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

"Spine to the future"-A narrative review of anatomy engagement

Anatomy has been integral to medical and health education for centuries, it has also had a significant role in wider public life, as an educational resource, a link to their health, and also as a darker deterrent. Historically, public engagement in anatomy is hallmarked by public dissections of convicted criminals across the globe. Artists, specifically non-medical men, such as Leonardo da Vinci, are reported to have participated in public dissection. Dissection would later rekindle public interest in anatomy as graverobbing led to the reform and regulation of anatomy in many countries. In recent years, there has been growing interest from the public in learning more about their bodies as health and well-being become of paramount importance, particularly following the COVID-19 pandemic. Anatomy sits in a prime position to direct and instigate conversations around health, well-being, and body image. Every human on earth possesses a perfect resource to look at and learn about. Models, art-based anatomical activities, and crafts provide active learning opportunities for the wider public around anatomy. Most recently, apps, games, and extended reality provide novel and insightful learning opportunities for the public relating to the body. Finally, training and resources must also be made available from institutions and professional bodies to anatomists to enable them to deliver engagement in an already congested and educationally heavy schedule. This resurgence of interest in anatomical public engagement sees anatomy re-enter the public spotlight, with more appropriate resources and educational settings to offer engagement with the aim of benefiting the public.

Unmasking the Pandemic's Hidden Challenge

In the COVID-19 pandemic, a new challenge emerges in the digital realm – a surge in cyberbullying fuelled by social isolation. This chapter explores the intricate connection between isolation measures and the alarming rise in online harassment. Lockdowns and distancing have turned the online space into both a refuge and a battlefield, revealing unique consequences of isolation. The pandemic has reshaped cyberbullying, with increased screen time, online education, and heightened social media engagement playing complex roles. As social isolation heightens vulnerability, the line between physical and digital blurs, exposing individuals to online harassers. The chapter acknowledges the profound impact of social isolation on mental health, with pandemic stressors and online anonymity fostering anxiety among cyberbullying victims. Educational settings, grappling with remote learning challenges, also experience the ripple effects of cyberbullying. Despite these challenges, coping strategies and support mechanisms emerge, aiding individuals in navigating the digital landscape safely.

Co-Occurrence Analysis of COVID-19 Publications with an Emphasis on the Global Health Governance (GHG)

Background

Analyzing co-occurrence is an effective way to monitor the overview of topic spreading. The present study aimed to conduct a co-occurrence analysis of scientific publications related to COVID-19, emphasizing Global Health Governance (GHG).

Materials and Methods

This applied research with an analytical approach was carried out on all the scientific publications related to COVID-19, emphasizing GHG (51056 records), extracted from PubMed Central on 26/01/2022. The research population consisted of all the scientific publications related to COVID-19, emphasizing GHG (51056 records), extracted from PubMed Central on 26/01/2022. The data were analyzed using BibExcel, UCINET, Excel, and SPSS software, and Spearman's test was used to confirm correlations.

Results

The co-word network of the thematic area of COVID-19 includes 226 nodes and 7292 edges. COVID-19 and the pandemic formed the most co-word pairs with 2224 connections. The COVID-19* mental health and COVID-19* anxiety, with 1019 and 925 connections, are ranked next, respectively. The term COVID-19 is ranked first with a centrality index of 225. The keywords of pandemic and public health are ranked second and third with the centrality index of 217 and 206, respectively.

Conclusion

The global approach of studies related to COVID-19 is more inclined to the epidemiological and public health fields. Assuming the GHG, detailed and comprehensive planning should be performed to strengthen these studies and pave the way for international cooperation, determining research requisites, and developing applied research studies.

Translation in action: Influence, collaboration, and evolution of COVID-19 research with Clinical and Translational Science Awards consortium support

The National Institutes of Health (NIH)'s Clinical and Translational Science Awards (CTSA) consortium aims to accelerate translational processes that move discoveries from bench to bedside. The coronavirus disease 2019 (COVID-19) pandemic presented unmatched challenges and applications for CTSA hubs nationwide. Our study used bibliometrics to assess features of COVID-19 publications supported by the national CTSA program to characterize the consortium's response to the pandemic. Our goal was to understand relative scientific influence, collaboration across hubs, and trends in research emphasis over time. We identified publications from NIH's curated iSearch COVID-19 Publication Portfolio from February 2020 to February 2023; 3234 peer-reviewed articles relevant to COVID-19 cited a CTSA grant. All 66 CTSA hubs were represented, with large-size and longstanding hubs contributing more publications. Most publications cited UL1 grants, 457 cited KL2/TL1 training grants, and 164 cited multiple hub grants. Compared to a random sample of non-CTSA-supported COVID-19 publications, the CTSA portfolio exhibited greater clinical relevance, more human research, and higher altmetric and citation influence. Results were similar for multi-hub publications involving networked initiatives like multi-site clinical trials or the National COVID-19 Cohort Collaborative. Shifts from molecular/cellular-oriented research toward human-oriented research over time were evident, demonstrating translation in action. Results illuminate how the CTSA consortium confronted the pandemic through high-quality projects oriented toward human research, working across hubs on high-value collaborations, advancing along the translational spectrum over time. Findings validate CTSA hubs as critical support structures during health emergencies.

COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution

COVID-19 has been an unprecedented challenge that disruptively reshaped societies and brought a massive amount of novel knowledge to the scientific community. However, as this knowledge flood continues surging, researchers have been disadvantaged by not having access to a platform that can quickly synthesize emerging information and link the new knowledge to the latent knowledge foundation. Aiming to fill this gap, we propose a research framework and develop a dashboard that can assist scientists in identifying, retrieving, and understanding COVID-19 knowledge from the ocean of scholarly articles. Incorporating principal component decomposition (PCD), a knowledge mode-based search approach, and hierarchical topic tree (HTT) analysis, the proposed framework profiles the COVID-19 research landscape, retrieves topic-specific latent knowledge foundation, and visualizes knowledge structures. The regularly updated dashboard presents our research results. Addressing 127,971 COVID-19 research papers from PubMed, the PCD topic analysis identifies 35 research hotspots, along with their inner correlations and fluctuating trends. The HTT result segments the global knowledge landscape of COVID-19 into clinical and public health branches and reveals the deeper exploration of those studies. To supplement this analysis, we additionally built a knowledge model from research papers on the topic of vaccination and fetched 92,286 pre-Covid publications as the latent knowledge foundation for reference. The HTT analysis results on the retrieved papers show multiple relevant biomedical disciplines and four future research topics: monoclonal antibody treatments, vaccinations in diabetic patients, vaccine immunity effectiveness and durability, and vaccination-related allergic sensitization.

Novel Methods for Leveraging Large Cohort Studies for Qualitative and Mixed-Methods Research

Qualitative research methods, while rising in popularity, are still a relatively underutilized tool in public health research. Usually reserved for small samples, qualitative research techniques have the potential to enhance insights gained from large questionnaires and cohort studies, both deepening the interpretation of quantitative data and generating novel hypotheses that might otherwise be missed by standard approaches; this is especially true where exposures and outcomes are new, understudied, or rapidly changing, as in a pandemic. However, methods for the conduct of qualitative research within large samples are underdeveloped. Here, we describe a novel method of applying qualitative research methods to free-text comments collected in a large epidemiologic questionnaire. Specifically, this method includes: 1) a hierarchical system of coding through content analysis; 2) a qualitative data management application; and 3) an adaptation of Cohen's κ and percent agreement statistics for use by a team of coders, applying multiple codes per record from a large codebook. The methods outlined in this paper may help direct future applications of qualitative and mixed methods within large cohort studies.

Radiology During the COVID-19 Pandemic: Mapping Radiology Literature in 2020

OBJECTIVES

Our aim was to assess articles published in the field of radiology, nuclear medicine, and medical imaging in 2020 and analyze the linkage of radiology-related topics with coronavirus disease 2019 (COVID-19) through literature mapping along with a bibliometric analysis for publications.

METHODS

We performed a search on the Web of Science Core Collection database for articles in the field of radiology, nuclear medicine, and medical imaging published in 2020. We analyzed the included articles using VOS viewer software, where we analyzed the co-occurrence of keywords, representing major topics discussed. Of the resulting topics, a literature map was created and linkage analysis was done.

RESULTS

A total of 24,748 articles were published in the field of radiology, nuclear medicine, and medical imaging in 2020. We found a total of 61,267 keywords; only 78 keywords occurred more than 250 times. COVID-19 had 449 occurrences, 29 links, with a total link strength of 271. MRI was the topic most commonly appearing in 2020 radiology publications, while "computed tomography" had the highest linkage strength with COVID-19, with a linkage strength of 149, representing 54.98% of the total COVID-19 linkage strength, followed by "radiotherapy, and "deep and machine learning". The top cited paper had a total of 1,687 citations. Nine out of the 10 most cited articles discussed COVID-19 and included "COVID-19" or "coronavirus" in their title, including the top cited paper.

CONCLUSION

While MRI was the topic that dominated, CT had the highest linkage strength with COVID-19 and represented the topic of top cited articles in 2020 radiology publications.

COVID-19 and the scientific publishing system: growth, open access and scientific fields

We model the growth of scientific literature related to COVID-19 and forecast the expected growth from 1 June 2021. Considering the significant scientific and financial efforts made by the research community to find solutions to end the COVID-19 pandemic, an unprecedented volume of scientific outputs is being produced. This questions the capacity of scientists, politicians and citizens to maintain infrastructure, digest content and take scientifically informed decisions. A crucial aspect is to make predictions to prepare for such a large corpus of scientific literature. Here we base our predictions on the Autoregressive Integrated Moving Average (ARIMA) and exponential smoothing models using the Dimensions database. This source has the particularity of including in the metadata information on the date in which papers were indexed. We present global predictions, plus predictions in three specific settings: by type of access (Open Access), by domain-specific repository (SSRN and MedRxiv) and by several research fields. We conclude by discussing our findings.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11192-022-04536-x.

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

Objective

Many studies have suggested herbal medicines as alternatives or adjuvants to modern drugs for COVID-19. Their scientometric analyses can provide a scientific overview of this topic.

Materials and methods

Web of Science (WOS) and Scopus were searched for articles on the use of herbal medicines in COVID-19 published until 26 October 2020. Collected data were analyzed for document type, subject area, top journal, citation number, and authors’ collaboration network using VOSviewer 1.6.15, ScientoPy 2.0.3, Gephi 0.9.2, and SPSS 15 statistical tools.

