered the countries with at least 5 documents (n = 32). We demonstrated the international collaboration network between these 32 countries in Figure 2. The network mapping indicated a total of 241 international collaborations with the strongest collaboration between China and the United States. Furthermore, each country in this network is illustrated with different colors, representing the number of average citations per document that has been received by them. The highest average citations per document regardless of the number of publications and collaborations belonged to Denmark (n = 8), Belgium (n = 7.2), Australia (n = 5.48), Hong Kong (n = 5.41), Netherlands (n = 5.38), China (n = 5.15), and Germany (n = 4.91). Although the United States ranked second in the number of documents, it received an average of 2.78 citations per document.
Fig. 2
The international collaboration network between the 32 countries with at least 5 COVID-19 documents is indicated. Through this network mapping, we realized there were a total of 241 collaborations with the strongest collaboration link between China and the United States. The color of each country represents the number of average citations per document that has been received by them and the size of each node represents the number of publications that has been published by that country. The first top 10 institutions affiliated with the retrieved documents are depicted in Table 2 that shows authors from The University of Hong Kong and Huazhong University of Science and Technology published most documents on this new emerging virus.
Table 2

The first top 10 institutions involved with COVID-19 documents

RankAffiliationNumber of publication
1The University of Hong Kong30
1Huazhong University of Science and Technology30
2Tongji Medical College28
3Chinese Academy of Sciences25
4Wuhan University23
5Capital Medical University22
5School of Medicine22
6London School of Hygiene & Tropical Medicine20
7Fudan University19
8Chinese University of Hong Kong17
8The University of Hong Kong Li Ka Shing Faculty of Medicine17
8Chinese Academy of Medical Sciences & Peking Union Medical College17
9Zhejiang University School of Medicine16
9Zhongnan Hospital of Wuhan University16
10Zhejiang University15
10University of Toronto15
We also ranked the journals by which these documents have been published and we realized that most of these documents were published in highly prestigious journals (Table 3), including the Lancet (n = 74 documents), BMJ Clinical Research Ed (n = 74 documents), and Journal of Medical Virology (n = 47 documents).
Table 3

The first top 10 journals that published COVID-19 documents

RankJournalNumber of Publications
1BMJ Clinical Research Ed74
1The Lancet74
2Journal of Medical Virology47
3Euro Surveillance Bulletin Europeen Sur Les Maladies Transmissibles European Communicable Disease Bulletin26
4JAMA Journal of The American Medical Association21
5Lancet Infectious Diseases20
6Travel Medicine And Infectious Disease15
7BMJ14
7Emerging Microbes And Infections14
7Intensive Care Medicine14
8Journal of Korean Medical Science13
8Zhongguo Dang Dai Er Ke Za Zhi Chinese Journal of Contemporary Pediatrics13
9Journal of Infection12
9New England Journal of Medicine12
10Nature11
The citation counting of all documents on COVID-19 discovered that many researchers were interested in 25 documents listed in Table 4.
Table 4

