Description and Analysis of Research on Death and Dying during the COVID-19 Pandemic, Published in Nursing Journals Indexed in SCOPUS

AIM

To offer an overall picture of the research published regarding the different aspects of death and dying during the COVID-19 pandemic in journals covering the field of nursing in the Scopus database.

DESIGN

bibliometric analysis.

METHODS

The metadata obtained were exported from Scopus for subsequent analysis through Bibliometrix. Using the VOSviewer co-word analysis function, the conceptual and thematic structure of the publications was identified.

RESULTS

A total of 119 papers were retrieved, with the participation of 527 authors. The publications were found in 71 journals covering the nursing area. The main lines of research revolved around the keywords "palliative care" and "end-of-life care" in regard to the ethical, psychological, and organizational challenges faced by the health professionals who cared for these patients.

CONCLUSION

The results obtained offer a range of data and images that characterize the scientific production published on this topic, coming to the conclusion that, due to the multifaceted and multidisciplinary approach to the experience of death, care, and accompaniment in the dying process, bibliometric maps improve the comprehensive understanding of the semantic and conceptual structure of this field of research. This study was retrospectively registered with the OSF Registries on the 14 March 2024.

Evaluating the dependability of reference-driven citation forecasts amid the COVID-19 pandemic: A bibliometric analysis across diverse journals

BACKGROUND

The journal impact factor significantly influences research publishing and funding decisions. With the surge in research due to COVID-19, this study investigates whether references remain reliable citation predictors during this period.

METHODS

Four multidisciplinary journals (PLoS One, Medicine [Baltimore], J. Formos. Med. Assoc., and Eur. J. Med. Res.) were analyzed using the Web of Science database for 2020 to 2022 publications. The study employed descriptive, predictive, and diagnostic analytics, with tools such as 4-quadrant radar plots, univariate regressions, and country-based collaborative maps via the follower-leading cluster algorithm.

RESULTS

Six countries dominated the top 20 affiliations: China, Japan, South Korea, Taiwan, Germany, and Brazil. References remained strong citation indicators during the COVID-19 period, except for Eur. J. Med. Res. due to its smaller sample size (n = 492) than other counterparts (i.e., 41,181, 12,793, and 1464). Three journals showed higher network density coefficients, suggesting a potential foundation for reference-based citation predictions.

CONCLUSION

Despite variations among journals, references effectively predict article citations during the COVID-19 era, underlining the importance of network density. Future studies should delve deeper into the correlation between network density and citation prediction.

Visual analysis of social events and stock market volatility in China and the USA during the pandemic

The COVID-19 pandemic is one of the most severe infectious diseases in recent decades, and has had a significant impact on the global economy, and the stock market. Most existing studies on stock market volatility during the pandemic have been conducted from a data science perspective, with statistical analysis and mathematical models often revealing the superficial relationship between Covid and the stock market at the data level. In contrast, few studies have explored the relationship between more specialised aspects of the pandemic. Specifically, the relationship found between major social events and the stock market. In this work, a multi-source, data-based relationship analysis method is proposed, that collects historical data on significant social events and related stock data in China and the USA, to further explore the potential correlation between stock market index fluctuations and the impact of social events by analysing cross-timeline data. The results suggest and offer more evidence that social events do indeed impact equity markets, and that the indices in both China and the USA were also affected more by the epidemic in 2020 than in 2021, and these indices became less affected by the epidemic as it became the world adapted. Moreover, these relationships may also be influenced by a variety of other factors not covered in this study. This research, so far, is in its initial stage, and the methodology is not rigorous and cannot be applied as an individual tool for decision; however, it could potentially serve as a supplementary tool and provide a multi-dimensional basis for stock investors and policymakers to make decisions.

Global Maps of Avian Leukosis Viruses: Research Trends and Themes Based on Networking

Avian leukosis virus (ALV) has a tremendous adverse impact on the poultry industry. Since its discovery, research on different aspects of ALV have been published. Due to the vast academic emphasis and economic importance of the ALV infection in poultry worldwide, this bibliometric analysis explored the scientific output associated with ALV utilizing the Web of Science (Core Collection) database. The relevant data were collected using the search query "AVIAN LEUKOSIS VIRUS", further refined by document types (article, book chapter, and proceedings paper). Finally, 1060 items with full records were imported in Plaintext and tab-delimited formats. The data analysis was carried out using MS Excel, VOS viewer, and R (Biblioshiny) software. Chinese and American research institutions produced the majority of papers during study time period. The Journal of Virology and Avian Diseases appeared as the favorite journal/source for publications. Apart from the avian leukosis virus and the ALV-J, the important keywords mentioned included avian leukosis virus subgroup j, chicken, and retrovirus. The analysis revealed substantial findings on ALV research, with a strong research response from the USA and China.

How COVID-19 Affected the Journal Impact Factor of High Impact Medical Journals: Bibliometric Analysis

BACKGROUND

Journal impact factor (IF) is the leading method of scholarly assessment in today's research world, influencing where scholars submit their research and where funders distribute their resources. COVID-19, one of the most serious health crises, resulted in an unprecedented surge of publications across all areas of knowledge. An important question is whether COVID-19 affected the gold standard of scholarly assessment.

OBJECTIVE

In this paper, we aimed to comprehensively compare the productivity trends of COVID-19 and non-COVID-19 literature as well as track their evolution and scholarly impact across 3 consecutive calendar years.

METHODS

We took as an example 6 high-impact medical journals (Annals of Internal Medicine [Annals], The British Medical Journal [The BMJ], Journal of the American Medical Association [JAMA], The Lancet, Nature Medicine [NatMed], and The New England Journal of Medicine [NEJM]) and searched the literature using the Web of Science database for manuscripts published between January 1, 2019, and December 31, 2021. To assess the effect of COVID-19 and non-COVID-19 literature in their scholarly impact, we calculated their annual IFs and percentage changes. Thereafter, we estimated the citation probability of COVID-19 and non-COVID-19 publications along with their rates of publication and citation by journal.

RESULTS

A significant increase in IF change for manuscripts including COVID-19 published from 2019 to 2020 (P=.002; Annals: 283%; The BMJ: 199%; JAMA: 208%; The Lancet: 392%; NatMed: 111%; and NEJM: 196%) and to 2021 (P=.007; Annals: 41%; The BMJ: 90%; JAMA: 6%; The Lancet: 22%; NatMed: 53%; and NEJM: 72%) was seen, against non-COVID-19 ones. The likelihood of highly cited publications was significantly increased in COVID-19 manuscripts between 2019 and 2021 (Annals: z=3.4, P<.001; The BMJ: z=4.0, P<.001; JAMA: z=3.8, P<.001; The Lancet: z=3.5, P<.001; NatMed: z=5.2, P<.001; and NEJM: z=4.7, P<.001). The publication and citation rates of COVID-19 publications followed a positive trajectory, as opposed to non-COVID-19. The citation rate for COVID-19 publications peaked by the second quarter of 2020 while that of the publication rate approximately a year later.