Results

After screening the 3185 retrieved records, 378 and 849 records, respectively from WOS and Scopus, remained for quantity analysis. Original and review articles were the two main types of papers in both databases. Top subject areas were drug and medicine, respectively in the WOS and Scopus databases. The top three productive countries in the field were China, the US, and India. The most cited article was a practice guideline in both databases. “Journal of Biomolecular Structure Dynamics” in WOS and “Chinese Traditional and Herbal Drugs” in Scopus were the top journals. Top keywords included “COVID-19″ and “Traditional Chinese Medicine”. US authors had the highest collaboration with other authors.

Conclusions

The current study provides a snapshot of the quantity and characteristics of published scholarly documents in recent months in the intersection of herbal medicines and COVID-19. Our findings help scientists to find the existing gaps, identify the active authors and scientific institutes to collaborate with and use their experience to produce new knowledge in the future.

The influence of Covid-19 on publications in economics: bibliometric evidence from five working paper series

We compare Covid-related working papers in economics to non-Covid-related working papers in four dimensions. Based on five well-known working papers series and data from the RePEc website, we find that Covid papers mainly cover topics in macroeconomics and health, they are written by larger teams than non-Covid papers, are more often downloaded and they receive more citations relative to non-Covid papers.

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.

A visual review of artificial intelligence and Industry 4.0 in healthcare

The COVID-19 outbreak has led to a substantial loss of human life throughout the world and has a tremendous impact on healthcare services. Industry 4.0 technologies have established effective supply chain management towards the fulfillment of customized demands in the healthcare field. In addition, the internet of things, artificial intelligence, big data analytics, and 3D printing have been extensively used to combat the COVID-19 pandemic and assist in providing value-added services in the healthcare sector. Henceforth, this paper presents a scientometric analysis on the literature of aforementioned Industry 4.0 technologies in the context of COVID-19. It provides extensive insights into co-citation and co-occurrence analysis of high cited publications, participating countries, influential authors, prolific journals, and keywords using the CiteSpace tool. The analyses reveal that China has produced the highest research outputs, although India is the most collaborative country in this field. The current research hotspots include supply chain, 4D printing, and social distancing technologies. Furthermore, it explores emerging trends, intellectual structure of publications, research frontiers, and potential research directions for further work in the Industry 4.0 assisted healthcare domain.

Between panic and motivation: did the first wave of COVID-19 affect scientific publishing in Mediterranean countries?

Due to the ongoing COVID-19 pandemic that began in the winter of 2020, all communities and activities globally have been positively or negatively affected. This scientometric study raises an interesting question concerning whether the volume and characteristics of scientific publishing in all disciplines in 23 Mediterranean countries have been impacted by the pandemic and whether variations in the cumulative totals of COVID-19 cases have resulted in significant changes in this context. The Scopus database and SciVal tool supplied the necessary data for the years targeted for comparison (2019 and 2020), and the annual growth rates and differences were computed. The study used the Mann–Whitney test to examine the significance of the differences between the two years and the Spearman and Kendall correlation tests to evaluate the effect of the number of infections on these differences for all aspects of scientific performance. The findings demonstrated that the COVID-19 pandemic served as a powerful incentive, and the Mediterranean region experienced considerable differences in the volume and features of publications during this crisis. The most substantial implications were the significant growth from 3.1 to 9.4% in productivity and the increases in the annual growth rates of international collaboration, by 12% for the collaboration among Mediterranean countries and 10% for collaboration with the top ten epidemic countries. It was also proven that some characteristics of the publications were positively correlated with the total number of infections. This investigation can help university leaders and decision-makers in higher education and research institutions in these countries make decisions and implement measures to bridge the gaps and motivate researchers in all fields to conduct more research during this ongoing pandemic.

Distribution of COVID-19 government support and its consequences for firm liquidity and solvency

We utilize several unique firm-level datasets in order to assess the efficiency and effectiveness of the government support aiming to curb the economic consequences of the coronavirus pandemic. The results, drawing on the experience of a small open European country, suggest the distributed COVID-19 subsidies save non-negligible number of jobs and sustain economic activity during the first wave of the pandemic. General distribution rules designed on the fly may bring close to optimal results in terms of the support allocation, as relatively more productive, privately owned, foreign-demand oriented firms are prioritized and firms with a high environmental footprint or zombie firms record a relatively lower chance of obtaining government funding. By assuming constant cost elasticities to sales, we show that the pandemic deteriorates strongly firm profits and increases significantly the share of illiquid and insolvent firms. Government wage subsidies somewhat mitigate firm losses and have statistically significant effect, but relatively mild compared to the size of the economic shock. Our estimates also confirm that larger firms, receiving smaller relative size of the support, have more space to cover their additional liquidity needs by increasing trade liabilities or liabilities to affiliated entities, while SMEs face higher risk of insolvencies.