Top COVID-19 documents that received the most citations

RankAuthorTitleSource titleCitationsArticle typeCiteScore
1Huang CClinical features of patients infected with 2019 novel coronavirus in Wuhan, ChinaThe Lancet250Article10.28
2Zhu NA novel coronavirus from patients with pneumonia in China, 2019New England Journal of Medicine180Article16.10
3Li QEarly Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected PneumoniaThe New England journal of medicine154Article16.10
4Chen NEpidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive studyThe Lancet135Article10.28
4Chan J.FA familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family clusterThe Lancet135Article10.28
5Wang DClinical Characteristics of 138 Hospitalized Patients with 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, ChinaJAMA - Journal of the American Medical Association111Article6.98
6Zhou PA pneumonia outbreak associated with a new coronavirus of probable bat originNature105Article15.21
7Lu RGenomic characterization and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor bindingThe Lancet97Article10.28
8Holshue M.LFirst case of 2019 novel coronavirus in the United StatesNew England Journal of Medicine66Article16.10
9Rothe CTransmission of 2019-NCOV infection from an asymptomatic contact in GermanyNew England Journal of Medicine62Letter16.10
10Wang CA novel coronavirus outbreak of global health concernThe Lancet55Note10.28
11Wu J.TNowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modeling studyThe Lancet51Article10.28
12Hui D.SThe continuing 2019-nCoV epidemic threat of novel coronaviruses to global health — The latest 2019 novel coronavirus outbreak in Wuhan, ChinaInternational Journal of Infectious Diseases46Editorial2.89
13Wu FA new coronavirus associated with human respiratory disease in ChinaNature36Article15.21
14Ji WCross-species transmission of the newly identified coronavirus 2019-nCoVJournal of Medical Virology31Article1.94
15Wan YReceptor Recognition by the Novel Coronavirus from Wuhan: an Analysis Based on Decade-Long Structural Studies of SARS CoronavirusJournal of virology30Article4.02
15Wu ZCharacteristics of and Important Lessons from the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases from the Chinese Center for Disease Control and PreventionJAMA - Journal of the American Medical Association30Article6.98
16Chen HClinical characteristics and intrauterine vertical transmission potential of COVID-19 infection in nine pregnant women: a retrospective review of medical recordsThe Lancet29Article10.28
16Wang MRemdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitroCell Research29Letter8.58
16Corman V.MDetection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCREuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin29Article5.05
17Chen YEmerging coronaviruses: Genome structure, replication, and pathogenesisJournal of Medical Virology27Review1.94
18Munster V.JA novel coronavirus emerging in China - Key questions for impact assessmentNew England Journal of Medicine26Review16.10
18Chan J.F.WGenomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting WuhanEmerging Microbes and Infections26Article4.36
19Chung MCT imaging features of 2019 novel coronavirus (2019-NCoV)Radiology23Article5.83
20Xu XEvolution of the novel coronavirus from the ongoing Wuhan outbreak and modeling of its spike protein for risk of human transmissionScience China Life Sciences21Letter2.14
In other words, these 25 documents received the most citations among all documents (1784 times which comprise almost 70% of all citations) and they ranged from 21 to 250 citations. These documents consisted of 18 original articles, 3 letters, 2 reviews, 1 editorial, and 1 note, of which 7 were published in the Lancet, 5 in the New England Journal of Medicine, 3 in the Euro surveillance: European communicable disease bulletin (bulletin Europeen sur les maladies transmissibles), 2 in the JAMA (Journal of the American Medical Association), 2 in Nature, 2 in the Journal of Medical Virology, and 1 in each of the International Journal of Infectious Diseases, the Journal of Virology, the Cell Research, the Emerging Microbes and Infections, the Radiology and the Science China Life Sciences. The first document in this ranking was published by Huang C. et al (2) on January 24, 2020 and was about the clinical characteristics of COVID-19 infected patients. They reported the symptoms, signs, laboratory findings, imaging findings, underlying diseases, and complications of 41 infected patients and concluded that COVID-19 resulted in severe acute respiratory distress syndrome leading to a higher probability of ICU cases and death. The second document in this list was a case-control study by Zhu N et al (7) published in the New England Journal of Medicine on February 20, 2020 and received 180 citations until the date of data extraction. This study used high-throughput sequencing technology and real time reverse transcription PCR to determine the etiology of a