CONCLUSIONS

The rapid surge of COVID-19 publications emphasized the capacity of scientific communities to respond against a global health emergency, yet inflated IFs create ambiguity as benchmark tools for assessing scholarly impact. The immediate implication is a loss in value of and trust in journal IFs as metrics of research and scientific rigor perceived by academia and society. Loss of confidence toward procedures employed by highly reputable publishers may incentivize authors to exploit the publication process by monopolizing their research on COVID-19 and encourage them to publish in journals of predatory behavior.

The evolution of e-government research over two decades: applying bibliometrics and science mapping analysis

Purpose

This study uses a bibliometric approach to analyze the overall status of e-government research by revealing patterns and trends that would help gain a broad understanding of global developments in the field and future directions.

Design/methodology/approach

All documents related to e-government published from 2000 to 2019 were extracted from the Scopus and the Digital Government Reference Library databases. Bibexcel, Biblioshiny, and VOSviewer were used to perform the analyses and visualize the science mapping.

Findings

The results showed that 21,320 documents related to e-government research were published and cited 263,179 times. The annual growth rate of e-government research has reached 21.50%. The regression analysis showed that the growth rate is expected to increase gradually over the coming years. Despite the significant role that conference papers play in the e-government literature, the impact of articles far exceeds conference papers. The University of Albany (SUNY) has played an important role in e-government research in terms of production and impact. Furthermore, the study revealed some countries that are expected to play a prominent role in e-government research, as well as several topics that may attract more attention soon.

Originality/value

The results presented in this study and the comprehensive picture obtained about the e-government field make it an effective supplement to the expert evaluation. Thus, researchers, research managers, policymakers, institutions, funding agencies, and governments can rely on it.

Differences in Global Scientific Production Between New mRNA and Conventional Vaccines Against COVID-19

The search for effective vaccines to stop the COVID-19 pandemic has led to an unprecedented amount of global scientific production and activity. This study aimed to analyze global scientific production on the different vaccine types (mRNA and conventional) that were validated for COVID-19 during the years 2020-2021. The scientific production generated on COVID-19 vaccines during the period 2020-2021 totaled the enormous amount of 20,459 studies published. New mRNA vaccines clearly showed higher production levels than conventional vaccines (viral and inactivated vectors), with 786 and 350 studies, respectively. The USA is the undisputed leader in the global production on COVID-19 vaccines, with Israel and Italy also playing an important role. Among the journals publishing works in this field, the New England Journal of Medicine, the British Medical Journal, and Vaccines stand out from the rest as the most important. The keyword 'immunogenicity' and its derivatives have been more researched for the new mRNA vaccines, while thrombosis has been more studied for conventional vaccines. The massive scientific production generated on COVID-19 vaccines in only two years has shown the enormous gravity of the pandemic and the extreme urgency to find a solution. This high scientific production and the main keywords found for the mRNA vaccines indicate the great potential that these vaccines have against COVID-19 and future infectious diseases. Moreover, this study provides valuable information for guiding future research lines and promoting international collaboration for an effective solution.

A Bibliometric Analysis of Research Publications of the Bucharest University of Economic Studies in Time of Pandemics: Implications for Teachers’ Professional Publishing Activity

The epidemic has forced the academic world, regardless of nation of origin, to unify to find a response to the economic and social difficulties we confront as quickly as possible. This paper investigates how academic performance in terms of scientific publications, especially during the pandemic period, may constitute the premises for boosting professional well-being. The analysis focuses on the researchers and professors of the Bucharest Academy of Economic Studies, analysing in a comparative way the academic performance during the pandemic as a fundamental side of their professional career. To do that, two samples of scientific publications collected between January 2020 and December 2021 were investigated. The first sample comprised 1411 documents indexed in the WoS database, while the second one was formed by 876 documents indexed in the Scopus database. All samples were published during the pandemic and have the university’s affiliation. The empirical findings indicated that the pandemic has created a boost in the number and quality of medical publications for the professors at the Bucharest University of Economic Studies. They created new multidisciplinary teams (economics and medicine), strengthening and widening national and international collaborations.

Current Scientific Research Trends on Salivary Biomarkers: A Bibliometric Analysis

Salivary biomarkers are indicators of many biological and pathological conditions and provide further information regarding the early detection of diseases. This bibliometric analysis aims to identify and evaluate the scientific literature addressing salivary biomarkers from a dental perspective, to identify the most prolific organizations, authors, journals, countries, and keywords used within this research domain. An electronic search was performed using Elsevier’s Scopus database. From a total of 587 retrieved papers (published between 1997 and 2021), 399 were selected. For the data analysis and its visualization, the title of the articles, year of publication, countries, authors, journals, articles, and keywords were analyzed using Microsoft Excel and VOSviewer (a bibliometric software program). An increase in the number of publications was identified from 1997 to 2021. The United States (U.S.) published the most papers (84) and received the highest citations (3778), followed by India and Brazil. The Journal of Periodontology published the highest number of articles (39) that received the highest citations. The University of Kentucky from the U.S. published most of the papers related to salivary biomarkers that received the highest citations. Timo Sorsa published the most papers (14 papers), while Craig Miller was the highest cited author (754 citations). Concerning the highly cited papers, a paper by Micheal et al., published in 2010, received the highest citations (487 citations). “Saliva”, followed by “human”, were the most common keywords used by the authors in the papers related to salivary biomarkers. The findings of this analysis revealed an increase in salivary biomarker-related publications that positively influenced the number of citations each paper received. The U.S. produced the most publications that received the highest citations, and the University of Kentucky, U.S., was the most prominent. The articles were mostly published in the Journal of Periodontology and received the highest number of citations.

A Bibliometric Analysis of COVID‐19 Publications in Nursing By Visual Mapping Method

Aim

This study conducted a bibliometric analysis of nursing publications on the COVID‐19 between 1 January 2020, and 24 October 2021.

Background

COVID‐19 has been a hot research topic that has attracted many researchers from various disciplines. One of the ways to combat the COVID‐19 pandemic is to produce knowledge and present it with a holistic approach. Therefore, it is crucial to make bibliometric and content analyses of scientific publications. Scientific data should be evaluated to keep up with the developments in the nursing profession and practices during the COVID‐19 pandemic.

Methods

Data were collected from the Web of Science database. The sample consisted of 1280 publications that met the inclusion criteria. The data were analysed using descriptive content and bibliometric analysis. The VOSviewer, a mapping and visualization software program, was used for bibliometric analysis.

