Skip to main content
  • Research article
  • Open access
  • Published:

Mapping the situation of research on coronavirus disease-19 (COVID-19): a preliminary bibliometric analysis during the early stage of the outbreak

Abstract

Background

The novel coronavirus, named as 2019-nCoV or coronavirus disease 2019 (COVID-19), has recently appeared in China and has spread worldwide, presenting a health threat to the global community. Therefore, it is important to understand the global scientific output of COVID-19 research during the early stage of the outbreak. Thus, to track the current hotspots, and highlight future directions, we performed a bibliometric analysis to obtain an approximate scenario of COVID-19 to date.

Methods

Relevant studies to COVID-19 were obtained from the Scopus database during the early stage of the outbreak. We then analysed the data by using well-established bibliometric indices: document type, country, collaboration patterns, affiliation, journal name, and citation patterns. VOSviewer was applied to map and determine hot topics in this field.

Results

The bibliometric analysis indicated that there were 19,044 publications on Scopus published on COVID-19 during the early stage of the outbreak (December 2019 up until June 19, 2020). Of all these publications, 9140 (48.0%) were articles; 4192 (22.0%) were letters; 1797 (9.4%) were reviews; 1754 (9.2%) were editorials; 1728 (9.1%) were notes; and 433 (2.3%) were others. The USA published the largest number of publications on COVID-19 (4479; 23.4%), followed by China (3310; 17.4%), Italy, (2314; 12.2%), and the UK (1981; 10.4%). British Medical Journal was the most productive. The Huazhong University of Science and Technology, Tongji Medical, and Harvard Medical School were the institutions that published the largest number of COVID-19 research. The most prevalent topics of research in COVID-19 include “clinical features studies”, “pathological findings and therapeutic design”, “care facilities preparation and infection control”, and “maternal, perinatal and neonatal outcomes”.

Conclusions

This bibliometric study may reflect rapidly emerging topics on COVID-19 research, where substantial research activity has already begun extensively during the early stage of the outbreak. The findings reported here shed new light on the major progress in the near future for hot topics on COVID-19 research including clinical features studies, pathological findings and therapeutic design, care facilities preparation and infection control, and maternal, perinatal and neonatal outcomes.

Peer Review reports

Background

A cluster of viral pneumonia cases of unknown cause, subsequently identified as a novel coronavirus, named as 2019-nCoV or COVID-19, was detected on December 31, 2019, in Wuhan, China [1,2,3,4]. The disease has spread rapidly from Wuhan to other regions in China. Further, the dissemination of this virus has been observed in 216 countries and over 535,700 deaths as of 7 July 2020 [5].

The clinical symptoms of COVID-19 range from asymptomatic to severe pneumonia and multiple organ failure [6]. The most commonly reported clinical features are fever, cough, breathlessness, myalgia, and fatigue, whereas less common reported clinical features to include diarrhea, headache, conjunctivitis, and runny nose [7, 8]. For a subset of patients, the disease may progress to pneumonia with respiratory failure and even death by the end of the first week [8, 9]. At this time, there are few specific antiviral strategies combined with supportive treatment, but several potent nominees of antivirals such as lopinavir/ritonavir, remdesivir, or chloroquine and repurposed drugs are under urgent investigation [10].

Bibliometric evaluation, a commonly accepted statistical tool, helps to present knowledge structures of a particular research field [11,12,13]. Throughout recent years, bibliometrics have been used to provide strong insights into several biomedical fields linked to many virus outbreaks [14,15,16,17,18,19,20,21,22,23,24,25,26,27]. There have been a few recent reviews of COVID-19 or Coronavirus [28,29,30,31,32,33,34,35,36], but no comprehensive evaluation of the existing research on COVID-19 has yet been performed or published. The previously published bibliometric studies [28,29,30,31,32,33,34,35,36] on COVID-19 have been published by using PubMed or Web of Science (WoS) database for data collection and were limited to biomedical research areas. Therefore, the purposes of the current study were to assess the global scientific output of COVID-19 research during the early stage of the outbreak through bibliometric analysis, determine the top-cited publications, and to explore the current hot topics in order to provide the scientists and researchers with a resource that can help them by identifying the current research priorities.