cluster of patients with unknown origin pneumonia linked to the Huanan seafood wholesale market in Wuhan, China. They reported that this novel infection was caused by the seventh member of the coronavirus family. The third study by Li Q et al (8) was published in the New England Journal of Medicine on March 26, 2020, and revealed that although this novel coronavirus infected humans through zoonotic exposure, the outbreak of this infection was initiated by human to human transmission in Wuhan since the mid-December 2019. In this section, we investigated the terms used in the title and abstract of all COVID-19 documents and the keywords to discover the hotspot of this topic in the documents. The most frequent terms were COVID (n = 983 repeats), patient (n = 741 repeats), SARS-CoV (n = 593 repeats), China (n = 497 repeats), case (n = 464 repeats), nCoV (n = 417 repeats), outbreak (n = 355 repeats), infection (n = 344 repeats), novel coronavirus (n = 324 repeats), Wuhan (n = 269 repeats), Coronavirus (n =243 repeats), virus (n = 204 repeats), pneumonia (n = 195 repeats), Coronavirus disease (n = 170 repeats), treatment (n = 162 repeats), transmission (n = 158 repeats), study (n = 156 repeats), data (n = 151 repeats), country (n = 137 repeats), and epidemic (n = 136 repeats). Next, we visualized the connection network of terms applying at least 15 times in the titles and abstracts. Accordingly, 168 terms of all 8078 terms were entered into the network and clustered into 4 groups, which are demonstrated with different colors in Figure 3. The most frequent terms in each cluster are COVID (blue), SARS-CoV (red), patient (green), and infection (yellow), respectively.
Fig. 3
The connection network of terms applying at least 15 times in the titles and abstracts. A total of 168 terms of all 8078 terms were entered into this network and clustered into 4 groups, which are shown with different colors. The most frequent terms in each cluster are COVID (blue), SARS-CoV (red), patient (green), and infection (yellow), respectively. Similarly, the counting of author keywords revealed that the most co-occurrence keywords in COVID-19 documents are COVID-19 (n = 139 repeats), Coronavirus (n = 117 repeats), SARS-CoV-2 (n = 100 repeats), 2019-nCOV (n = 86 repeats), pneumonia (n = 34 repeats), epidemiology (n = 31 repeats), SARS (n = 24 repeats), novel Corona virus (n = 23 repeats), Wuhan (n = 22 repeats), outbreak (n = 21 repeats), infection (n = 18 repeats), SARS-CoV (n = 17 repeats), epidemic (n = 13 repeats), Coronavirus disease 2019 (n = 12 repeats), China (n = 12 repeats), MERS (n = 10 repeats), virology (n = 9 repeats), 2019 novel Coronavirus (n = 9 repeats), acute respiratory disease (n = 8 repeats), MERS-CoV (n = 8 repeats), transmission (n = 8 repeats), and diagnosis (n = 8 repeats). To visualize the connection network between author keywords, we considered only keywords with at least 5 co-occurrences and found out that 38 of 786 keywords were entered into the network and clustered into 6 groups (Fig. 4). The most frequent keywords in each cluster are 2019-nCOV (red), Coronavirus (green), COVID-19 (dark blue), epidemiology (yellow), novel Corona virus (purple), and SARS-CoV-2 (light blue), respectively.
Fig. 4
The connection network between author keywords with at least 5 co-occurrences. Out of 786 keywords, 38 were entered into this network and clustered into 6 groups, which are depicted in different colors. The most frequent keywords in each cluster are 2019-nCOV (red), coronavirus (green), COVID-19 (dark blue), epidemiology (yellow), novel coronavirus (purple), and SARS-CoV-2 (light blue), respectively. The bibliographic coupling of journals in the literature of COVID-19 reveals how many COVID-19 articles of 2 journals had been bibliography coupled. In other words, when 2 articles cite the same document in their bibliographies, they are bibliographically coupled. Figure 5 shows the bibliographic coupling map of journals with at least 5 COVID-19 documents. Out of 308 journals, 41 met this threshold and 32 constructed the largest coupling network (Fig. 5).
Fig. 5
The bibliographic coupling connection network of journals with at least 5 documents related to COVID-19. The bibliographic coupling of journals in the literature of 2019-nCOV reveals how many COVID-19 articles of 2 journals had been bibliography coupled. In other words, when 2 articles cite the same document in their bibliographies, they are bibliographically coupled. In addition, the results of journal cocitation analysis indicates the number of articles that cocited the COVID-19 articles of 2 given journals. In this regard, we visualized the cocitation rainbow density of journals with at least 20 citations in the literature of COVID-19 (Fig. 6).
Fig. 6
The cocitation rainbow density of journals with at least 20 citations in the literature about COVID-19. The journal cocitation analysis indicates the number of 2019-nCOV articles that were cocited in 2 given journals.

