Analysis of acute COVID-19 including chronic morbidity: protocol for the deep phenotyping National Pandemic Cohort Network in Germany (NAPKON-HAP)

BACKGROUND

The severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) pandemic causes a high burden of acute and long-term morbidity and mortality worldwide despite global efforts in containment, prophylaxis, and therapy. With unprecedented speed, the global scientific community has generated pivotal insights into the pathogen and the host response evoked by the infection. However, deeper characterization of the pathophysiology and pathology remains a high priority to reduce morbidity and mortality of coronavirus disease 2019 (COVID-19).

METHODS

NAPKON-HAP is a multi-centered prospective observational study with a long-term follow-up phase of up to 36 months post-SARS-CoV-2 infection. It constitutes a central platform for harmonized data and biospecimen for interdisciplinary characterization of acute SARS-CoV-2 infection and long-term outcomes of diverging disease severities of hospitalized patients.

RESULTS

Primary outcome measures include clinical scores and quality of life assessment captured during hospitalization and at outpatient follow-up visits to assess acute and chronic morbidity. Secondary measures include results of biomolecular and immunological investigations and assessment of organ-specific involvement during and post-COVID-19 infection. NAPKON-HAP constitutes a national platform to provide accessibility and usability of the comprehensive data and biospecimen collection to global research.

CONCLUSION

NAPKON-HAP establishes a platform with standardized high-resolution data and biospecimen collection of hospitalized COVID-19 patients of different disease severities in Germany. With this study, we will add significant scientific insights and provide high-quality data to aid researchers to investigate COVID-19 pathophysiology, pathology, and chronic morbidity.

Making science public: a review of journalists' use of Open Access research

Science journalists are uniquely positioned to increase the societal impact of open research outputs by contextualizing and communicating findings in ways that highlight their relevance and implications for non-specialist audiences. Yet, it is unclear to what degree journalists use open research outputs, such as open access publications or preprints, in their reporting; what factors motivate or constrain this use; and how the recent surge in openly available research seen during the COVID-19 pandemic has affected this. This article examines these questions through a review of relevant literature published from 2018 onwards-particularly literature relating to the COVID-19 pandemic-as well as seminal articles outside the search dates. We find that research that explicitly examines journalists' engagement with open access publications or preprints is scarce, with existing literature mostly addressing the topic tangentially or as a secondary concern, rather than a primary focus. Still, the limited body of evidence points to several factors that may hamper journalists' use of these outputs and thus warrant further exploration. These include an overreliance on traditional criteria for evaluating scientific quality; concerns about the trustworthiness of open research outputs; and challenges using and verifying the findings. We also find that, while the COVID-19 pandemic encouraged journalists to explore open research outputs such as preprints, the extent to which these explorations will become established journalistic practices remains unclear. Furthermore, we note that current research is overwhelmingly authored and focused on the Global North, and the United States specifically. We conclude with recommendations for future research that attend to issues of equity and diversity, and more explicitly examine the intersections of open access and science journalism.

Investigating the Psychological, Social, Cultural, and Religious Predictors of COVID-19 Vaccine Uptake Intention in Digital Age: A Media Dependency Theory Perspective

Media exposure to health communication contents related to the COVID-19 pandemic alone is inadequate to measure the influence of media on individuals in adopting precautionary behaviors against COVID-19, such as vaccine uptake. Certain individuals may pay attention to and be influenced by communication content. However, literature has suggested other instrumental determinants in developing and adopting health precautionary measures, such as culture or religion, especially regarding vaccination. In times of crisis, such as the COVID-19 pandemic, it is valuable to examine the interrelationships among psychological, sociocultural, and informational factors. This can provide valuable insights for policymakers in developing effective communication strategies. Drawing an analogy between the Media dependency theory (MDT) and the Theory of Planned Behavior (TPB) model, this study unravels the factors underpinning the COVID-19 vaccine uptake intention among Pakistanis. The study utilized a cross-sectional research design and employed a survey method to gather data from a sample of 993 participants. The findings obtained from the PLS-SEM analysis confirmed that individuals relied on both traditional and social media to cope with the COVID-19 pandemic. The findings show that individuals rely more on the informational content disseminated through conventional media channels. The findings also suggest that individuals from Asian countries, such as Pakistan, tend to be more inclined toward collectivism. The findings about the moderating role of religiosity suggest that religious beliefs significantly shape individuals' reliance on traditional media. Hence, this study has uniquely contributed to public health and media management by providing a strategy for managers to address disseminating misinformation related to religion and its impact on vaccination-related health issues. The study has theoretically confirmed the principles of media dependency theory. As a result, it is recommended that various information sources be utilized to cultivate resilience among individuals to manage health crises effectively.