Methods

Data source

Published papers were retrieved via a topic search (title/abstract) of the Scopus on 19 June 2020. In the current analysis, the Scopus database was used without restricting the findings to any particular field of search as a difference from previous bibliometric studies on COVID-19 [28,29,30,31,32,33,34,35,36]. The use of Scopus as a bibliometric resource in our study was based on the truth that it has the world’s largest abstract and citation database of peer-reviewed scientific literature compared with PubMed or Web of Science [37,38,39].

Search strategy

Concerning COVID-19 during the early stage of the outbreak, the terms used in the search engine of Scopus were either in Title or Abstract (“COVID 19” or “2019 novel coronavirus” or “coronavirus 2019” or “coronavirus disease 2019” or “2019-novel CoV” or “2019 ncov” or COVID 2019 or COVID19 or “corona virus 2019” or nCoV-2019 or nCoV2019 or “nCoV 2019” or 2019-ncov or COVID-19 or “Severe acute respiratory syndrome coronavirus 2” or “SARS-CoV-2”).

Bibliometric analysis

All relevant data to COVID-19 were downloaded from the Scopus. In this study, we analyzed the retrieved data through Excel to collect the following bibliometric indicators based on previous similar studies [40,41,42,43]: (1) publication output; (2) document type; (3) country/region; (4) institute; (5) journal; (6) h-index; and (7) citation.

Visualized analysis

VOSviewer v.1.6.14 (https://www.vosviewer.com/) is frequently used to construct and visualize network terms used in title/abstract articles to detect hot topics in this field [44, 45]. The policy adopted by Scopus does not provide complete information on all the data and allows for the export of up to 2000 articles. The exported file is in an excel file format. Therefore, we decided to export the top 2000 cited articles and further analyzed them to construct and visualize networks terms used in title/abstract articles to detect hot topics in this field.

Results

The bibliometric analysis indicated that there were 19,044 publications on Scopus published related to COVID-19 during the early stage of the outbreak (December 2019 up until June 19, 2020). Of all these publications, 9140 (48.0%) were articles; 4192 (22.0%) were letters; 1797 (9.4%) were reviews; 1754 (9.2%) were editorials; 1728 (9.1%) were notes; and 433 (2.3%) were others. In addition, the h-index for all data collected related to the research of COVID-19 was 108.

The publications linked to COVID-19 included authors from 159 different countries. The top 10 countries published 16,957 (89%) articles each are presented in Table 1. The USA published the largest number of publications on COVID-19 (4479; 23.4%), followed by China (3310; 17.4%), Italy, (2314; 12.2%), and the UK (1981; 10.4%).

Table 1 The top 10 countries of origin of papers in novel coronavirus (COVID-19) research

During the early stage of the COVID-19 outbreak, a total of 8387 institutions were identified. The top 10 institutions that published the most publications on COVID-19 were shown in Table 2. The Huazhong University of Science and Technology was the most productive institution with 422 publications, followed by Tongji Medical College with 415 publications, and Harvard Medical School with 331 publications.

Table 2 The top 10 institutions contributed to publications on novel coronavirus (COVID-19) research

Amongst the top 10 journals shown in Table 3. British Medical Journal with IF, 2019 = 30.223, published the most number of publications on COVID-19 (n = 522), followed by Journal of Medical Virology (n = 311; IF, 2019 = 2.021), Lancet (n = 215; IF, 2019 = 60.392), and Journal of the American Medical Association (n = 137; IF, 2019 = 45.540).

