Medical Literature on Novel Coronavirus (COVID-19) Pandemic: A Scientometric Study with Special Reference to WHO COVID- 19 Database

Since the emergence of the novel Coronavirus disease from Wuhan, China, in early December 2019, scientists every where in the world have focused on this infection to find a way to deal with it. Due to the rapid growth in the literature on this disease, the WHO took the initiative to collate the emerging publications and created "WHO COVID-19 Database". A scientometric study was conducted to better understand the nature of medical literature on COVID-19 included in the WHO COVID- 19 Database, and this article aims to provide an analysis of the coverage of those publications focusing on the twelve months, from December 2019 to November 2020. A total of 35,791 full-text research articles on Coronavirus infections has been published across the world. These publications were originated from 57 countries, indicating the international spread of COVID-19 research. The USA was the largest contributor with 12,989 articles, followed by UK and Netherlands. All the publications mentioned above are written in 15 different languages where English has become the dominant language out of all those languages with 93.25%. According to the findings, the co-authorship network of 3 authors Eric J. Rubin, Lindsey R. Baden and Stephen Morrissey has made the highest contribution with 34 papers published in the New England Journal of Medicine (N Engl J Med). The journal with the highest number of publications on COVID-19 research was the International Journal of Environmental Research and Public Health (Int. J. Environ. Res. Public Health - online). The classification of study type reveals that the maximum number of articles are published on risk factors. This study showed that core journals publishing COVID-19 research are scattered among journals, closely conforming to Bradford's Law of scattering. The Lotka's Law on authorship productivity has been tested to confirm the law's applicability to the present dataset. According to the test, there is a variation of author productivity between the observed percentage and expected percentage of authors as in Lotka's Law. This study will help the research community to get the required information for their research. Further, the information in this paper will encourage the researchers in finding more facts on COVID-19.


Introduction
The outbreak of the novel Coronavirus Disease 2019  with human to human transmission originated in Wuhan, China, in early December 2019, is an ongoing global epidemic incident (Huang et al., 2019). The current outbreak of Coronavirus Disease 2019  has posed many challenges in the world. To control the ongoing COVID-19 is a disease caused by a new strain of Coronavirus. 'CO' stands for corona, 'VI' for the virus, and 'D' for the disease. This disease was formally referred to as '2019 novel Coronavirus' or '2019-nCoV'' (World Health Organization, 2020c. The virus spread rapidly world wide, exerting influence on 220 countries and caused a catastrophe in almost all the spheres of life, including public health, daily living, and the current world economy. Sixty-three million seven hundred nineteen thousand two hundred thirteen confirmed cases of the virus reported so far, and it has taken nearly 1,482,084 lives. More than 45,043,555 people have recovered to date November 2020 (Worldometer, 2020).
Medical literature written on the current pandemic is vital to combat this novel Coronavirus. Researchers world wide are engaged in identifying the cause, clinical features and developing possible vaccines for COVID-19. As a result, rapid growth in publishing scholarly literature on this matter can be seen worldwide. The present surge in publications resulted in the need to generate a systematic database of all COVID-19 related articles to get the full advantage of research. The leader in world health, the World Health Organization (WHO), created one of the largest databases of COVID-19 research related databases (World Health Organization, 2020b). This study aims to identify and analyse the trends in the global research on COVID-19 based on the WHO COVID-19 database by applying scientometric tools. Using scientometric tools, one can measure the various parameters related to publications based on quantitative analysis.
The study of the quantitative aspects of the process of science as a communication system is called scientometrics. Scientometrics, also known as "science of science," is a popular statistical method to critically analyse scientific literature in a particular field (Hood & Wilson, 2001).
The scientometric studies provide various metrics to assess the scholarly literature (Tran et al., 2019). Scientometrics is the investigation of science as the development of information process, and "scientometric studies broadly constitute quantitative analyses of scientific literature to reveal the latest developments in various fields and the patterns of the geographical distribution of science and scientific productivity of individual nations" (Nalimov & Mulchenk, 1969, p. 2).
This study helps people to understand the nature of the medical literature on Coronavirus infections and relationship within the research output of the COVID-19 pandemic and will help overcome the problems to some extent. The findings of the study will be important for library professionals, medical professionals, and medical students who will be using the literature on Coronavirus infections during their research.
Hence, this kind of study will significantly impact the researchers interested in Coronavirus infections, outline the research trends, and determine the most relevant research areas for future endeavours.

Objectives of the Study
Extracting data from clinical research related to COVID-19 will be crucial for improving and developing the diagnosis, treatment, and preventive strategies against this viral infection. Many epidemiological and clinical pieces of evidence have emerged, and a significant number of researches have been published as well. Therefore, the aim of this study is to analyse and investigate the nature and publication pattern of COVID-19 related publications in the WHO COVID-19 database using scientometrics indicators.