Results

The United States is one of the countries with the highest number of publications, citations and international cooperation during the pandemic. Of all these publications, 1183 (92.42%) are original articles. The Journal of Nursing Management has the highest number of publications and citations. The publications focus primarily on the topics of COVID‐19, pandemic, nursing, coronavirus and nurses. The current topics that the publications address are online education, online learning, practice, nursing student, perceived stress, stress, fear, quality of life and experience to determine the impacts of the pandemic on mental health nursing education.

Conclusions

The COVID‐19 pandemic has an impact on nursing, and the number of publications is increasing worldwide. In the early days of the pandemic, researchers focused on the topics of coronavirus infections, infection control, global health, health policy and nursing policy. Afterward, they addressed current topics, such as education and the psychological effects of the pandemic.

Implications for nursing management

Our results will help nurse managers identify issues related to COVID‐19 that have not been researched yet and have not been adequately explained in their own institutions. They will also help them choose appropriate journals to get their studies published, appropriate countries to cooperate with and access information about the studies on the subject matter. Our results will also help them make evidence‐based decisions about mental health and nursing education.

How has academia responded to the urgent needs created by COVID-19? A multi-level global, regional and national analysis

In the context of the COVID-19 pandemic, gaining insights into how academia has responded to this urgent challenge is of great significance. This article presents academic response patterns at a global, regional and national level from an analysis of publication volume versus reported cases of COVID-19, scientific collaboration and research focus. We also compare academic activity associated with this newly emerging infection to that related to long-standing infections. Our results show that the research community has responded quickly to COVID-19. The highly developed countries, which have the highest number of confirmed cases, are also the major academic contributors. National-level analysis reveals diverse response patterns from different countries. Specifically, academic research in the United Kingdom remained at a relatively constant level throughout the whole year (2020), while the global share of China’s research output was prone to shift as its domestic pandemic status changed. Strong alliances have formed among countries with academic capabilities in response to the COVID-19 pandemic. The distribution of disciplines is relatively decentralised, indicating that a diverse and broad knowledge base contributes to the COVID-19 literature. Most of the analysed countries show dynamic patterns of research focus that vary over time as the pandemic evolves, except India. As one of the world’s biggest suppliers of vaccines, India makes consistent efforts on vaccine research, especially those related to pharmaceutical preparations. Our findings may serve as resources for fostering strategies to respond to future threats of pandemics.

Bibliometric Analysis of Global Research Productivity on Vitamin D and Bone Metabolism (2001-2020): Learn from the Past to Plan Future

Vitamin D has long been known for preserving bone and non-skeletal health. Despite its magnitude of impact, scarce literature has explored the evolution of the relevant published literature. This study aimed at evaluating the trends and performance of Vitamin D and bone metabolism-related publications (2001−2020). All pertinent English language 16,887 articles were searched and extracted from the Web of Science (WoS) database and “R-Bibliometrix” was used for comprehensive analysis. Around 60,149 authors contributed from 114 countries, showing the USA on top with >1/4th of all articles, followed by Japan, China, and the United Kingdom. For authors, Cooper C, Dawson-Hughes B, and Holick MF were found to have written the most articles, citations and highest h-index, respectively. Corresponding authors from the top 20 countries collectively were responsible for around 84% of the articles. Among 2735 sources, Osteoporosis International (632), Journal of Bone and Mineral Research (569), and Bone (448) were foremost. Most prominent sources showed recent declining contributions. The increasing trend of publications with a higher spike from 2008 to 2014, followed by a gradual increase till 2017, was observed. Leading countries, affiliations, and authors showed collaborative publications and were mostly from developed countries with limited contributions, particularly from low- and middle-income countries.

Bibliometric Analysis of International Scientific Production on Pharmacologic Treatments for SARS-CoV-2/COVID-19 During 2020

Background

COVID-19 is causing a grave global health and economic crisis and the fight against the pandemic has led to unprecedented scientific activity. Bibliometrics could be a useful tool for guiding future researches lines and promoting international collaboration for an effective treatment. For this purpose, we have conducted a bibliometric analysis of scientific publications on drugs and therapies used to treat COVID-19 during 2020.

Methods

Data source: Web of Science. We gathered data on scientific production relating to drugs used to treat COVID-19. We calculated impact factors and analyzed production by institution, country, and journal, visualizing our results in bibliometric networks.

Results

In 1 year, production relating to COVID-19 exceeded 100 000 publications, with over 6,500 on Drugs and COVID-19. Research into hydroxychloroquine and chloroquine, remdesivir, lopinavir and ritonavir, tocilizumab and convalescent plasma is particularly noteworthy. Mean citations/study range from 11.9 to 15.4. Producer institutions fall into three groups: one in the US and centered on Harvard Medical School; another in Europe led by INSERS; and another in China led by Huazhong University of Science and Technology. Production by journal is widespread but the Journal of Medical Virology, International Journal of Antimicrobial Agents, and American Journal of Transplantation are noteworthy.

Conclusions

The volume of research that is currently under way is comparable to the magnitude of the pandemic itself. Such a high volume of studies is infrequent and the impact they have achieved has no known precedent. The producing countries are those with highest incidence of the pandemic and greatest scientific potential; moreover, inter-agency and international collaboration has reached extraordinarily high levels.

Prevalence of Anxiety in University Students during the COVID-19 Pandemic: A Systematic Review

There is a dearth of evidence synthesis on the prevalence of anxiety among university students even though the risk of psychological disorders among this population is quite high. We conducted a quantitative systematic review to estimate the global prevalence of anxiety among university students during the COVID-19 pandemic. A systematic search for cross-sectional studies on PubMed, Scopus, and PsycINFO, using PRISMA guidelines, was conducted from September 2020 to February 2021. A total of 36 studies were included, using a random-effects model to calculate the pooled proportion of anxiety. A meta-analysis of the prevalence estimate of anxiety yielded a summary prevalence of 41% (95% CI = 0.34–0.49), with statistically significant evidence of between-study heterogeneity (Q = 80801.97, I² = 100%, p ≤ 0.0001). A subgroup analysis reported anxiety prevalence in Asia as 33% (95% CI:0.25–0.43), the prevalence of anxiety in Europe as 51% (95% CI: 0.44–0.59), and the highest prevalence of anxiety in the USA as 56% (95% CI: 0.44–0.67). A subgroup gender-based analysis reported the prevalence of anxiety in females as 43% (95% CI:0.29–0.58) compared to males with an anxiety prevalence of 39% (95% CI:0.29–0.50). University students seem to have a high prevalence of anxiety, indicating an increased mental health burden during this pandemic.