Discussion

In this study, we aimed to provide the perspective of COVID-19 documents in the world and identify our current position in the publication on this novel Coronavirus. We illustrated the hotspots of research on this topic so far and determined the origin of these documents from which countries, institutions, journals, and authors have arisen. This novel virus from the seventh membrane of the coronavirus family originated from Wuhan, Hubei Province, China, in early December 2019, causing a cluster of pneumonia with an unknown etiology that almost all patients linked to the Huanan seafood wholesale market (9). The WHO named this virus as COVID-19 on February 11, 2020, and declared it as a pandemic on March 11, 2020 (10). Since the emergence of COVID-19, the number of publications on this novel coronavirus has grown rapidly and different aspects of this infection such as epidemiology, pathogenesis, transmission, prevention, treatment, complications, prognosis, etc, attract much interest. Also, many promising documents have been published to date, most of which having been accepted and released by prestigious journals like the Lancet, BMJ Clinical Research Ed, the Journal of Medical Virology, the Euro Surveillance: European Communicable Disease Bulletin, and JAMA. We also observed that most of the top cited articles have been published in these journals. In addition, about 84% of the documents in this field were open access, with the purpose of understanding this novel infection sooner and decreasing this serious health threat in humankind. The country analysis based on the COVID-19 confirmed cases and the COVID-19 documents revealed that 7 out of top 10 countries with the most COVID-19 positive cases also worked the most in producing scientific documents and finding a solution for this pandemic. Spain, Iran, and Turkey which listed in the top countries with the most COVID-19 positive cases should pay more attention to this statistics in their policies. The analysis of the most frequent keywords applying in the literature of COVID-19 revealed some hotspots of focus during the study period. For example, this novel virus has been used under different names in this area, including COVID-19, Coronavirus, 2019-nCoV, SARS-CoV-2, and 2019 novel Coronavirus. In addition, during this time many studies have been conducted on the pathogenesis, epidemiology, transmission, and diagnosis of this virus; eg, (1) the similarity between this virus and other viruses from the Coronavirus family, such as SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome); (2) the role of quarantine for the infection control of COVID-19 outbreak; (3) the diagnostic ability of CT scan (computed tomography);(4) ARDS (acute respiratory distress syndrome) complication; and (5) the status of this virus in the world as an epidemic which after a while changed into a pandemic. Interestingly, angiotensin-converting enzyme 2 (ACE2) is the only substrate in this network, suggesting its potential effect on the novel Coronavirus disease. ACE2 plays a critical role in the renin-angiotensin system (RAS) through which converts the angiotensin (Ang) I into Ang (1-9) and Ang II into Ang (1-7), respectively (11, 12), and accordingly contributes to cardiovascular diseases such as coronary artery disease, hypertension, congestive heart failure, and myocarditis (13). Many studies suggested that this enzyme could be a potential target in Influenza infection (H1N1, H7N9 and H5N1), inducing acute lung injury (14-16) and Coronavirus infection (SARS, HCoV-NL63 and 2019-nCoV) mainly through binding to the viral spike glycoprotein, which was a highly-focused subject in our bibliometric analysis on the most frequent terms in the literature of 2019-nCoV (17-20). Therefore, ACE2 could be targeted to manage COVID-19 disease in future studies. However, some bibliometric studies on COVID-19 have been conducted so far (21-23) included fewer COVID-19 documents than ours due to earlier data extraction or the use of other databases. Therefore, this study provided the comprehensive perspective of the COVID-19 documents indexed in Scopus to date. Chahrour M et al (21) conducted a bibliometric analysis on 564 documents on COVID-19 that had been published until March 18, 2020. They reported that China and the United States published most of these documents (377 and 39 documents, respectively) and Singapore ranked first based on the number of the documents per million persons (n = 1.069). Hossain MM (22) also conducted a bibliometric analysis on 422 COVID-19 documents indexed in Web of Science (WoS) core collection until April 1, 2020 and reported that China, the United States, the United Kingdom, Italy, and Canada produced the most documents on COVID-19 (185, 68, 36, 23 and 23 articles, respectively). In addition, top journals with the most COVID-19 documents were British Medical Journal (n = 47), the Lancet (n = 37), Eurosurveillance (n = 22), and Journal of Medical Virology (n = 22). We found that their findings based on the searching in WOS database are consistent with the results of our analysis on the documents indexed in Scopus.

Conclusion

Since the emergence of COVID-19, many countries, journals, institutions, and researchers focused on this topic, which led to the rapid growing publications on this area of literature. To date, China, the United States, and the United Kingdom had the most scientific performance as well as international collaborations on COVID-19 research. The most published documents on COVID-19 were open access and were published in prestigious journals with high impact factors, including the Lancet, BMJ Clinical Research Ed, and Journal of Medical Virology. In addition, the present bibliometric analysis on COVID-19 literature shows the focused subjects in various aspects of this infection such as pathogenesis, epidemiology, transmission, diagnosis, treatment, prevention, and its complications.