Table 3 The top 10 journals that published articles on novel coronavirus (COVID-19) research

Research hot topics for publications related to COVID-19 were visualized and presented in network visualization by mapping of co-occurrences of terms in title/abstract for the top-2000 most cited publications (Fig. 1). Of the 20,897 terms, 721 terms occurred at least 10 times. The largest network of connected terms involves of 433 terms in four clusters. The four most used topics in publications related to COVID-19 are signified by four colored clusters: red, blue, green, and yellow colors. Cluster number 1 (red color) involved terms related to clinical features and characteristics topic such as “fever”, “cough”, “severe patients”, “diabetes”, “hypertension” or “C-reactive protein”; Cluster number 2 (blue color) involved terms related to pathological findings and therapeutic design topic such as “receptor”, “enzyme”, “inhibitor”, “angiotensin”, “spike glycoprotein”, “drug”, “antiviral” or “chloroquine”; Cluster number 3 (green color) involved terms related to care facilities preparation and infection control topic such as “control measures”, “recommendations”, “preparedness”, “experience” or “medical staff”; and Cluster number 4 (yellow color) involved terms related to maternal, perinatal and neonatal outcomes topic such as “delivery”, “infant”, “mother”, “neonate”, or “newborn”.

Fig. 1
figure 1

Research topics clustered by mapping of co-occurrences of terms in title/abstract for publications related to COVID-19. Of the 20,897 terms, 721 terms have occurred at least 10 times. For each of the 721 terms, a relevance score was determined and used to select the 60% most relevant terms. The size of the circles in Fig. 1 represents the occurrences of terms in title/abstract. The largest set of connected terms consists of 433 terms in four clusters: Clinical features studies (red), pathological findings and therapeutic design (blue), care facilities preparation and infection control (green), and maternal, perinatal and neonatal outcomes (yellow)

The citation counts for the final 20 articles ranged from 387 to 2554 (Table 4). All documents were published in 7 different journals [3, 7, 9, 46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62]. Most documents were published in New England Journal of Medicine (n = 7), followed by the Lancet (n = 6), Lancet Respiratory Medicine (n = 2), Journal of the American Medical Association (n = 2), Cell Research (n = 1), Nature (n = 1), and Cell (n = 1).

Table 4 The Top 20 Cited Papers in novel coronavirus (COVID-19) research

Discussion

The purpose of this bibliometric study was to summarize and examine the evolution of the immediate effect of the COVID-19 pandemic on scientific output. The findings of the study reflect the latest global scholarly publications on COVID-19. The analysis of this study showed some significant insights. The current study has shown a rapid increase in research activities related to COVID-19 over such a short period of time compared to other diseases or infections [14,15,16, 18, 21, 22, 63,64,65,66]. This rapid increase in research output on COVID-19 in such a short period of time is due to several reasons: COVID-19 is a global pandemic that has impacted and influenced the global health status, due to a lockout in many countries where scientists have more time to write and publish, and most of the journals considered COVID-19 related papers as a top priority for publication and their editorial process is fast-tracked [31].

The current study has revealed the leading role played by the USA, China, Italy, and the UK, in COVID-19 research. A potential reason for these findings may be attributed to the high prevalence of COVID-19 in those countries witnessing the first outbreak [67,68,69,70,71]. The USA tends to have superior conditions for basic medical research or experimental trials, including sufficient funding and resources, advanced equipment, and skilled researchers [34].

As we have seen in our evidence maps on the main topics, a large number of articles focused on clinical features studies, pathological findings and therapeutic design, care facilities preparation and infection control, and maternal, perinatal and neonatal outcomes Meanwhile, all these topics have been emerging commonly in recent months and may become a major topic in the next years, particularly after COVID-19 in Wuhan as suggested by a more recent study [33].

The current study showed that most of the top-cited articles were published in high impact journals. Scientists are likely to rely on these Journals for higher impact [72]. Many journals, including all leading journals with high impact factors, highlighted specific issues of COVID-19 and most publishers published them as a top priority for their publication and also provided free access to such papers [31].