Measuring the funding landscape of COVID-19 research

Purpose

The purpose of the study is to map the funding status of COVID-19 research. The various aspects, such as funding ratio, geographical distribution of funded articles, journals publishing funded research and institutions that sponsor the COVID-19 research are studied. To visualize the country collaboration network and research trends/hotspots in the field of COVID-19 funded research, keyword analysis is also performed. The open-access (OA) status of the funded research on COVID-19 is also discussed.

Design/methodology/approach

The leading indexing and abstracting database, i.e. Web of Science (WoS), was used to retrieve the funded articles published on the topic COVID-19. The scientometric approach, more particularly “funding acknowledgment analysis (FAA),” was used to study the research funding.

Findings

A total of 5,546 publications of varied nature have been published on COVID-19, of which 1,760 are funded, thus indicating a funding ratio of 32%. China is the leading producer of funded research (760, 43.182%) on COVID-19 followed by the USA (482, 27.386%), England (179, 10.17%), Italy (119, 6.761%), Germany (107, 6.08%) and Canada (107, 6.08%). China is also in lead in terms of the funding ratio (60.94%). However, the funding ratio of the USA (31.54%) is at 11th rank behind Canada (40.68%), Germany (34.18%) and England (35.87%). The USA occupies a central position in the collaboration network having the highest score of articles with other countries (n = 489), with the USA–China collaboration ranking first (n = 123). National Natural Science Foundation of China (NSFC) is the largest source of funding for COVID-19 research, supporting 342 (19.432%) publications, followed by the United States Department of Health Human Services (DHHS) and National Institute of Health (NIH), USA with 211 (11.989%) and 200 (11.364%) publications, respectively. However, China's National Key Research and Development Program achieves the highest citation impact (80.24) for its funded publications. Journal of Medical Virology, Science of the Total Environment and EuroSurveillance are the three most prolific journals publishing 63 (3.58%), 35 (1.989%) and 32 (1.818%), respectively, of the sponsored research articles on the COVID-19. A total of 3,138 institutions produce funded articles with Huazhong University of Science Technology and Wuhan University from China at the forefront publishing 92 (5.227%) and 83 (4.716%) publications, respectively. The funded research on COVID-19 is largely available in OA mode (1,674, 95.11%) and mainly through the Green and Bronze routes. The keyword clustering reveals that the articles mainly focus on the impact, structure and clinical characteristics of the virus.

Research limitations/implications

The study's main limitation is that the results are based on the publications indexed by WoS, which has limited coverage compared to other databases. Moreover, all the funding agencies do not require or authors miss to acknowledge funding sources in their publications, which ultimately undermines the number of funded publications. The research publications on COVID-19 are also proliferating; thus, the study's findings shall be valid for a minimum period.

Practical implications

The funding of research on the COVID-19 is highly essential to accelerate innovative research and help countries fight against the global pandemic. The study's findings reflect the efforts made by nations and institutions to remove the financial and accessibility hurdles. It not only underscores the lead of the USA in the research on COVID-19, but also shows China as a forerunner in sponsoring the research, thus, helping to know the contribution of nations toward understanding the dynamics of pandemic and controlling it. The study will help healthcare practitioners and policymakers recognize the areas that remain the focus of sponsored research on COVID-19 and other left-out areas that need to be taken up and thus may help in policy formulation. It further highlights the impact of prolific funding agencies so that efforts may be initiated to increase the impact and thereby the returns of investment. The study can help to map the scientific structure of COVID-19 through the lens of funded research and recognize core inclinations of its development. Overall, a comprehensive analysis has been performed to present the detailed characteristics of sponsored research on emerging area of COVID-19, and it is informative, useful and one of its kind on the theme.

Originality/value

The study explores the funding support of research on COVID-19 and its other aspects, along with the mode of availability.

Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining

The COVID-19 pandemic has wreaked havoc in every country in the world, with serious health-related, economic, and social consequences. Since its outbreak in March 2020, many researchers from different fields have joined forces to provide a wide range of solutions, and the support for this work from artificial intelligence (AI) and other emerging concepts linked to intelligent data analysis has been decisive. The enormous amount of research and the high number of publications during this period makes it difficult to obtain an overall view of the different applications of AI to the management of COVID-19 and an understanding of how research in this field has been evolving. Therefore, in this paper, we carry out a scientometric analysis of this area supported by text mining, including a review of 18,955 publications related to AI and COVID-19 from the Scopus database from March 2020 to June 2021 inclusive. For this purpose, we used VOSviewer software, which was developed by researchers at Leiden University in the Netherlands. This allowed us to examine the exponential growth in research on this issue and its distribution by country, and to highlight the clear hegemony of the United States (USA) and China in this respect. We used an automatic process to extract topics of research interest and observed that the most important current lines of research focused on patient-based solutions. We also identified the most relevant journals in terms of the COVID-19 pandemic, demonstrated the growing value of open-access publication, and highlighted the most influential authors by means of an analysis of citations and co-citations. This study provides an overview of the current status of research on the application of AI to the pandemic.

Scientists’ response to global public health emergencies: A bibliometrics perspective

The unprecedented COVID-19 outbreak at the end of 2019 has produced a worldwide health crisis. Scientific research, especially international research collaboration, is crucial to deal successfully with the epidemic. This article aims to review the response modes, and especially the international collaboration characteristic, of the academic community to similar public health events in the past. Based on relevant studies of four major public health emergencies in the past, the major public health emergencies were regarded as ‘new knowledge’ in the academic field. By using knowledge diffusion indicators, such as the breadth and speed of diffusion, and combined with the development characteristics of the event, this article explores the diffusion characteristics of the four major public health emergencies in the academic exchange system and then identifies the academic community’s response mode to the outbreaks. In addition, the characteristics of international collaboration in response to the public health events and the impact of international collaboration on the academic community’s response are analysed. Through the analysis of the international collaboration network, the cooperative groups and core countries in the research collaboration network related to the major public health emergencies are obtained. In terms of COVID-19, it is found that the response speed and intensity of scientists have been significantly improved, but more focus should be given to international collaboration. Our findings could be beneficial to both decision-makers and researchers in policy formulation and conducting research, respectively, to optimally deal with COVID-19 and possible outbreaks in the future.

The emergence of scholarly literature on physical/social distancing related to Coronavirus: A bibliometric analysis

Background: The world is witnessing new public health crises due to the emergence of the novel coronavirus. This study aims to present a bibliometric analysis of research on coronavirus-related physical/social distancing.

Design and Methods: In this study, a bibliometric analysis was applied to see the research productivity and its impact on coronavirus- related physical/social distancing. For this purpose, Scopus was used to retrieve the data for the analysis. A total of 2900 records was downloaded from the database for analysis.