Conflict of Interests

The authors declare that they have no competing interests.
  21 in total

1.  Software survey: VOSviewer, a computer program for bibliometric mapping.

Authors:  Nees Jan van Eck; Ludo Waltman
Journal:  Scientometrics       Date:  2009-12-31       Impact factor: 3.238

2.  Angiotensin-converting enzyme 2 (ACE2) mediates influenza H7N9 virus-induced acute lung injury.

Authors:  Penghui Yang; Hongjing Gu; Zhongpeng Zhao; Wei Wang; Bin Cao; Chengcai Lai; Xiaolan Yang; LiangYan Zhang; Yueqiang Duan; Shaogeng Zhang; Weiwen Chen; Wenbo Zhen; Maosheng Cai; Josef M Penninger; Chengyu Jiang; Xiliang Wang
Journal:  Sci Rep       Date:  2014-11-13       Impact factor: 4.379

3.  A pneumonia outbreak associated with a new coronavirus of probable bat origin.

Authors:  Peng Zhou; Xing-Lou Yang; Xian-Guang Wang; Ben Hu; Lei Zhang; Wei Zhang; Hao-Rui Si; Yan Zhu; Bei Li; Chao-Lin Huang; Hui-Dong Chen; Jing Chen; Yun Luo; Hua Guo; Ren-Di Jiang; Mei-Qin Liu; Ying Chen; Xu-Rui Shen; Xi Wang; Xiao-Shuang Zheng; Kai Zhao; Quan-Jiao Chen; Fei Deng; Lin-Lin Liu; Bing Yan; Fa-Xian Zhan; Yan-Yi Wang; Geng-Fu Xiao; Zheng-Li Shi
Journal:  Nature       Date:  2020-02-03       Impact factor: 69.504

4.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.

Authors:  Qun Li; Xuhua Guan; Peng Wu; Xiaoye Wang; Lei Zhou; Yeqing Tong; Ruiqi Ren; Kathy S M Leung; Eric H Y Lau; Jessica Y Wong; Xuesen Xing; Nijuan Xiang; Yang Wu; Chao Li; Qi Chen; Dan Li; Tian Liu; Jing Zhao; Man Liu; Wenxiao Tu; Chuding Chen; Lianmei Jin; Rui Yang; Qi Wang; Suhua Zhou; Rui Wang; Hui Liu; Yinbo Luo; Yuan Liu; Ge Shao; Huan Li; Zhongfa Tao; Yang Yang; Zhiqiang Deng; Boxi Liu; Zhitao Ma; Yanping Zhang; Guoqing Shi; Tommy T Y Lam; Joseph T Wu; George F Gao; Benjamin J Cowling; Bo Yang; Gabriel M Leung; Zijian Feng
Journal:  N Engl J Med       Date:  2020-01-29       Impact factor: 176.079

5.  A novel coronavirus outbreak of global health concern.

Authors:  Chen Wang; Peter W Horby; Frederick G Hayden; George F Gao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

6.  Clinical Characteristics of Coronavirus Disease 2019 in China.

Authors:  Wei-Jie Guan; Zheng-Yi Ni; Yu Hu; Wen-Hua Liang; Chun-Quan Ou; Jian-Xing He; Lei Liu; Hong Shan; Chun-Liang Lei; David S C Hui; Bin Du; Lan-Juan Li; Guang Zeng; Kwok-Yung Yuen; Ru-Chong Chen; Chun-Li Tang; Tao Wang; Ping-Yan Chen; Jie Xiang; Shi-Yue Li; Jin-Lin Wang; Zi-Jing Liang; Yi-Xiang Peng; Li Wei; Yong Liu; Ya-Hua Hu; Peng Peng; Jian-Ming Wang; Ji-Yang Liu; Zhong Chen; Gang Li; Zhi-Jian Zheng; Shao-Qin Qiu; Jie Luo; Chang-Jiang Ye; Shao-Yong Zhu; Nan-Shan Zhong
Journal:  N Engl J Med       Date:  2020-02-28       Impact factor: 91.245

7.  A Novel Coronavirus from Patients with Pneumonia in China, 2019.

Authors:  Na Zhu; Dingyu Zhang; Wenling Wang; Xingwang Li; Bo Yang; Jingdong Song; Xiang Zhao; Baoying Huang; Weifeng Shi; Roujian Lu; Peihua Niu; Faxian Zhan; Xuejun Ma; Dayan Wang; Wenbo Xu; Guizhen Wu; George F Gao; Wenjie Tan
Journal:  N Engl J Med       Date:  2020-01-24       Impact factor: 91.245