In the current study, highly cited articles were evidence-based research, for example, the first most cited article was from Huang et al. [7] in the Lancet. This article focused on the epidemiology, laboratory diagnosis, sign and symptoms, and clinical outcomes of 41 patients who were reported as having COVID-19 infection. In addition, this study [7] demonstrated that COVID-19 infection caused serious respiratory disease clusters and was linked to ICU mortality. The second most cited study was from Wang et al. [9] in the Journal of the American Medical Association. The aim of this study was to describe the clinical characteristics of patients with COVID-19-infected pneumonia in Wuhan, China. The third most cited was from Guan et al. [46] in the New England Journal of Medicine. This study aimed to describe the clinical features of Covid-19 in a selected cohort of patients across China. The fourth most cited study was from Zhu et al. [47] in the New England Journal of Medicine. The purpose of this study was to characterize a novel coronavirus found in patients with pneumonia and to identify the source of the pneumonia clusters whose specimens were tested by the China CDC at an early stage of the outbreak.

Strengths and limitations

Bibliometric and visual analysis has been performed to represent the current status of COVID-19 research through analysis of citation patterns and hot topics in this field. This provides quick information during the early stage of the outbreak that shows important patterns in several different dimensions, which to the best of our knowledge is the first analysis of its type in the field. A limitation of our study was that only the Scopus database was used for article retrieval. Other databases, like PubMed, were not considered. The total number of publications related to COVID-19 from PubMed could be a little bit higher than Scopus. PubMed is updated daily, including online in an early version by various journals. In contrast, Scopus is readily updated for published issues but does not include the online version of publications before inclusion in an issue for most indexed journals [37]. Although several databases are used in bibliometric studies at the global level [37, 38, 73], our study applied the Scopus database for data extraction, which is commonly accepted by investigators for high-quality bibliometric analysis [74,75,76,77,78,79,80]. Furthermore, Scopus contains a higher degree of features than PubMed, including the affiliations for all authors and citations per document [38, 81]. In addition, it should be noted the limitation of the speed at which evidence appears, which undoubtedly influences the actuality of the manuscript. Therefore, we emphasized that this bibliometric analysis only represents the initial phase of the pandemic. Thus, studies published in Scopus after June 19, 2020, were not included in this study.

Conclusions

This bibliometric study may reflect rapidly emerging topics on COVID-19 research, where substantial research activity has already begun extensively during the early stage of the outbreak. Overall, our results may provide useful information to outline new viewpoints and shape future directions for COVID-19 research. COVID-19 research is a hot issue nowadays. Clinical features studies, pathological findings and therapeutic design, care facilities preparation and infection control, and maternal, perinatal and neonatal outcomes could be a research frontier in the future.

Availability of data and materials

The datasets generated and/or analysed during the current study are available upon request to the corresponding authors (saedzyoud@yahoo.com; samahjabi@yahoo.com).

Abbreviations

COVID-19:

Coronavirus disease 2019

JCR:

Journal Citation Reports;

IFs:

Impact factors

2019-nCoV:

2019 novel coronavirus.

Reference`s

  1. Pung R, Chiew CJ, Young BE, Chin S, Chen MI, Clapham HE, Cook AR, Maurer-Stroh S, Toh M, Poh C, et al. Investigation of three clusters of COVID-19 in Singapore: implications for surveillance and response measures. Lancet. 2020;395(10229):1039–46.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Wu Y, Ho W, Huang Y, Jin DY, Li S, Liu SL, Liu X, Qiu J, Sang Y, Wang Q, et al. SARS-CoV-2 is an appropriate name for the new coronavirus. Lancet. 2020;395(10228):949–50.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, Xiang J, Wang Y, Song B, Gu X, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054–62.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Shi H, Han X, Jiang N, Cao Y, Alwalid O, Gu J, Fan Y, Zheng C. Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. Lancet Infect Dis. 2020;20(4):425–34.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. World Health Organization. Coronavirus disease (COVID-19) outbreak situation. 2020. https://www.who.int/emergencies/diseases/novel-coronavirus-2019 (accessed July 7 2020).

    Google Scholar 

  6. Singhal T. A review of coronavirus Disease-2019 (COVID-19). Indian J Pediatr. 2020;87(4):281–6.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. Adhikari SP, Meng S, Wu YJ, Mao YP, Ye RX, Wang QZ, Sun C, Sylvia S, Rozelle S, Raat H, et al. Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (COVID-19) during the early outbreak period: a scoping review. Infect Dis Poverty. 2020;9(1):29.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;323(11):1061–9.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  10. Guo YR, Cao QD, Hong ZS, Tan YY, Chen SD, Jin HJ, Tan KS, Wang DY, Yan Y. The origin, transmission and clinical therapies on coronavirus disease 2019 (COVID-19) outbreak - an update on the status. Mil Med Res. 2020;7(1):11.