Results: The findings revealed that the top four authors published their research in the year 2020. The study ranked the British Medical Journal (BMJ) at the top position on publishing the research on the topic. Similarly, the USA took the lead in all countries in producing research on the topic. The researchers preferred the document type ‘Article’ for sharing their research, and a single authorship pattern was dominated on all other patterns.

Conclusions: Plenty of bibliometric studies are available on coronavirus, but not a single study is found on coronavirus-related physical/social distancing. This study will be valuable in identifying different bibliometric dimensions on the topic.

COVID-19 and diabetes: Analysis of the scientific production indexed in Scopus

BACKGROUND AND AIM

COVID-19 has affected the world population, with a higher impact among at-risk groups, such as diabetic patients. This has led to an exponential increase in the number of studies related to the subject, although their bibliometric characteristics are unknown. This article aims to characterize the world scientific production on COVID-19 and diabetes indexed in Scopus.

METHODS

Articles on the subject were retrieved using a search strategy and bibliometric indicators of production, visibility, collaboration and impact were studied.

RESULTS

The total scientific production was 1956 documents, which have 35086 citations and an h-index of 67. Articles published in Diabetes and Metabolic Syndrome: Clinical Research and Reviews (n = 127), as well as those by researchers from the United States (n = 498) predominated. Articles by Chinese authors (n = 314) had the highest impact according to the received citations (n = 21757). India, China and Spain are leading countries in terms of the research in which they participate. There is extensive international scientific collaboration led by China, the United States and Italy.

CONCLUSION

The volume of publications on COVID-19 and diabetes and their scientific impact show the incentive that the study of these diseases represents for the scientific community worldwide.

A bibliometric analysis of the dental scientific literature on COVID-19

Objectives

The rapid production of a large volume of literature during the early phase of the COVID-19 outbreak created a substantial burden for clinicians and scientists. Therefore, this manuscript aims to identify and describe the scientific literature addressing COVID-19 from a dental research perspective, in terms of the manuscript origin, research domain, study type, and level of evidence (LoE).

Materials and methods

Data were retrieved from Web of Science, Scopus, and PubMed. A descriptive analysis of bibliographic data, collaboration network, and keyword co-occurrence analysis were performed. Articles were further classified according to the field of interest, main research question, type of study, and LoE.

Results

The present study identified 296 dental scientific COVID-19 original papers, published in 89 journals, and co-authored by 1331 individuals affiliated with 429 institutions from 53 countries. Although 81.4% were single-country papers, extensive collaboration among the institutions of single countries (Italian, British, and Brazilian institutions) was observed. The main research areas were as follows: the potential use of saliva and other oral fluids as promising samples for COVID-19 testing, dental education, and guidelines for the prevention of COVID-19 transmission in dental practice. The majority of articles were narrative reviews, cross-sectional studies, and short communications. The overall LoE in the analyzed dental literature was low, with only two systematic reviews with the highest LoE I.

Conclusion

The dental literature on the COVID-19 pandemic does not provide data relevant to the evidence-based decision-making process. Future studies with a high LoE are essential to gain precise knowledge on COVID-19 infection within the various fields of Dentistry.

Clinical relevance

The published dental literature on COVID-19 consists principally of articles with a low level of scientific evidence which do not provide sufficient reliable high-quality evidence that is essential for decision making in clinical dental practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00784-021-03916-6.

Prevalence of anxiety and depression in South Asia during COVID-19: A systematic review and meta-analysis

INTRODUCTION

The COVID-19 pandemic has impacted biopsychosocial health and wellbeing globally. Pre-pandemic studies suggest a high prevalence of common mental disorders, including anxiety and depression in South Asian countries, which may aggravate during this pandemic. This systematic meta-analytic review was conducted to estimate the pooled prevalence of anxiety and depression in South Asian countries during the COVID-19 pandemic.

METHOD

We systematically searched for cross-sectional studies on eight major bibliographic databases and additional sources up to October 12, 2020, that reported the prevalence of anxiety or depression in any of the eight South Asian countries. A random-effects model was used to calculate the pooled proportion of anxiety and depression.

RESULTS

A total of 35 studies representing 41,402 participants were included in this review. The pooled prevalence of anxiety in 31 studies with a pooled sample of 28,877 was 41.3% (95% confidence interval [CI]: 34.7-48.1, I 2 = 99.18%). Moreover, the pooled prevalence of depression was 34.1% (95% CI: 28.9-39.4, I 2 = 99%) among 37,437 participants in 28 studies. Among the South Asian countries, India had a higher number of studies, whereas Bangladesh and Pakistan had a higher pooled prevalence of anxiety and depression. No studies were identified from Afghanistan, Bhutan, and Maldives. Studies in this review had high heterogeneity, high publication bias confirmed by Egger's test, and varying prevalence rates across sub-groups.

CONCLUSION

South Asian countries have high prevalence rates of anxiety and depression, suggesting a heavy psychosocial burden during this pandemic. Clinical and public mental health interventions should be prioritized alongside improving the social determinants of mental health in these countries. Lastly, a low number of studies with high heterogeneity requires further research exploring the psychosocial epidemiology during COVID-19, which may inform better mental health policymaking and practice in South Asia.

COVID-19 in Management Studies: A Systematic Literature Review

In 2020, the whole world had to face a pandemic with inevitable profound changes in all aspects of life, from the social to the economic sphere. The profound economic crisis that followed the rise of the pandemic has pushed firms and researchers to question the necessary changes and new challenges for the survival of businesses. In this scenario, the aim of the paper is to analyze and classify the main contributions published on the topic of COVID-19 in managerial literature, seeking to discover the perspective and the gaps and outline future avenues of research. A systematic review of the literature has been performed. The results highlight the orientation of studies in this field and the various links between different aspects that emerged. Limitations and implications complete the research.

A Comprehensive Overview of the COVID-19 Literature: Machine Learning-Based Bibliometric Analysis

BACKGROUND

Shortly after the emergence of COVID-19, researchers rapidly mobilized to study numerous aspects of the disease such as its evolution, clinical manifestations, effects, treatments, and vaccinations. This led to a rapid increase in the number of COVID-19-related publications. Identifying trends and areas of interest using traditional review methods (eg, scoping and systematic reviews) for such a large domain area is challenging.

OBJECTIVE

We aimed to conduct an extensive bibliometric analysis to provide a comprehensive overview of the COVID-19 literature.

METHODS

We used the COVID-19 Open Research Dataset (CORD-19) that consists of a large number of research articles related to all coronaviruses. We used a machine learning-based method to analyze the most relevant COVID-19-related articles and extracted the most prominent topics. Specifically, we used a clustering algorithm to group published articles based on the similarity of their abstracts to identify research hotspots and current research directions. We have made our software accessible to the community via GitHub.