A multilayer network model of Covid-19: Implications in public health policy in Costa Rica

Successful partnerships between researchers, experts, and public health authorities have been critical to navigate the challenges of the Covid-19 pandemic worldwide. In this collaboration, mathematical models have played a decisive role in informing public policy, with findings effectively translated into public health measures that have shaped the pandemic in Costa Rica. As a result of interdisciplinary and cross-institutional collaboration, we constructed a multilayer network model that incorporates a diverse contact structure for each individual. In July 2020, we used this model to test the effect of lifting restrictions on population mobility after a so-called "epidemiological fence" imposed to contain the country's first big wave of cases. Later, in August 2020, we used it to predict the effects of an open and close strategy (the Hammer and Dance). Scenarios constructed in July 2020 showed that lifting restrictions on population mobility after less than three weeks of epidemiological fence would produce a sharp increase in cases. Results from scenarios in August 2020 indicated that the Hammer and Dance strategy would only work with 50% of the population adhering to mobility restrictions. The development, evolution, and applications of a multilayer network model of Covid-19 in Costa Rica has guided decision-makers to anticipate implementing sanitary measures and contributed to gain valuable time to increase hospital capacity.

Fluorescence signatures of SARS-CoV-2 spike S1 proteins and a human ACE-2: excitation-emission maps and fluorescence lifetimes

SIGNIFICANCE

Fast and reliable detection of infectious SARS-CoV-2 virus loads is an important issue. Fluorescence spectroscopy is a sensitive tool to do so in clean environments. This presumes a comprehensive knowledge of fluorescence data.

AIM

We aim at providing fully featured information on wavelength and time-dependent data of the fluorescence of the SARS-CoV-2 spike protein S1 subunit, its receptor-binding domain (RBD), and the human angiotensin-converting enzyme 2, especially with respect to possible optical detection schemes.

APPROACH

Spectrally resolved excitation-emission maps of the involved proteins and measurements of fluorescence lifetimes were recorded for excitations from 220 to 295 nm. The fluorescence decay times were extracted by using a biexponential kinetic approach. The binding process in the SARS-CoV-2 RBD was likewise examined for spectroscopic changes.

RESULTS

Distinct spectral features for each protein are pointed out in relevant spectra extracted from the excitation-emission maps. We also identify minor spectroscopic changes under the binding process. The decay times in the biexponential model are found to be   (  2.0  ±  0.1  )   ns and   (  8.6  ±  1.4  )    ns.

CONCLUSIONS

Specific material data serve as an important background information for the design of optical detection and testing methods for SARS-CoV-2 loaded media.

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.

A Literature Review of the COVID-19 Pandemic’s Effect on Sustainable HRM

The ramifications of the COVID-19 pandemic continue to emerge across all facets of the world of work, including the field of human resource management (HRM). Sustainable HRM, drawing on the triple bottom line elements of the economic, environmental and social pillars of sustainability, provides an ideal basis from which to understand the intersection of the COVID-19 pandemic and HRM. In this systematic literature review, we analyze peer reviewed articles published in the nexus of the pandemic and sustainable HRM, identifying the dimensions and extent of research in this topical area of study. Our CEDEL model—complicator–exposer–disruptor–enabler–legitimizer—conceptualizes our understanding of the role of COVID-19 in sustainable HRM. This paper provides a framework from which future studies can benefit when investigating the impacts of COVID-19, and a comprehensive identification of future research avenues.

The Impact of the COVID-19 Pandemic on the Practice of Forensic Medicine: An Overview

During the COVID-19 pandemic, forensic sciences, on the one hand, contributed to gaining knowledge about different aspects of the pandemic, while on the other hand, forensic professionals were called on to quickly adapt their activities to respond adequately to the changes imposed by the pandemic. This review aims to clarify the state of the art in forensic medicine at the time of COVID-19, discussing the following: the influence of external factors on forensic activities, the impact of autopsy practice on COVID-19 and vice-versa, the persistence of SARS-CoV-2 RNA in post-mortem samples, forensic personnel activities during the SARS-CoV-2 pandemic, the global vaccination program and forensic sciences, forensic undergraduate education during and after the imposed COVID-19 lockdown, and the medico-legal implications in medical malpractice claims during the COVID-19 pandemic. The COVID-19 pandemic has greatly influenced different aspects of human life, and, accordingly, the practical activities of forensic sciences that are defined as multidisciplinary, involving different expertise. Indeed, the activities are very different, including crime scene investigation (CSI), external examination, autopsy, and genetic and toxicological examinations of tissues and/or biological fluids. At the same time, forensic professionals may have direct contact with subjects in life, such as in the case of abuse victims (in some cases involving children), collecting biological samples from suspects, or visiting subjects in the case of physical examinations. In this scenario, forensic professionals are called on to implement methods to prevent the SARS-CoV-2 infection risk, wearing adequate PPE, and working in environments with a reduced risk of infection. Consequently, in the pandemic era, the costs involved for forensic sciences were substantially increased.

Discovering temporal scientometric knowledge in COVID-19 scholarly production

The mapping and analysis of scientific knowledge makes it possible to identify the dynamics and/or growth of a particular field of research or to support strategic decisions related to different research entities, based on bibliometric and/or scientometric indicators. However, with the exponential growth of scientific production, a systematic and data-oriented approach to the analysis of this large set of productions becomes increasingly essential. Thus, in this work, a data-oriented methodology was proposed, combining Data Analysis, Machine Learning and Complex Network Analysis techniques, and Data Version Control (DVC) tool, for the extraction of implicit knowledge in scientific production bases. In addition, the approach was validated through a case study in a COVID-19 manuscripts dataset, which had 199,895 articles published on arXiv, bioRxiv, medRxiv, PubMed and Scopus databases. The results suggest the feasibility of the proposed methodology, indicating the most active countries and the most explored themes in each period of the pandemic. Therefore, this study has the potential to instrument and expand strategic decisions by the scientific community, aiming at extracting knowledge that supports the fight against the COVID-19 pandemic.