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.

Citation advantage of COVID-19-related publications

With the global spread of the COVID-19 pandemic, scientists from various disciplines responded quickly to this historical public health emergency. The sudden boom of COVID-19-related papers in a short period of time may bring unexpected influence to some commonly used bibliometric indicators. By a large-scale investigation using Science Citation Index Expanded and Social Sciences Citation Index, this brief communication confirms the citation advantage of COVID-19-related papers empirically through the lens of Essential Science Indicators’ highly cited paper. More than 8% of COVID-19-related papers published during 2020 and 2021 were selected as Essential Science Indicators highly cited papers, which was much higher than the set global benchmark value of 1%. The citation advantage of COVID-19-related papers for different Web of Science categories/countries/journal impact factor quartiles was also demonstrated. The distortions of COVID-19-related papers’ citation advantage to some bibliometric indicators such as journal impact factor were discussed at the end of this brief communication.

The development of phishing during the COVID-19 pandemic: An analysis of over 1100 targeted domains

To design preventive policy measures for email phishing, it is helpful to be aware of the phishing schemes and trends that are currently applied. How phishing schemes and patterns emerge and adapt is an ongoing field of study. Existing phishing works already reveal a rich set of phishing schemes, patterns, and trends that provide insight into the mechanisms used. However, there seems to be limited knowledge about how email phishing is affected in periods of social disturbance, such as COVID-19 in which phishing numbers have quadrupled. Therefore, we investigate how the COVID-19 pandemic influences the phishing emails sent during the first year of the pandemic. The email content (header data and html body, excl. attachments) is evaluated to assess how the pandemic influences the topics of phishing emails over time (peaks and trends), whether email campaigns correlate with momentous events and trends of the COVID-19 pandemic, and what hidden content revealed. This is studied through an in-depth analysis of the body of 500.000 phishing emails addressed to Dutch registered top-level domains collected during the start of the pandemic. The study reveals that most COVID-19 related phishing emails follow known patterns indicating that perpetrators are more likely to adapt than to reinvent their schemes.

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.

Egyptian physicians' information-seeking behavior while serving in public isolation hospitals for coronavirus patients

Purpose

The purpose of this study is to explore the information-seeking behavior of Egyptian physicians serving in COVID-19 isolation hospitals.

Design/methodology/approach

A sample of 91 physicians serving in Egyptian isolation hospitals answered the study questionnaire.

Findings

Demographically, more than half of respondents were males. Over one-third of them are holding Doctor of Medicine (M.D), followed by one-third holding Master of Medicine (MMed). Respondents' age ranged from 30 to 60 years. Internal medicine is the most common specialty, accounting for nearly half of all physicians, followed by chest medicine and intensive care medicine. The information-seeking behavior of these three groups in their regular work is believed to be different, but since all of the participants are working in COVID-19 isolation hospitals, they should have the same information resources, Internet access and the same needs relevant to COVID-19 in order to make accurate clinical decisions. The physicians used traditional and electronic information sources to fulfill their information needs, the most important of which were to make a specific research, find an answer to a specific case, and deliver a medical lecture. Colleagues, coworkers, nurses and pharmacists were the most important channels pursued by Egyptian physicians to obtain information.

Originality/value

This study is the first study that focuses on investigating the information-seeking behavior of Egyptian physicians serving in isolation hospitals. Any findings resulted from this study may serve as a noteworthy reference that may be useful to the Egyptian health sector, experts, researchers, as well as policymakers in establishing strategic decisions for making the understating much better.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2020-0350

Reporting preprints in the media during the COVID-19 pandemic

Preprints have gained prominence in the dissemination of scientific findings. This development has been reinforced by the COVID-19 pandemic, which continues to require the rapid dissemination of new scientific information. However, since preprints usually have not undergone peer review, they lack the rigour of other scientific publications such as journal articles. This presents a challenge for the news media tasked with keeping the public informed about the latest scientific developments in the context of great uncertainty during a global pandemic. This research note investigates the reporting of scientific information from preprints in 80 news articles identified in news articles related to COVID-19 published in four South African online media outlets. Our results show that despite the publication of guidelines for reporting on preprints in the media, there is still a way to go regarding the judicious use of scientific information from preprints by the news media.