8.  Downregulation of angiotensin-converting enzyme 2 by the neuraminidase protein of influenza A (H1N1) virus.

Authors:  Xin Liu; Ning Yang; Jun Tang; Song Liu; Deyan Luo; Qing Duan; Xiliang Wang
Journal:  Virus Res       Date:  2014-03-21       Impact factor: 3.303

9.  Functional assessment of cell entry and receptor usage for SARS-CoV-2 and other lineage B betacoronaviruses.

Authors:  Michael Letko; Andrea Marzi; Vincent Munster
Journal:  Nat Microbiol       Date:  2020-02-24       Impact factor: 17.745

10.  Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus.

Authors:  Wenhui Li; Michael J Moore; Natalya Vasilieva; Jianhua Sui; Swee Kee Wong; Michael A Berne; Mohan Somasundaran; John L Sullivan; Katherine Luzuriaga; Thomas C Greenough; Hyeryun Choe; Michael Farzan
Journal:  Nature       Date:  2003-11-27       Impact factor: 49.962

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  19 in total

1.  Scientometric assessment of scientific documents published in 2020 on herbal medicines used for COVID-19.

Authors:  Rasha Atlasi; Aboozar Ramezani; Ozra Tabatabaei-Malazy; Sudabeh Alatab; Vahideh Oveissi; Bagher Larijani
Journal:  J Herb Med       Date:  2022-07-11       Impact factor: 2.542

2.  Comparison of COVID-19 and non-COVID-19 papers.

Authors:  Cristina Candal-Pedreira; Alberto Ruano-Ravina; Mónica Pérez-Ríos
Journal:  Gac Sanit       Date:  2022-04-27       Impact factor: 2.479

3.  Covid-19 pandemic and the unprecedented mobilisation of scholarly efforts prompted by a health crisis: Scientometric comparisons across SARS, MERS and 2019-nCoV literature.

Authors:  Milad Haghani; Michiel C J Bliemer
Journal:  Scientometrics       Date:  2020-09-21       Impact factor: 3.238

Review 4.  Bibliometric Analysis of Early COVID-19 Research: The Top 50 Cited Papers.

Authors:  Hassan ElHawary; Ali Salimi; Nermin Diab; Lee Smith
Journal:  Infect Dis (Auckl)       Date:  2020-10-13

Review 5.  Global research trends in COVID-19 with MRI and PET/CT: a scoping review with bibliometric and network analyses.

Authors:  Nathaly Rivera-Sotelo; Raul-Gabriel Vargas-Del-Angel; Sergey K Ternovoy; Ernesto Roldan-Valadez
Journal:  Clin Transl Imaging       Date:  2021-08-14

6.  Visualizing the knowledge outburst in global research on COVID-19.

Authors:  Jiban K Pal
Journal:  Scientometrics       Date:  2021-03-06       Impact factor: 3.238

7.  Scientific globalism during a global crisis: research collaboration and open access publications on COVID-19.

Authors:  Jenny J Lee; John P Haupt
Journal:  High Educ (Dordr)       Date:  2020-07-24

8.  The Arab region's contribution to global COVID-19 research: Bibliometric and visualization analysis.

Authors:  Sa'ed H Zyoud
Journal:  Global Health       Date:  2021-03-25       Impact factor: 4.185

9.  Analyzing knowledge entities about COVID-19 using entitymetrics.

Authors:  Qi Yu; Qi Wang; Yafei Zhang; Chongyan Chen; Hyeyoung Ryu; Namu Park; Jae-Eun Baek; Keyuan Li; Yifei Wu; Daifeng Li; Jian Xu; Meijun Liu; Jeremy J Yang; Chenwei Zhang; Chao Lu; Peng Zhang; Xin Li; Baitong Chen; Islam Akef Ebeid; Julia Fensel; Chao Min; Yujia Zhai; Min Song; Ying Ding; Yi Bu
Journal:  Scientometrics       Date:  2021-03-12       Impact factor: 3.801

10.  A critical analysis of COVID-19 research literature: Text mining approach.

Authors:  Ferhat D Zengul; Ayse G Zengul; Michael J Mugavero; Nurettin Oner; Bunyamin Ozaydin; Dursun Delen; James H Willig; Kierstin C Kennedy; James Cimino
Journal:  Intell Based Med       Date:  2021-06-17
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