Visibility, collaboration and impact of the Cuban scientific output on COVID-19 in Scopus

INTRODUCTION

COVID-19 is a disease with worldwide impact that has fully caught attention of researchers. The Cuban scientific output, after one year of confronting this pandemic, has not been studied from a bibliometric perspective.

OBJECTIVE

To characterize the output of original scientific articles and review articles on COVID-19 published by Cuban authors in the journals included in the Scopus bibliographic database, the collaborations in these publications and their impact, according to the citation of the research in the world literature.

MATERIALS AND METHODS

A cross-sectional, descriptive and observational study was performed, using a bibliometric approach. A search strategy was used to retrieve articles on the subject and bibliometric indicators of output, visibility, leadership, collaboration and impact were studied.

RESULTS

Cuba contributed 2.5% of the Latin American output and 0.2% of the world output. Of the national scientific output (133 articles, 111 original and 22 reviews), 84.2% were authored by a Cuban corresponding author (Cuban leadership). However, the majority (n = 20; 71.4%) of articles with international collaboration (n = 28; 21.1%) had foreign corresponding authors. Of the total, 33.8% (n = 45) corresponded to articles without collaboration. Only 13.5% of the articles (n = 18) were published in journals with high visibility (Q1). Of all the output, 68.4% (n = 91) was in Cuban journals. The output in English represented 29.3% (n = 39) and achieved greater impact than the articles in Spanish in terms of citations. As the visibility of the journals increased according to the quartiles where they are, the percentage of articles published in English and cited articles increased too, but Cuban scientific leadership decreased.

CONCLUSIONS

The greater the leadership in Cuban research, the lower its impact, and the lower the indexes of international collaboration. Cuban researchers are not yet able to systematically generate research that has a significant impact on the international scientific community.

Evolution and structure of research fields driven by crises and environmental threats: the COVID-19 research

Evolution of science and behavior of new research fields emerging under conditions of crisis are newtopics hardly known in social studies of science and scientometrics. In particular, the ecosystem and dynamics of research fields during crisis are vital aspects for explaining and planning the scientific development, and allocating resources efficaciously toward positive societal impact. This study here endeavors to analyze the evolution and structure of COVID-19 (Coronavirus Disease 2019) research, a new research field emerged and driven by a global pandemic crisis. The dynamics and structure of this research field are compared to related fields concerning respiratory disorders that are not guided by pandemic crisis, such as chronic obstructive pulmonary disease and lung cancer, to explain similarities and differences. Results suggest that a crisis-driven research field is characterized by an unparalleled velocity of scientific production equal to about 1.2% daily, based on notes and short papers mainly open access that support scientific advances and discoveries in research arena over a short period of time, such as the development of innovative drugs given by novel vaccines and new antiviral COVID-19 treatments. Findings are generalized in properties that clarify the evolution and structure of new research fields and their research behavior in a period of crisis for guiding decisions of policymakers to support scientific and technological progress in human society in the presence of environmental threats.

The private versus public contribution to the biomedical literature during the COVID-19, Ebola, H1N1, and Zika public health emergencies

Background

The private versus public contribution to developing new health knowledge and interventions is deeply contentious. Proponents of commercial innovation highlight its role in late-stage clinical trials, regulatory approval, and widespread distribution. Proponents of public innovation point out the role of public institutions in forming the foundational knowledge undergirding downstream innovation. The rapidly evolving COVID-19 situation has brought with it uniquely proactive public involvement to characterize, treat, and prevent this novel health treat. How has this affected the share of research by industry and public institutions, particularly compared to the experience of previous pandemics, Ebola, H1N1 and Zika?

Methods

Using Embase, we categorized all publications for COVID-19, Ebola, H1N1 and Zika as having any author identified as affiliated with industry or not. We placed all disease areas on a common timeline of the number of days since the WHO had declared a Public Health Emergency of International Concern with a six-month lookback window. We plotted the number and proportion of publications over time using a smoothing function and plotted a rolling 30-day cumulative sum to illustrate the variability in publication outputs over time.

Results

Industry-affiliated articles represented 2% (1,773 articles) of publications over the 14 months observed for COVID-19, 7% (278 articles) over 7.1 years observed for Ebola, 5% (350 articles) over 12.4 years observed for H1N1, and 3% (160 articles) over the 5.7 years observed for Zika. The proportion of industry-affiliated publications built steadily over the time observed, eventually plateauing around 7.5% for Ebola, 5.5% for H1H1, and 3.5% for Zika. In contrast, COVID-19’s proportion oscillated from 1.4% to above 2.7% and then declined again to 1.7%. At this point in the pandemic (i.e., 14 months since the PHEIC), the proportion of industry-affiliated articles had been higher for the other three disease areas; for example, the proportion for H1N1 was twice as high.