    PubMed  PubMed Central  CAS  Google Scholar 

  11. Cooper ID. Bibliometrics basics. J Med Libr Assoc. 2015;103(4):217–8.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Gisbert JP, Panes J. Scientific publication, bibliometric indicators, and Hirsch's h-index. Gastroenterol Hepatol. 2009;32(3):140–9.

    Article  PubMed  Google Scholar 

  13. Wallin JA. Bibliometric methods: pitfalls and possibilities. Basic Clin Pharmacol Toxicol. 2005;97(5):261–75.

    Article  PubMed  CAS  Google Scholar 

  14. Zyoud SH. Global research trends of Middle East respiratory syndrome coronavirus: a bibliometric analysis. BMC Infect Dis. 2016;16:255.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Al-Jabi SW. Global research trends in West Nile virus from 1943 to 2016: a bibliometric analysis. Glob Health. 2017;13(1):55.

    Article  Google Scholar 

  16. Hagel C, Weidemann F, Gauch S, Edwards S, Tinnemann P. Analysing published global Ebola virus disease research using social network analysis. PLoS Negl Trop Dis. 2017;11(10):e0005747.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Sweileh WM. Bibliometric analysis of literature in AIDS-related stigma and discrimination. Transl Behav Med. 2019;9(4):617–28.

    Article  PubMed  Google Scholar 

  18. Zou Y, Luo Y, Zhang J, Xia N, Tan G, Huang C. Bibliometric analysis of oncolytic virus research, 2000 to 2018. Medicine (Baltimore). 2019;98(35):e16817.

    Article  Google Scholar 

  19. Culquichicon C, Cardona-Ospina JA, Patino-Barbosa AM, Rodriguez-Morales AJ. Bibliometric analysis of Oropouche research: impact on the surveillance of emerging arboviruses in Latin America. F1000Res. 2017;6:194.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Pereira-Silva JW. Bibliometric assessment of scientific production of literature of West Nile virus. J Infect Public Health. 2017;10(3):363–5.

    Article  PubMed  Google Scholar 

  21. Albuquerque PC, Castro MJ, Santos-Gandelman J, Oliveira AC, Peralta JM, Rodrigues ML. Bibliometric indicators of the Zika outbreak. PLoS Negl Trop Dis. 2017;11(1):e0005132.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Rios-Gonzalez CM. Bibliometric study of international scientific production in O'nyong-nyong virus during the years 1962-2016. J Infect Public Health. 2017;10(1):137–8.

    Article  PubMed  Google Scholar 

  23. Garg KC, Kumar S. Bibliometrics of global Ebola virus disease research as seen through science citation index expanded during 1987-2015. Travel Med Infect Dis. 2017;16:64–5.

    Article  PubMed  CAS  Google Scholar 

  24. Sweileh WM. Global research output on HIV/AIDS-related medication adherence from 1980 to 2017. BMC Health Serv Res. 2018;18(1):765.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Del Carpio OL. Guillain-Barre syndrome associated with zika virus infection in the Americas: a bibliometric study. Neurologia. 2020;35(6):426–9.

  26. Singh N. Scientometric analysis of research on Zika virus. Virusdisease. 2016;27(3):303–6.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Rios-Gonzalez CM, Veron Mellid FG. When has it been studied about La Crosse virus?: Bibliometric analysis of world scientific production. J Infect Public Health. 2018;11(5):745–6.

    Article  PubMed  Google Scholar 

  28. Andersen JP, Nielsen MW, Simone NL, Lewiss RE, Jagsi R. COVID-19 medical papers have fewer women first authors than expected. Elife. 2020;9:e58807.