The high scholarly value of grey literature before and during Covid-19

New academic knowledge in journal articles is partly built on peer reviewed research already published in journals or books. Academics can also draw from non-academic sources, such as the websites of organisations that publish credible information. This article investigates trends in the academic citing of this type of grey literature for 17 health, media, statistics, and large international organisations, with a focus on Covid-19. The results show substantial and steadily increasing numbers of citations to all 17 sites, with larger increases from 2019 to 2020. In 2020, Covid-19 citations to these websites were particularly common for news organisations, the WHO, and the UK Office for National Statistics, apparently for up-to-date information in the rapidly changing circumstances of the pandemic. Except for the UN, the most cited URLs of each organisation were not traditional report-like grey literature but were other types, such as news stories, data, statistics, and general guidance. The Covid-19 citations to most of these websites originated primarily from medical research, commonly for coronavirus data and statistics. Other fields extensively cited some of the non-health websites, as illustrated by social science (including psychology) studies often citing UNESCO. The results confirm that grey literature from major websites has become even more important within academia during the pandemic, providing up-to-date information from credible sources despite a lack of academic peer review. Researchers, reviewers, and editors should accept that it is reasonable to cite this information, when relevant, and evaluators should value academic work that supports these non-academic outputs.

Search where you will find most: Comparing the disciplinary coverage of 56 bibliographic databases

This paper introduces a novel scientometrics method and applies it to estimate the subject coverages of many of the popular English-focused bibliographic databases in academia. The method uses query results as a common denominator to compare a wide variety of search engines, repositories, digital libraries, and other bibliographic databases. The method extends existing sampling-based approaches that analyze smaller sets of database coverages. The findings show the relative and absolute subject coverages of 56 databases—information that has often not been available before. Knowing the databases’ absolute subject coverage allows the selection of the most comprehensive databases for searches requiring high recall/sensitivity, particularly relevant in lookup or exploratory searches. Knowing the databases’ relative subject coverage allows the selection of specialized databases for searches requiring high precision/specificity, particularly relevant in systematic searches. The findings illustrate not only differences in the disciplinary coverage of Google Scholar, Scopus, or Web of Science, but also of less frequently analyzed databases. For example, researchers might be surprised how Meta (discontinued), Embase, or Europe PMC are found to cover more records than PubMed in Medicine and other health subjects. These findings should encourage researchers to re-evaluate their go-to databases, also against newly introduced options. Searching with more comprehensive databases can improve finding, particularly when selecting the most fitting databases needs particular thought, such as in systematic reviews and meta-analyses. This comparison can also help librarians and other information experts re-evaluate expensive database procurement strategies. Researchers without institutional access learn which open databases are likely most comprehensive in their disciplines.

Are automated accounts driving scholarly communication on Twitter? a case study of dissemination of COVID-19 publications

From a network perspective, this study analyzes 659 users mentioning sampled COVID-19 articles 10 or more times on Twitter with a focus on their roles in facilitating the process of scholarly communication. Different from existing studies, we consider both the user types and the automation of accounts to profile influential users in the network of research dissemination. Our study found that similar to academic users, non-academic users can also be active players in communicating scientific publications. The results highlight the intensive interactions between human users and automated accounts, including bots and cyborgs, which accounted for 45% of connections among the top users. This study also demonstrates the important role of automated accounts in initiating and facilitating research dissemination. Specifically, (1) bot-assisted academic publishers showed the highest amplifier scores, which measures a user’s tendency of being the first to share information and reach out to others within their trusted networks, (2) 5.28% of the selected articles was first tweeted by automated research feeds, ranking the fourth among the 22 classified user groups, and (3) bot-assisted publishers and automated feeds of generic topics and news alerts were highly ranked in authority, a network measure to quantify the degree to which a user consumes important resources of relevant topics. In the conclusion section, we discuss future directions to improve the validity of Twitter metrics in assessing research impacts.

Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages

Abstractive summarization is a technique that allows for extracting condensed meanings from long texts, with a variety of potential practical applications. Nonetheless, today’s abstractive summarization research is limited to testing the models on various types of data, which brings only marginal improvements and does not lead to massive practical employment of the method. In particular, abstractive summarization is not used for social media research, where it would be very useful for opinion and topic mining due to the complications that social media data create for other methods of textual analysis. Of all social media, Reddit is most frequently used for testing new neural models of text summarization on large-scale datasets in English, without further testing on real-world smaller-size data in various languages or from various other platforms. Moreover, for social media, summarizing pools of texts (one-author posts, comment threads, discussion cascades, etc.) may bring crucial results relevant for social studies, which have not yet been tested. However, the existing methods of abstractive summarization are not fine-tuned for social media data and have next-to-never been applied to data from platforms beyond Reddit, nor for comments or non-English user texts. We address these research gaps by fine-tuning the newest Transformer-based neural network models LongFormer and T5 and testing them against BART, and on real-world data from Reddit, with improvements of up to 2%. Then, we apply the best model (fine-tuned T5) to pools of comments from Reddit and assess the similarity of post and comment summarizations. Further, to overcome the 500-token limitation of T5 for analyzing social media pools that are usually bigger, we apply LongFormer Large and T5 Large to pools of tweets from a large-scale discussion on the Charlie Hebdo massacre in three languages and prove that pool summarizations may be used for detecting micro-shifts in agendas of networked discussions. Our results show, however, that additional learning is definitely needed for German and French, as the results for these languages are non-satisfactory, and more fine-tuning is needed even in English for Twitter data. Thus, we show that a ‘one-for-all’ neural-network summarization model is still impossible to reach, while fine-tuning for platform affordances works well. We also show that fine-tuned T5 works best for small-scale social media data, but LongFormer is helpful for larger-scale pool summarizations.

Impact of Covid-19 on research output by gender across countries

The massive shock of the COVID-19 pandemic has already shown its negative effects on economies around the world, unprecedented in recent history. COVID-19 infections and containment measures caused a general slowdown in research and new knowledge production. Because of the link between R&D output and economic growth, it is to be expected then that a slowdown in research activities will slow in turn the global recovery from the pandemic. Many recent studies also claim an uneven impact on scientific production across gender. In this paper, we investigate the phenomenon across countries, analysing preprint depositions in main repositories. Differently from other works, that compare the number of preprint depositions before and after the pandemic outbreak, we analyse the depositions trends across geographical areas, and contrast after-pandemic outbreak depositions with expected ones. Differently from common belief and initial evidence, the decrease in research output is not more severe for women than for men.

BIP4COVID19: Releasing impact measures for articles relevant to COVID-19

Since the beginning of the coronavirus pandemic, a large number of relevant articles have been published or become available in preprint servers. These articles, along with earlier related literature, compose a valuable knowledge base affecting contemporary research studies or even government actions to limit the spread of the disease, and directing treatment decisions taken by physicians. However, the number of such articles is increasing at an intense rate, making the exploration of the relevant literature and the identification of useful knowledge challenging. In this work, we describe BIP4COVID19, an open data set that offers a variety of impact measures for coronavirus-related scientific articles. These measures can be exploited for the creation or extension of added-value services aiming to facilitate the exploration of the respective literature, alleviating the aforementioned issue. In the same context, as a use case, we provide a publicly accessible keyword-based search interface for COVID-19-related articles, which leverages our data to rank search results according to the calculated impact indicators.

Covid-19 refereeing duration and impact in major medical journals

Two partly conflicting academic pressures from the seriousness of the Covid-19 pandemic are the need for faster peer review of Covid-19 health-related research and greater scrutiny of its findings. This paper investigates whether decreases in peer review durations for Covid-19 articles were universal across 97 major medical journals, Nature, Science, and Cell. The results suggest that on average, Covid-19 articles submitted during 2020 were reviewed 1.7–2.1 times faster than non-Covid-19 articles submitted during 2017–2020. Nevertheless, whilst the review speed of Covid-19 research was particularly fast during the first five months (1.9–3.4 times faster) of the pandemic (January–May 2020), this speed advantage was no longer evident for articles submitted November–December 2020. Faster peer review also associates with higher citation impact for Covid-19 articles in the same journals, suggesting it did not usually compromise the scholarly impact of important Covid-19 research. Overall, then, it seems that core medical and general journals responded quickly but carefully to the pandemic, although the situation returned closer to normal within a year.