Conclusions

While the industry-affiliated contribution to the biomedical literature for COVID is extraordinary in its absolute number, its proportional share is unprecedentedly low currently. Nevertheless, the world has witnessed one of the most remarkable mobilizations of the biomedical innovation ecosystem in history.

How Has Covid-19 Affected Published Academic Research? A Content Analysis of Journal Articles Mentioning the Virus

Purpose

Methods to tackle Covid-19 have been developed by a wave of biomedical research but the pandemic has also influenced many aspects of society, generating a need for research into its consequences, and potentially changing the way existing topics are investigated. This article investigates the nature of this influence on the wider academic research mission.

Design/methodology/approach

This article reports an inductive content analysis of 500 randomly selected journal articles mentioning Covid-19, as recorded by the Dimensions scholarly database on 19 March 2021. Covid-19 mentions were coded for the influence of the disease on the research.

Findings

Whilst two thirds of these articles were about biomedicine (e.g. treatments, vaccines, virology), or health services in response to Covid-19, others covered the pandemic economy, society, safety, or education. In addition, some articles were not about the pandemic but stated that Covid-19 had increased or decreased the value of the reported research or changed the context in which it was conducted.

Research limitations

The findings relate only to Covid-19 influences declared in published journal articles.

Practical implications

Research managers and funders should consider whether their current procedures are effective in supporting researchers to address the evolving demands of pandemic societies, particularly in terms of timeliness.

Originality/value

The results show that although health research dominates the academic response to Covid-19, it is more widely disrupting academic research with new demands and challenges.

Bibliometric Analysis of SARS, MERS, and COVID-19 Studies from India and Connection to Sustainable Development Goals

India is ranked fifth in the world in terms of COVID-19 publications accounting for 6.7% of the total. About 60% of the COVID-19 publications in the year 2020 are from United States, China, UK, Italy, and India. We present a bibliometric analysis of the publication trends and citation structure along with the identification of major research clusters. By performing network analysis of authors, citations, institutions, keywords, and countries, we explore semantic associations by applying visualization techniques. Our study shows lead taken by the United States, China, UK, Italy, India in COVID-19 research may be attributed to the high prevalence of COVID-19 cases in those countries witnessing the first outbreak and also due to having access to COVID-19 data, access to labs for experimental trials, immediate funding, and overall support from the govt. agencies. A large number of publications and citations from India are due to co-authored publications with countries like the United States, UK, China, and Saudi Arabia. Findings show health sciences have the highest number of publications and citations, while physical sciences and social sciences and humanities counts were low. A large proportion of publications fall into the open-access category. With India as the focus, by comparing three major pandemics—SARS, MERS, COVID-19—from a bibliometrics perspective, we observe much broader involvement of authors from multiple countries for COVID-19 studies when compared to SARS and MERS. Finally, by applying bibliometric indicators, we see an increasing number of sustainable development-related studies from the COVID-19 domain, particularly concerning the topic of good health and well-being. This study allows for a deeper understanding of how the scholarly community from a populous country like India pursued research in the midst of a major pandemic which resulted in the closure of scientific institutions for an extended time.

Mapping the intellectual structure of the coronavirus field (2000-2020): a co-word analysis

Over the two last decades, coronaviruses have affected human life in different ways, especially in terms of health and economy. Due to the profound effects of novel coronaviruses, growing tides of research are emerging in various research fields. This paper employs a co-word analysis approach to map the intellectual structure of the coronavirus literature for a better understanding of how coronavirus research and the disease itself have developed during the target timeframe. A strategic diagram has been drawn to depict the coronavirus domain's structure and development. A detailed picture of coronavirus literature has been extracted from a huge number of papers to provide a quick overview of the coronavirus literature. The main themes of past coronavirus-related publications are (a) "Antibody-Virus Interactions," (b) "Emerging Infectious Diseases," (c) "Protein Structure-based Drug Design and Antiviral Drug Discovery," (d) "Coronavirus Detection Methods," (e) "Viral Pathogenesis and Immunity," and (f) "Animal Coronaviruses." The emerging infectious diseases are mostly related to fatal diseases (such as Middle East respiratory syndrome, severe acute respiratory syndrome, and COVID-19) and animal coronaviruses (including porcine, turkey, feline, canine, equine, and bovine coronaviruses and infectious bronchitis virus), which are capable of placing animal-dependent industries such as the swine and poultry industries under strong economic pressure. Although considerable research into coronavirus has been done, this unique field has not yet matured sufficiently. Therefore, "Antibody-virus Interactions," "Emerging Infectious Diseases," and "Coronavirus Detection Methods" hold interesting, promising research gaps to be both explored and filled in the future.

Research on Covid-19: a disruptive phenomenon for bibliometrics

The Covid-19 pandemic has been the highest disruptive event in the world recent history. Worldwide academic research on this topic has led to an explosion of scientific literature, never seen before. Bibliometrics provide methods to illustrate this exceptional phenomenon in academic publications. The objective of this paper is to analyze the Covid-19 research from a bibliometric perspective and to study the impact of the publication explosion on bibliometric indicators. The present study shows how an exceptional phenomenon has a disruptive impact on bibliometric indicators, such as the h-index and the Journal Impact Factor. The higher the specialization, the higher the possible impact of a disruptive phenomenon. In applied sciences, more important than the research or the discipline, the specific theme of the research is crucial for citations of articles and for their impact. The salience of the topic, the magnitude of the problem at study and the urgency to find solutions are drivers for citations. The study of the Covid-19 research illustrates the relativity of indicators and the need for context. The present study also confirms the plead for responsible metrics of the San Francisco Declaration on Research Assessment (DORA).