  29. Chahrour M, Assi S, Bejjani M, Nasrallah AA, Salhab H, Fares M, Khachfe HH. A Bibliometric analysis of COVID-19 research activity: a call for increased output. Cureus. 2020;12(3):e7357.

    PubMed  PubMed Central  Google Scholar 

  30. Haghani M, Bliemer MCJ, Goerlandt F, Li J. The scientific literature on coronaviruses, COVID-19 and its associated safety-related research dimensions: a scientometric analysis and scoping review. Saf Sci. 2020;129:104806.

    Article  PubMed Central  PubMed  Google Scholar 

  31. Kambhampati SBS, Vaishya R, Vaish A. Unprecedented surge in publications related to COVID-19 in the first three months of pandemic: a bibliometric analytic report. J Clin Orthop Trauma. 2020;11(Suppl 3):S304–6.

    Article  PubMed Central  PubMed  Google Scholar 

  32. Lou J, Tian SJ, Niu SM, Kang XQ, Lian HX, Zhang LX, Zhang JJ. Coronavirus disease 2019: a bibliometric analysis and review. Eur Rev Med Pharmacol Sci. 2020;24(6):3411–21.

    PubMed  CAS  Google Scholar 

  33. Mao X, Guo L, Fu P, Xiang C. The status and trends of coronavirus research: a global bibliometric and visualized analysis. Medicine (Baltimore). 2020;99(22):e20137.

    Article  CAS  Google Scholar 

  34. Tao Z, Zhou S, Yao R, Wen K, Da W, Meng Y, Yang K, Liu H, Tao L. COVID-19 will stimulate a new coronavirus research breakthrough: a 20-year bibliometric analysis. Ann Transl Med. 2020;8(8):528.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Zhai F, Zhai Y, Cong C, Song T, Xiang R, Feng T, Liang Z, Zeng Y, Yang J, Yang J, et al. Research Progress of Coronavirus Based on Bibliometric Analysis. Int J Environ Res Public Health. 2020;17(11):3766.

  36. Zhou Y, Chen L. Twenty-Year Span of Global Coronavirus Research Trends: A Bibliometric Analysis. Int J Environ Res Public Health. 2020;17(9):3082.

  37. Falagas ME, Pitsouni EI, Malietzis GA, Pappas G. Comparison of PubMed, Scopus, web of science, and Google scholar: strengths and weaknesses. FASEB J. 2008;22(2):338–42.

    Article  PubMed  CAS  Google Scholar 

  38. Kulkarni AV, Aziz B, Shams I, Busse JW. Comparisons of citations in web of science, Scopus, and Google scholar for articles published in general medical journals. JAMA. 2009;302(10):1092–6.

    Article  PubMed  CAS  Google Scholar 

  39. Mongeon P, Paul-Hus A. The journal coverage of web of science and Scopus: a comparative analysis. Scientometrics. 2015;106(1):213–28.

    Article  Google Scholar 

  40. Zyoud SH, Smale S, Waring WS, Sweileh WM, Al-Jabi SW. Global research trends in microbiome-gut-brain axis during 2009-2018: a bibliometric and visualized study. BMC Gastroenterol. 2019;19(1):158.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Zyoud SH. Global scientific trends on aflatoxin research during 1998-2017: a bibliometric and visualized study. J Occup Med Toxicol. 2019;14:27.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Al-Jabi SW. Arab world's growing contribution to global leishmaniasis research (1998-2017): a bibliometric study. BMC Public Health. 2019;19(1):625.

    Article  PubMed  PubMed Central  Google Scholar 

  43. F DEF. Polimeni a: coronavirus disease (COVID-19): a machine learning Bibliometric analysis. In Vivo. 2020;34(3 Suppl):1613–7.

    Article  CAS  Google Scholar 

  44. van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010;84(2):523–38.

    Article  PubMed  Google Scholar 

  45. van Eck NJ, Waltman L. Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics. 2017;111(2):1053–70.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382(18):1708–20.