Literature Review
It is evident that during December 2019 and November 2020, COVID-19 related medical literature has upsurged unprecedentedly. Kambhampati et al. (2020) conducted a research study on exploring the PubMed database with 6,831 papers. Out of these papers, six thousand four hundred and fifteen papers were in the English

Methodology
This particular study has adopted a descriptive research approach through scientometric study, because of its nature as an exploratory investigation to describe the quantity and productivity of global medical

Bradford Law of Scattering
Bradford Law of scattering explains how the literature on a particular subject is scattered or distributed in journals. Bradford (1948) formulated his law as follows: When we arrange scientific journals in order of decreasing productivity of articles on a given subject, in that case, they may be divided into a nucleus of periodicals more particularly devoted to the subject, and several groups or zones containing the same number of articles as the nucleus. The number of divisions in the nucleus and succeeding zones will be as 1: n: n 2 , where 'n' is a multiplier. (Brookes, 1985, p. 177) 1: n: n 2 , where 'n' is a multiplier

Lotka's Law
Lotka's Law is one of the bibliometrics laws, which deals with the authors' frequency of publication in any given field. The researchers measured research productivity using different parameters from time to time. "Lotka's Law of scientific productivity (author's productivity in a subject) is a law of scientometric. One can use it to map authors' productivity patterns in a subject. The following equation better articulate the Lotka's Law" (Lotka, 1926, p. 318): The law describes that the number (of authors) making 'n' contributions is about 1/n² of those making one. The number of authors that make a single contribution is of about 60 %. It means that 60% of the authors produce one publication; 15% (1/2² 60) produces two publications, 7 % (1/3² 60) produces three publications, and so on. The law is a generalised approach that maps the authorship far better than a rigid law that varies from one field to another. Still, it gives an expanded prospect to know authors' productivity pattern in a discipline (Coile, 1978).
Here 'x' represents the number of articles published (1, 2, 3, 4…); ' ' is the number of authors having the frequency 'x' number of articles; 'n' is an exponential constant for a particular set of data, and 'C' is a constant. When n=2 is used for a data set, in the case that 'C= 0.6079', the law is called 'Inverse-square law of scientific productivity', in this case. The value of 'n' differs from data set to data set. (Askew, 2008, p. 9)

Results and Discussion
During period under the study was found to be uneven but slightly in an increasing nature from January to May 2020.

Distribution of Journals
Research on Coronavirus infections has been published in several sources. In the study, highly productive journals were identified, and it was found that these journals collectively contributed immensely. Out of the 15,796 journals in the database, there are 35,791 articles in 3,861 journals. Table 2 shows the distribution of articles in these journals.
It is visible that 3,820 out of 3,861 journals have published less than 100 articles so that less than 25 articles in 3,567 journals, between 99 articles in 25 journals. There are 30 journals that have between 101-200 articles. From the remaining 11 journals, 6 journals have articles between 201-300, 4 journals with the number of articles between 301-400 and only one journal with 401-500 articles during the study period.

Table 2
Distribution of Articles in Journals

Bradford Law of Scattering
Bradford's Law of scattering describes a quantitative relationship between papers and journals in which they publish. It further explains that only a small number of core journals will supply the nucleus of papers on a given topic which accounts for a substantial percentage (1/3) of the articles. There is a second more extensive group of journals that accounts for another one-third of the articles. Consequently, the next group contains the remaining one-third of the articles.
Bradford's Law of scatters discusses the mathematical distribution the journals to produce nearly equal numbers of articles are roughly in proportion 1: n: n 2 , where 'n' is called the Bradford multiplier. Bradford's law states that a small core of journals, For example, journals that have as many papers on a given subject and as a much larger number of journals 'n', which again has as many papers on the subject as 'n 2 ' journals (Rao, 1998).
Bradford's Law of scattering explains the quantitative connection between journals. The journals are divided in to three equal zones: onethird of articles in each zone after arranging in descending order of productivity. Hence, applying the above expression to this study, 35791 articles are divided into three groups, as presented in Table 3.

Journals with more than 100 Publications
The ranking of the journals (with articles greater than 100) by its number of articles on Coronavirus infections is given in

Geographical Distribution of Publications
The global COVID-19 research output is originated from 57 countries during the study period and contributed 35791 full-text articles.

Infections Research
A total of 16 different languages were encountered in retrieved articles, while three are bilingual. English (93.25%) was the most common, followed by Spanish (2.77%), Portuguese (1.08%), and Chinese (1.04%). Articles written in other languages are shown in Table   7. Three author contributions occupy the third position with 1.11% of the total publication. It indicates that the multi authored contribution is extremely less than that of the single authored. Most productive authors are based on the number of articles and those who have written more than ten articles. All the articles here are in English and appeared on the MEDLINE database.

Infections Research Output
Lotka's Law reveals the productivity frequency distribution of authors in a given subject/discipline. In this paper, an attempt has been made to study Lotka's Law's applicability to Coronavirus infections publications. In testing the applicability of the law, the value of 'n', and 'C' of the data set has been determined with the help of calculations made in Table 9 shown below. Lotka's Law well explains the author productivity, and Table 9 shows the details. According to the Table 9, though, there is a slight variation between the observed percentage of authors and the expected percentage of authors. It is close to conforming to Lotka's Law.

Conclusion
The widespread COVID-19 epidemic disease has created many challenges and raised severe public health issues for people in almost all