Outbreaks of publications about emerging infectious diseases: the case of SARS-CoV-2 and Zika virus

BACKGROUND

Outbreaks of infectious diseases generate outbreaks of scientific evidence. In 2016 epidemics of Zika virus emerged, and in 2020, a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of coronavirus disease 2019 (COVID-19). We compared patterns of scientific publications for the two infections to analyse the evolution of the evidence.

METHODS

We annotated publications on Zika virus and SARS-CoV-2 that we collected using living evidence databases according to study design. We used descriptive statistics to categorise and compare study designs over time.

RESULTS

We found 2286 publications about Zika virus in 2016 and 21,990 about SARS-CoV-2 up to 24 May 2020, of which we analysed a random sample of 5294 (24%). For both infections, there were more epidemiological than laboratory science studies. Amongst epidemiological studies for both infections, case reports, case series and cross-sectional studies emerged first, cohort and case-control studies were published later. Trials were the last to emerge. The number of preprints was much higher for SARS-CoV-2 than for Zika virus.

CONCLUSIONS

Similarities in the overall pattern of publications might be generalizable, whereas differences are compatible with differences in the characteristics of a disease. Understanding how evidence accumulates during disease outbreaks helps us understand which types of public health questions we can answer and when.

Visualizing the knowledge outburst in global research on COVID-19

The scholarly output of the new coronavirus research has been proliferating. During five months, an amount of 14,588 scientific publications about nCoV-2 and COVID-19 has been generated intensively (as indexed in Scopus on 31 May 2020). Such a knowledge outburst has created ample interest in understanding the research landscape of this newly configured area. This paper demonstrates on scientometric dimensions of the novel coronavirus (2019-nCov) research using quantifiable characteristics of the publication dataset. Findings reveal that the rate of publication growth (1600%) is very significant to a synergic response of the researchers to combat with the most extended sequence of an RNA virus. Indeed their response has geared up to an average of 100 articles per day. Many scholarly publishers have disclosed their preprint servers to make the publications available immediately, even by enabling Open Access. The scientific contents have published in more than 500 journals from 240 academic publishers. While the top-ten publishers occupied almost 70% of the articles, then about 25% of the studies were sponsored by 300 funding agencies. Among the notable journals Lancet, Nature, BMJ, JAMA, JMV, and NEJM are prominent. Findings also reveal that majority of the contributions have occurred in Medical Science, focusing on virology, immunology, epidemiology, pharmacology, public health, critical care, and emergency medicine. However, the closely associated terms are virus transmission, infection control, asymptomatic, quarantine, pneumonia, human, disease severity, clinical trials, viral pathogenesis, pandemic, risk, and mortality. The study suggests that academic hubs are located mostly in the USA, China, Italy, and the UK. Among the productive institutions; Huazhong Univ (China), Tongji Med. College (China), Harvard Med. School (USA), Univ of Milan (Italy), INSERM (France), UCL (UK) are outstanding. The G7 countries together produced 50% of the global research output on nCov-2. It also noted an encouraging trend of collaborative research across many countries and disciplines, where the values of CI (6.46), DC (0.79), and CC (0.59) are very significant. It examines the geographical diversity of the collaborating authors, thereby visualized their linkages via co-authorship occurrences. Finally, it analyzed the publications' impact to showcase the most influential contributions of the new coronavirus research.

Iranian researchers' contributions to research on COVID-19: A bibliometric analysis and visualization

Background: COVID-19 pandemic crisis motivated researchers worldwide to deeply investigate it from different perspectives. As Iran is one of the highly-affected countries by Covid-19, Iranian researchers have focused on studying it. This study aimed at analyzing and visualizing Iranian researchers' papers on COVID-19 from a bibliometric perspective. Methods: By searching MeSH-selected keywords related to COVID-19 in Scopus, Iranian researchers' papers on COVID-19 were extracted in a CSV format and underwent bibliometric techniques, such as coauthorship analysis, citation, and co-citation analysis, keyword and term co-occurrence mapping and etc. in the Microsoft Excel and VOSviewer software package. Results: A total of 405 papers were authored by Iranian researchers on COVID-19 during the study period, with the average number of citations per paper of 2.60 and a mean h-index of 15. The majority of papers were original articles in English. Archives of Clinical Infectious Diseases and Archives of Iranian Medicine and Medical Hypotheses were highly ranked publishing journals, respectively. The most productive institute and author were Tehran University of Medical Sciences with 119 papers and Rezaei, N. with 12 papers. Iranian researchers collaborated with the researchers of 73 countries, with the USA ranking first in Covid-19 research, followed by Italy, Canada, and United Kingdom. In publishing papers on COVID-19, Iran ranked first among the Middle Eastern countries and thirteenth internationally. Conclusion: Iranian researchers were active in 5 main areas of COVID-19 research, including epidemiology, diagnosis, treatment, virology, and systematic review.

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.