RESULTS

Of the 196,630 publications retrieved from the database, we included 28,904 in our analysis. The mean number of weekly publications was 990 (SD 789.3). The country that published the highest number of COVID-19-related articles was China (2950/17,270, 17.08%). The highest number of articles were published in bioRxiv. Lei Liu affiliated with the Southern University of Science and Technology in China published the highest number of articles (n=46). Based on titles and abstracts alone, we were able to identify 1515 surveys, 733 systematic reviews, 512 cohort studies, 480 meta-analyses, and 362 randomized control trials. We identified 19 different topics covered among the publications reviewed. The most dominant topic was public health response, followed by clinical care practices during the COVID-19 pandemic, clinical characteristics and risk factors, and epidemic models for its spread.

CONCLUSIONS

We provide an overview of the COVID-19 literature and have identified current hotspots and research directions. Our findings can be useful for the research community to help prioritize research needs and recognize leading COVID-19 researchers, institutes, countries, and publishers. Our study shows that an AI-based bibliometric analysis has the potential to rapidly explore a large corpus of academic publications during a public health crisis. We believe that this work can be used to analyze other eHealth-related literature to help clinicians, administrators, and policy makers to obtain a holistic view of the literature and be able to categorize different topics of the existing research for further analyses. It can be further scaled (for instance, in time) to clinical summary documentation. Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.

A scientometric analysis on coronaviruses research (1900-2020): Time for a continuous, cooperative and global approach

Infectious diseases remain a complex, recurring, and challenging public health hazard. Coronaviruses have led to multidimensional consequences on health, mobility, and socio-economic conditions. Despite the significance and magnitude of impact from epidemics to the pandemic, literature is sparse on comprehensive coronaviruses related research performance over time. This study aimed at a scientometric evaluation of coronaviruses related literature including COVID-19. Data related to Coronavirus research was extracted from the Web of Science (WoS). All types of publications (28,846) were included and retrieved. To measure the quantity and quality of the publications, "R-Bibliometrix" package was used for detailed analysis exploring a wide range of indicators. Generally, an increasing trend was observed over time led by the USA and China followed by the United Kingdom, Europe, and few other developed countries. The last two decades contributed around 39.5% of documents while only 06 months of 2020 additionally contributed around 46.5% of total documents. Earlier shorter spikes of increased post epidemic publications followed by decreased productivity were detected in the last 2 decades and showed a lack of continuity-'a research epidemic following a disease epidemic'. Articles (53.4%) were the most common publication type. Journal of Virology, British Medical Journal (BMJ), and Virology were leading sources while BMJ, and Lancet showed increased contributions recently. Overall, similar trends of top authors were observed in terms of productivity, impact, collaborations, funding sources, and affiliations with few exceptions mainly from affected regions. Top 20 countries contributed >89% of documents suggesting a lack of global efforts. Networking was found to be mainly among developed nations with limited contributions from resource-limited countries perhaps requiring more cooperation. Recent post-COVID publications rise is highest, unprecedented, and rapidly growing. Authors strongly recommend recent COVID-19 pandemic as a call for continuous, more cooperative, and collective global research.

Digital screen time during the COVID-19 pandemic: a public health concern

Due to the restrictions imposed to contain the coronavirus disease 2019 (COVID-19) pandemic, different population groups have adapted to varying screen time levels, which may have profound implications on their physical and mental wellbeing. Several empirical studies included in this review reported a sudden upward change in screen time across different population groups. A higher number of people with increased screen time compared to their pre-pandemic state and prolonged duration of total screen time substantiates such assertions. The available evidence suggests that screen time is associated with obesity, hypertension, type 2 diabetes, myopia, depression, sleep disorders, and several non-communicable diseases. This elevated burden of diseases is more prevalent among individuals who have sedentary lifestyles and other unhealthy behaviors that are likely to increase during quarantine or isolation due to COVID-19. Hence, it is critical to assess the adverse health outcomes that may appear as long-term consequences of such behavior. Researchers and practitioners need to revisit the available guidelines and incorporate evidence-based interventions for preventing unhealthy screen time among the affected individuals. Such interventions may address harmful behaviors associated with screen time and promote active lifestyles that may improve health across populations during and after this pandemic.

A Comparative NLP-Based Study on the Current Trends and Future Directions in COVID-19 Research

COVID-19 is a global health crisis that has altered human life and still promises to create ripples of death and destruction in its wake. The sea of scientific literature published over a short time-span to understand and mitigate this global phenomenon necessitates concerted efforts to organize our findings and focus on the unexplored facets of the disease. In this work, we applied natural language processing (NLP) based approaches on scientific literature published on COVID-19 to infer significant keywords that have contributed to our social, economic, demographic, psychological, epidemiological, clinical, and medical understanding of this pandemic. We identify key terms appearing in COVID literature that vary in representation when compared to other virus-borne diseases such as MERS, Ebola, and Influenza. We also identify countries, topics, and research articles that demonstrate that the scientific community is still reacting to the short-term threats such as transmissibility, health risks, treatment plans, and public policies, underpinning the need for collective international efforts towards long-term immunization and drug-related challenges. Furthermore, our study highlights several long-term research directions that are urgently needed for COVID-19 such as: global collaboration to create international open-access data repositories, policymaking to curb future outbreaks, psychological repercussions of COVID-19, vaccine development for SARS-CoV-2 variants and their long-term efficacy studies, and mental health issues in both children and elderly.

Coronavirus research before 2020 is more relevant than ever, especially when interpreted for COVID-19

The speed with which biomedical specialists were able to identify and characterize COVID-19 was partly due to prior research with other coronaviruses. Early epidemiological comparisons with Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), also made it easier to predict COVID-19’s likely spread and lethality. This article assesses whether academic interest in prior coronavirus research has translated into interest in the primary source material, using Mendeley reader counts for early academic impact evidence. The results confirm that SARS and MERS research in 2008–2017 experienced anomalously high increases in Mendeley readers in April–May 2020. Nevertheless, studies learning COVID-19 lessons from SARS and MERS or using them as a benchmark for COVID-19 have generated much more academic interest than primary studies of SARS or MERS. Thus, research that interprets prior relevant research for new diseases when they are discovered seems to be particularly important to help researchers to understand its implications in the new context.

Early survey with bibliometric analysis on machine learning approaches in controlling COVID-19 outbreaks

BACKGROUND AND OBJECTIVE

The COVID-19 pandemic has caused severe mortality across the globe, with the USA as the current epicenter of the COVID-19 epidemic even though the initial outbreak was in Wuhan, China. Many studies successfully applied machine learning to fight COVID-19 pandemic from a different perspective. To the best of the authors' knowledge, no comprehensive survey with bibliometric analysis has been conducted yet on the adoption of machine learning to fight COVID-19. Therefore, the main goal of this study is to bridge this gap by carrying out an in-depth survey with bibliometric analysis on the adoption of machine learning-based technologies to fight COVID-19 pandemic from a different perspective, including an extensive systematic literature review and bibliometric analysis.