    Article  PubMed  CAS  Google Scholar 

  47. Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, Zhao X, Huang B, Shi W, Lu R, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382(8):727–33.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507–13.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, Ren R, Leung KSM, Lau EHY, Wong JY, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med. 2020;382(13):1199–207.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Wu Z, McGoogan JM. Characteristics 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 Prevention. JAMA. 2020; 323(13):1239–42.

  51. Zhou P, Yang XL, Wang XG, Hu B, Zhang L, Zhang W, Si HR, Zhu Y, Li B, Huang CL, et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature. 2020;579(7798):270–3.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Chan JF, Yuan S, Kok KH, KK T, Chu H, Yang J, Xing F, Liu J, Yip CC, Poon RW, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514–23.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, Wang W, Song H, Huang B, Zhu N, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet. 2020;395(10224):565–74.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Holshue ML, DeBolt C, Lindquist S, Lofy KH, Wiesman J, Bruce H, Spitters C, Ericson K, Wilkerson S, Tural A, et al. First case of 2019 novel coronavirus in the United States. N Engl J Med. 2020;382(10):929–36.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, Wu Y, Zhang L, Yu Z, Fang M, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020;8(5):475–81.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Wang M, Cao R, Zhang L, Yang X, Liu J, Xu M, Shi Z, Hu Z, Zhong W, Xiao G. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res. 2020;30(3):269–71.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  57. Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C, Liu S, Zhao P, Liu H, Zhu L, et al. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. 2020;8(4):420–2.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. van Doremalen N, Bushmaker T, Morris DH, Holbrook MG, Gamble A, Williamson BN, Tamin A, Harcourt JL, Thornburg NJ, Gerber SI, et al. Aerosol and surface stability of SARS-CoV-2 as compared with SARS-CoV-1. N Engl J Med. 2020;382(16):1564–7.

    Article  PubMed  Google Scholar 

  59. Hoffmann M, Kleine-Weber H, Schroeder S, Kruger N, Herrler T, Erichsen S, Schiergens TS, Herrler G, Wu NH, Nitsche A, et al. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell. 2020;181(2):271–80 e278.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Rothe C, Schunk M, Sothmann P, Bretzel G, Froeschl G, Wallrauch C, Zimmer T, Thiel V, Janke C, Guggemos W, et al. Transmission of 2019-nCoV infection from an asymptomatic contact in Germany. N Engl J Med. 2020;382(10):970–1.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Mehta P, McAuley DF, Brown M, Sanchez E, Tattersall RS, Manson JJ. HLH across Speciality collaboration UK: COVID-19: consider cytokine storm syndromes and immunosuppression. Lancet. 2020;395(10229):1033–4.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. Zou L, Ruan F, Huang M, Liang L, Huang H, Hong Z, Yu J, Kang M, Song Y, Xia J, et al. SARS-CoV-2 viral load in upper respiratory specimens of infected patients. N Engl J Med. 2020;382(12):1177–9.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Maula AW, Fuad A, Utarini A. Ten-years trend of dengue research in Indonesia and south-east Asian countries: a bibliometric analysis. Glob Health Action. 2018;11(1):1504398.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Okoroiwu HU, Lopez-Munoz F, Povedano-Montero FJ. Bibliometric analysis of global Lassa fever research (1970-2017): a 47 - year study. BMC Infect Dis. 2018;18(1):639.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Sweileh WM. Global research trends of World Health Organization's top eight emerging pathogens. Glob Health. 2017;13(1):9.

    Article  Google Scholar 

  66. Zyoud SH. Dengue research: a bibliometric analysis of worldwide and Arab publications during 1872-2015. Virol J. 2016;13:78.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Bernard Stoecklin S, Rolland P, Silue Y, Mailles A, Campese C, Simondon A, Mechain M, Meurice L, Nguyen M, Bassi C et al: First cases of coronavirus disease 2019 (COVID-19) in France: surveillance, investigations and control measures, January 2020. Euro Surveill. 2020;25(6):2000094.

  68. Marchand-Senecal X, Kozak R, Mubareka S, Salt N, Gubbay JB, Eshaghi A, Allen V, Li Y, Bastien N, Gilmour M, et al. Diagnosis and Management of First Case of COVID-19 in Canada: lessons applied from SARS. Clin Infect Dis. 2020. https://doi.org/10.1093/cid/ciaa227.