Temporal evolution, most influential studies and sleeping beauties of the coronavirus literature

Following the outbreak of SARS-CoV-2 disease, within less than 8 months, the 50 years-old scholarly literature of coronaviruses grew to nearly three times larger than its size prior to 2020. Here, temporal evolution of the coronavirus literature over the last 30 years (N = 43,769) is analysed along with its subdomain of SARS-CoV-2 articles (N = 27,460) and the subdomain of reviews and meta-analytic studies (N = 1027). The analyses are conducted through the lenses of co-citation and bibliographic coupling of documents. (1) Of the N = 1204 review and meta-analytical articles of the coronavirus literature, nearly 88% have been published and indexed during the first 8 months of 2020, marking an unprecedented attention to reviews and meta-analyses in this domain, prompted by the SARS-CoV-2 pandemic. (2) The subset of 2020 SARS-CoV-2 articles is bibliographically distant from the rest of this literature published prior to 2020. Individual articles of the SARS-CoV-2 segment with a bridging role between the two bodies of articles (i.e., before and after 2020) are identifiable. (3) Furthermore, the degree of bibliographic coupling within the 2020 SARS-CoV-2 cluster is much poorer compared to the cluster of articles published prior to 2020. This could, in part, be explained by the higher diversity of topics that are studied in relation to SARS-CoV-2 compared to the literature of coronaviruses published prior to the SARS-CoV-2 disease. (4) The analyses on the subset of SARS-CoV-2 literature identified studies published prior to 2020 that have now proven highly instrumental in the development of various clusters of publications linked to SARS-CoV-2. In particular, the so-called "sleeping beauties" of the coronavirus literature with an awakening in 2020 were identified, i.e., previously published studies of this literature that had remained relatively unnoticed for several years but gained sudden traction in 2020 in the wake of the SARS-CoV-2 outbreak. This work documents the historical development of the literature on coronaviruses as an event-driven literature and as a domain that exhibited, arguably, the most exceptional case of publication burst in the history of science. It also demonstrates how scholarly efforts undertaken during peace time or prior to a disease outbreak could suddenly play a critical role in prevention and mitigation of health disasters caused by new diseases.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11192-021-04036-4.

Health-care guidelines and policies during the COVID-19 pandemic in Mexico: A case of health-inequalities

Background

Heterogeneous government responses have been reported in reaction to COVID-19. The aim of this study is to generate an exploratory review of healthcare policies published during COVID-19 by health-care institutions in Mexico. Analyzing policies within different health sub-systems becomes imperative in the Mexican case due to the longstanding fragmentation of the health-care system and health inequalities.

Data and Methods

Policies purposely included in the analysis were published by four public health institutions (IMSS, ISSSTE, SSA and PEMEX) during the COVID-19 epidemic in Mexico (from February 29th to June 15th, 2020) on official institutional websites. Researchers reviewed each document and classified them into seven policy categories set by the Rapid Research Evaluation and Appraisal Lab (RREAL): public health response, health-care delivery, human resources, health-system infrastructure and supplies, clinical response, health-care management, and epidemiological surveillance.

Results

Policy types varied by health institution. The largest number of policies were aimed at public health responses followed by health-care delivery and human resources. Policies were mainly published during the community transmission phase.

Conclusions

The pandemic exposed underlying health-care system inequalities and a reactive rather than prepared response to the outbreak. Additionally, this study outlines potential policy gaps and delays in the response that could be avoided in the future.

Tracking and Mining the COVID-19 Research Literature

The unprecedented, explosive growth of the COVID-19 domain presents challenges to researchers to keep up with research knowledge within the domain. This article profiles this research to help make that knowledge more accessible via overviews and novel categorizations. We provide websites offering means for researchers to probe more deeply to address specific questions. We further probe and reassemble COVID-19 topical content to address research issues concerning topical evolution and emphases on tactical vs. strategic approaches to mitigate this pandemic and reduce future viral threats. Data suggest that heightened attention to strategic, immunological factors is warranted. Connecting with and transferring in research knowledge from outside the COVID-19 domain demand a viable COVID-19 knowledge model. This study provides complementary topical categorizations to facilitate such modeling to inform future Literature-Based Discovery endeavors.

Trends in Family Violence Are Not Causally Associated with COVID-19 Stay-at-Home Orders: a Commentary on Piquero et al

COVID-19 has caused a wave of research publications in academic and pre-print outlets which have resulted in several high-profile retractions. While the breadth of emerging research has been instrumental in understanding and curbing the global pandemic in near real-time, unfortunately manuscripts with major methodological challenges have fallen through the cracks. In this perspective, we illustrate this issue in light of a recent manuscript by Piquero et al. (2020). In the study, a statistically significant association between stay-at-home orders and family violence was not detected; however, the authors widely disseminated a "12.5% increase in family violence" offenses to a variety of media outlets. This negligent dissemination of inaccurate research findings has important implications for policy and the virus mitigation efforts, which might urge policymakers to terminate stay-at-home orders in an effort to reduce family violence and other social risk factors. Changes may ultimately result in more COVID-related deaths as stay-at-home orders are prematurely and inappropriately lifted to prevent purported injuries in the home. Therefore, the widespread propagation of these claims in the absence of scientific evidence of an increase has great potential to cause harm.