METHODS

We applied a literature survey methodology to retrieved data from academic databases and subsequently employed a bibliometric technique to analyze the accessed records. Besides, the concise summary, sources of COVID-19 datasets, taxonomy, synthesis and analysis are presented in this study. It was found that the Convolutional Neural Network (CNN) is mainly utilized in developing COVID-19 diagnosis and prognosis tools, mostly from chest X-ray and chest CT scan images. Similarly, in this study, we performed a bibliometric analysis of machine learning-based COVID-19 related publications in the Scopus and Web of Science citation indexes. Finally, we propose a new perspective for solving the challenges identified as direction for future research. We believe the survey with bibliometric analysis can help researchers easily detect areas that require further development and identify potential collaborators.

RESULTS

The findings of the analysis presented in this article reveal that machine learning-based COVID-19 diagnose tools received the most considerable attention from researchers. Specifically, the analyses of results show that energy and resources are more dispenses towards COVID-19 automated diagnose tools while COVID-19 drugs and vaccine development remains grossly underexploited. Besides, the machine learning-based algorithm that is predominantly utilized by researchers in developing the diagnostic tool is CNN mainly from X-rays and CT scan images.

CONCLUSIONS

The challenges hindering practical work on the application of machine learning-based technologies to fight COVID-19 and new perspective to solve the identified problems are presented in this article. Furthermore, we believed that the presented survey with bibliometric analysis could make it easier for researchers to identify areas that need further development and possibly identify potential collaborators at author, country and institutional level, with the overall aim of furthering research in the focused area of machine learning application to disease control.

A Bibliometric Analysis of COVID-19 across Science and Social Science Research Landscape

The lack of knowledge about the COVID-19 pandemic has encouraged extensive research in the academic sphere, reflected in the exponentially growing scientific literature. While the state of COVID-19 research reveals it is currently in an early stage of developing knowledge, a comprehensive and in-depth overview is still missing. Accordingly, the paper’s main aim is to provide an extensive bibliometric analysis of COVID-19 research across the science and social science research landscape, using innovative bibliometric approaches (e.g., Venn diagram, Biblioshiny descriptive statistics, VOSviewer co-occurrence network analysis, Jaccard distance cluster analysis, text mining based on binary logistic regression). The bibliometric analysis considers the Scopus database, including all relevant information on COVID-19 related publications (n = 16,866) available in the first half of 2020. The empirical results indicate the domination of health sciences in terms of number of relevant publications and total citations, while physical sciences and social sciences and humanities lag behind significantly. Nevertheless, there is an evidence of COVID-19 research collaboration within and between different subject area classifications with a gradual increase in importance of non-health scientific disciplines. The findings emphasize the great need for a comprehensive and in-depth approach that considers various scientific disciplines in COVID-19 research so as to benefit not only the scientific community but evidence-based policymaking as part of efforts to properly respond to the COVID-19 pandemic.

Alice in Wonderland syndrome (AIWS): a research overview

BACKGROUND

Alice in Wonderland syndrome (AIWS) is a rare neuropsychiatric condition characterized by distorted visual perceptions, body schema, and experience of time. A global overview of research on AIWS can inform future developments and clinical practice in this field. This bibliometric study aimed to analyze the characteristics of the global research landscape on AIWS.

METHODS

Bibliometric data on AIWS related publications published until 2019 were retrieved from the Web of Science database. The data were analyzed using statistical and scientometric tools to evaluate the publication trends, key research domains, top contributing journals, institutions, and countries associated with AIWS-related research.

RESULTS

A total of 125 published items were analyzed with a mean of 3 authors and 8.15 citations per document. Most articles were published after 2008, in medical journals focused on neuropsychiatric sciences, and most institutions affiliated with AIWS research were based on high-income countries. Major research domains associated with AIWS included visual disturbances, body image, migraine, infections, risk factors, and other clinical correlates. Several overarching domains were identified; however, clinical research on diagnosis, treatment, and prognosis of AIWS is relatively limited.

CONCLUSION

The current research landscape informs a developing trend in AIWS research in selected regions and specialties. Future research should emphasize multidisciplinary and translational investigations on clinical and epidemiological areas through global collaborations that may advance the knowledge and practice on AIWS.

Evaluating research performance of Coronavirus and Covid-19 pandemic using scientometric indicators

Purpose

This study is an attempt to evaluating the growth of scientific literature in the domain of coronavirus and Covid-19 pandemic research based on scientometric indicators: prolific countries and relative citation impact (RCI); influential institutions; author analysis and network, h-index and citation; DC (degree of collaboration), CC (collaboration coefficient), MCI (modified collaboration index) in the subject domain of coronavirus and Covid-19 research.

Design/methodology/approach

The authors adopted approaches to obtain the literature data from Scopus database from 2000 to 2020 by conducting a systematic search using keywords related to the studied subject domain. In total, 15,297 numbers of records were considered for the literature analysis considering the real significant growth of this subject domain. This study presented the scientometric analysis of these publications. Furthermore, statistical correlations have been used to understand the collaboration pattern. Visualization tool VOSviewer is used to construct the co-author network.

Findings

The present study found that 53.57% (8,195) of the research documents published on the open-access platform. Journal of Virology was found to be most preferred journal by the researcher producing around 839(5.48%) articles. USA and China dominate in the research output, and the University of Hong Kong has produced the highest number of research paper 547(3.58%). A significant portion of the research documents are published in the subject domain of medicine (49.70%), followed by immunology and microbiology (35.72%), and biochemistry, genetics and molecular biology subject domains (22.32%). There has been an unparalleled proliferation of publications on COVID-19 since January 2020 and also a significant distribution of research funds across the globe.

Research limitations/implications

The study exclusively examines 15,297 research outputs which have been indexed in the Scopus database from 2000 to 2020 (till 01 April 2020). Thus, documents published in any other different channels and sources which are not covered in Scopus are excluded from the purview of research.

Practical implications

It will be beneficial for researchers and practitioners worldwide for understanding the growth of scientific literature in the coronavirus and COVID-19 and identifying potential collaborator.

Originality/value

Considering the global impact and social distress due to the outbreak of COVID-19 pandemic, this study is significant in the present scenario for identifying the growth of scientific literature in this field and evolving of this domain of research around the globe. The research results are useful to identify valuable research patterns from publications and of developments in the field of coronavirus and COVID-19.