  69. Wells CR, Sah P, Moghadas SM, Pandey A, Shoukat A, Wang Y, Wang Z, Meyers LA, Singer BH, Galvani AP. Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak. Proc Natl Acad Sci U S A. 2020;117(13):7504–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Livingston E, Bucher K. Coronavirus disease 2019 (COVID-19) in Italy. JAMA. 2020;323(14):1335.

  71. Spiteri G, Fielding J, Diercke M, Campese C, Enouf V, Gaymard A, Bella A, Sognamiglio P, Sierra Moros MJ, Riutort AN, et al. First cases of coronavirus disease 2019 (COVID-19) in the WHO European region, 24 January to 21 February 2020. Euro Surveill. 2020;25(9):2000178.

  72. Kiraz M, Demir E. A Bibliometric analysis of publications on spinal cord injury during 1980-2018. World Neurosurg. 2020;136:e504–13.

    Article  PubMed  Google Scholar 

  73. Bakkalbasi N, Bauer K, Glover J, Wang L. Three options for citation tracking: Google scholar, Scopus and Web of Science. Biomed Digit Libr. 2006;3:7.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Hernandez-Vasquez A, Alarcon-Ruiz CA, Bendezu-Quispe G, Comande D, Rosselli D. A bibliometric analysis of the global research on biosimilars. J Pharm Policy Pract. 2018;11:6.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Khalili M, Rahimi-Movaghar A, Shadloo B, Mojtabai R, Mann K, Amin-Esmaeili M. Global scientific production on illicit drug addiction: a two-decade analysis. Eur Addict Res. 2018;24(2):60–70.

    Article  PubMed  Google Scholar 

  76. Lee RP, Xu R, Dave P, Ajmera S, Lillard JC, Wallace D, Broussard A, Motiwala M, Norrdahl S, Howie C, et al. Taking the next step in publication productivity analysis in pediatric neurosurgery. J Neurosurg Pediatr. 2018;21(6):655–65.

    Article  PubMed  Google Scholar 

  77. Sweileh WM. Global output of research on epidermal parasitic skin diseases from 1967 to 2017. Infect Dis Poverty. 2018;7(1):74.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Teles RHG, Moralles HF, Cominetti MR. Global trends in nanomedicine research on triple negative breast cancer: a bibliometric analysis. Int J Nanomedicine. 2018;13:2321–36.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  79. Yao H, Wan JY, Wang CZ, Li L, Wang J, Li Y, Huang WH, Zeng J, Wang Q, Yuan CS. Bibliometric analysis of research on the role of intestinal microbiota in obesity. PeerJ. 2018;6:e5091.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Zyoud SH. Investigating global trends in paraquat intoxication research from 1962 to 2015 using bibliometric analysis. Am J Ind Med. 2018;61(6):462–70.

    Article  PubMed  Google Scholar 

  81. Agarwal A, Durairajanayagam D, Tatagari S, Esteves SC, Harlev A, Henkel R, Roychoudhury S, Homa S, Puchalt NG, Ramasamy R, et al. Bibliometrics: tracking research impact by selecting the appropriate metrics. Asian J Androl. 2016;18(2):296–309.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

No funding was received for writing this study.

Author information

Authors and Affiliations

Authors

Contributions

Both authors (SZ and SA) contributed equally to this manuscript, initiated the study, designed and performed the analysis, interpreted the data, wrote the main paper. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Sa’ed H. Zyoud or Samah W. Al-Jabi.

Ethics declarations

Ethics approval and consent to participate

No ethical approval was required, as this was a bibliometric review for the existing literature.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zyoud, S.H., Al-Jabi, S.W. Mapping the situation of research on coronavirus disease-19 (COVID-19): a preliminary bibliometric analysis during the early stage of the outbreak. BMC Infect Dis 20, 561 (2020). https://doi.org/10.1186/s12879-020-05293-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12879-020-05293-z

Keywords