Systematic review of bibliometric studies on SARS-CoV-2

Objective: To perform a systematic review of articles that evaluated the scientific production on SARS-CoV-2 through bibliometric analyzes. Methods: Scopus, Web of Science and Google Scholar databases were used. After applying the pre-established inclusion criteria, 30 articles were included. Results. The total number of articles found in the bibliometric studies on SARS-CoV-2 varied widely from 153 to 21,395 articles and an average equal to 4,279 (± 5,510). A total of 17 countries published within the scope of this study, but only six published more than one article, emphasizing authors from Chinese institutions (17%). Scopus was the most used database in bibliometric studies (50%, n = 15). The articles used 72 different keywords with emphasis on: COVID-19 (15%), SARS-CoV-2 (12%) and 2019-nCoV (9%). Conclusion. We are facing an unprecedented scenario of information about SARS-CoV-2 and this has required a collective scientific effort reflected in the daily publication of hundreds of studies (articles, pre-prints, clinical guides, protocols). Bibliometric methods are being increasingly used by the scientific community to systematize this information. Therefore, the systematic review carried out in this study provided an overview of the bibliometric literature on the SARS-CoV-2 virus.

Machine Learning Maps Research Needs in COVID-19 Literature

As of August 2020, thousands of COVID-19 (coronavirus disease 2019) publications have been produced. Manual assessment of their scope is an overwhelming task, and shortcuts through metadata analysis (e.g., keywords) assume that studies are properly tagged. However, machine learning approaches can rapidly survey the actual text of publication abstracts to identify research overlap between COVID-19 and other coronaviruses, research hotspots, and areas warranting exploration. We propose a fast, scalable, and reusable framework to parse novel disease literature. When applied to the COVID-19 Open Research Dataset, dimensionality reduction suggests that COVID-19 studies to date are primarily clinical, modeling, or field based, in contrast to the vast quantity of laboratory-driven research for other (non-COVID-19) coronavirus diseases. Furthermore, topic modeling indicates that COVID-19 publications have focused on public health, outbreak reporting, clinical care, and testing for coronaviruses, as opposed to the more limited number focused on basic microbiology, including pathogenesis and transmission.

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AI/machine learning techniques can analyze coronavirus research at massive scale

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COVID-19 research has so far focused on non-lab-based (e.g., observational) research

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COVID-19 lab-based/basic microbiological research is less prevalent than expected

The impact of the COVID-19 pandemic has led scientists to produce a vast quantity of research aimed at understanding, monitoring, and containing the disease; however, it remains unclear whether the research that has been produced to date sufficiently addresses existing knowledge gaps. We use artificial intelligence (AI)/machine learning techniques to analyze this massive amount of information at scale. We find key discrepancies between literature about COVID-19 and what we would expect based on research on other coronaviruses. These discrepancies—namely, the lack of basic microbiological research, which is often expensive and time-consuming—may negatively impact efforts to mitigate the pandemic and raise questions regarding the research community's ability to quickly respond to future crises. Continually measuring what is being produced, both now and in the future, is key to making better resource allocation and goal prioritization decisions as a society moving forward.

A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis (Preprint).. [DOI: 10.2196/preprints.23703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

BACKGROUND

Shortly after the emergence of COVID-19, researchers rapidly mobilized to study numerous aspects of the disease such as its evolution, clinical manifestations, effects, treatments, and vaccinations. This led to a rapid increase in the number of COVID-19–related publications. Identifying trends and areas of interest using traditional review methods (eg, scoping and systematic reviews) for such a large domain area is challenging.

OBJECTIVE

We aimed to conduct an extensive bibliometric analysis to provide a comprehensive overview of the COVID-19 literature.

METHODS

We used the COVID-19 Open Research Dataset (CORD-19) that consists of a large number of research articles related to all coronaviruses. We used a machine learning–based method to analyze the most relevant COVID-19–related articles and extracted the most prominent topics. Specifically, we used a clustering algorithm to group published articles based on the similarity of their abstracts to identify research hotspots and current research directions. We have made our software accessible to the community via GitHub.

RESULTS

Of the 196,630 publications retrieved from the database, we included 28,904 in our analysis. The mean number of weekly publications was 990 (SD 789.3). The country that published the highest number of COVID-19–related articles was China (2950/17,270, 17.08%). The highest number of articles were published in bioRxiv. Lei Liu affiliated with the Southern University of Science and Technology in China published the highest number of articles (n=46). Based on titles and abstracts alone, we were able to identify 1515 surveys, 733 systematic reviews, 512 cohort studies, 480 meta-analyses, and 362 randomized control trials. We identified 19 different topics covered among the publications reviewed. The most dominant topic was public health response, followed by clinical care practices during the COVID-19 pandemic, clinical characteristics and risk factors, and epidemic models for its spread.

CONCLUSIONS

We provide an overview of the COVID-19 literature and have identified current hotspots and research directions. Our findings can be useful for the research community to help prioritize research needs and recognize leading COVID-19 researchers, institutes, countries, and publishers. Our study shows that an AI-based bibliometric analysis has the potential to rapidly explore a large corpus of academic publications during a public health crisis. We believe that this work can be used to analyze other eHealth-related literature to help clinicians, administrators, and policy makers to obtain a holistic view of the literature and be able to categorize different topics of the existing research for further analyses. It can be further scaled (for instance, in time) to clinical summary documentation. Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.

Epidemiology of mental health problems in COVID-19: a review

The novel coronavirus disease 2019 (COVID-19) has become a pandemic affecting health and wellbeing globally. In addition to the physical health, economic, and social implications, the psychological impacts of this pandemic are increasingly being reported in the scientific literature. This narrative review reflected on scholarly articles on the epidemiology of mental health problems in COVID-19. The current literature suggests that people affected by COVID-19 may have a high burden of mental health problems, including depression, anxiety disorders, stress, panic attack, irrational anger, impulsivity, somatization disorder, sleep disorders, emotional disturbance, posttraumatic stress symptoms, and suicidal behavior. Moreover, several factors associated with mental health problems in COVID-19 are found, which include age, gender, marital status, education, occupation, income, place of living, close contact with people with COVID-19, comorbid physical and mental health problems, exposure to COVID-19 related news and social media, coping styles, stigma, psychosocial support, health communication, confidence in health services, personal protective measures, risk of contracting COVID-19, and perceived likelihood of survival. Furthermore, the epidemiological distribution of mental health problems and associated factors were heterogeneous among the general public, COVID-19 patients, and healthcare providers. The current evidence suggests that a psychiatric epidemic is cooccurring with the COVID-19 pandemic, which necessitates the attention of the global health community. Future epidemiological studies should emphasize on psychopathological variations and temporality of mental health problems in different populations. Nonetheless, multipronged interventions should be developed and adopted to address the existing psychosocial challenges and promote mental health amid the COVID-19 pandemic.