Peer Review

https://publons.com/publon/10.1162/qss_a_00176

The promising drugs included in WHO's Solidarity Project: a choice based in scientific knowledge and institutional competencies

BACKGROUND

In March 2020, the World Health Organization (WHO) launched the Solidarity Program, probably the largest global initiative to encourage and support research in four promising drugs, named Remdesivir, Hydroxychloroquine, β Interferon and the combination Lopinavir / Ritonavir, to reduce the mortality of Coronavirus disease 2019 (COVID-19).

OBJECTIVES

Considering the potential impact of Solidarity Program to restrain the current pandemic, the present study aims to investigate whether it was designed upon indicators of scientific productivity, defined as the level of the production of new scientific knowledge and of the institutional capabilities, estimated in terms of scientific publications and technological agreements.

METHODS

The scientific documents on Alphacoronavirus, Betacoronavirus, Gammacoronavirus and Coronavirus were retrieved from Scopus database while the technological agreements on coronavirus were obtained through Cortellis. As for the institutions and countries, we have considered the data on author's affiliations in both set of data. For comparison, we included the analysis of documents related with other drugs or therapies, such as vaccines and antibodies, which were listed in a Clarivate's report on coronaviruses research.

FINDINGS

Most of the analysis refers to documents on Coronavirus, the largest group. The number of documents related to WHO's drugs are almost five times higher than in the other groups. This subset of documents involves the largest and most diverse number of institutions and countries. As for agreements, we observed a smaller number of institutions involved in it, suggesting differences between countries in terms of technical and human capabilities to develop basic and/or clinical research on coronavirus and to develop new forms or products to treat or to prevent the disease.

MAIN CONCLUSIONS

Hence, the results shown in this study illustrate that decisions taken by an international scientific body, as WHO, were mainly based in scientific knowledge and institutional competencies.

Validation of the COVID-19 Disbelief Scale: Conditional indirect effects of religiosity and COVID-19 fear on intent to vaccinate

The COVID-19 pandemic uprooted economies, infected millions, and altered behaviors. Yet, the invisible nature of the disease, paralleled symptoms to the common flu, and misinformation generated COVID-19 disbelief. Many believed COVID-19 was a hoax. Many believed case numbers were fabricated. Others claimed it was a ruse for sociopolitical reasons. The construction of the 8-item COVID-19 Disbelief Scale (CDS) measures the false belief COVID-19 was not real and life-threatening. The CDS demonstrated discriminant validity and robust reliability across two studies. Predictive analysis evinced COVID-19 disbelievers feared COVID-19 less and had lower intent to get vaccinated. In the U.S., certain religious organizations spread misinformation. Religiosity associated with greater COVID-19 disbelief. Among disbelievers, conditional indirect effects of religiosity associated with greater COVID-19 fear and higher intent to get vaccinated. The moderated mediation model validated utility of the CDS as a concise instrument to study variable relationships.

YouTube as a source of information during the Covid-19 pandemic: a content analysis of YouTube videos published during January to March 2020

BACKGROUND

Institutions, government departments, and healthcare professionals engage in social media because it facilitates reaching a large number of people simultaneously. YouTube provides a platform whereby anyone can upload videos and gain feedback on their content from other users. Many YouTube videos are related to health and science, and many people search YouTube for health-related information. YouTube has been acknowledged as a key public information source in recent crises caused by Zika, H1N1, swine flu, and most recently, COVID-19.

METHODS

YouTube videos were collected from the YouTube Application Programming Interface (API) using the search terms COVID-19, coronavirus, COVID19, and corona. The search was conducted on April 4 and 5, 2020. The initial investigation found a total of 1084 videos. The second step involved identifying and verifying the videos for their relationship to COVID-19 information and excluding videos that did not relate to COVID-19 or were in a language other than English and Hindi.

RESULTS

An analysis of YouTube videos covering COVID-19, uploaded in early 2020, in English and Hindi. The sample comprised 349 videos (n = 334 English). Videos were characterized by contributor, duration, content, and reception (views/likes/dislikes/comments). The majority contained general information, with only 4.01% focusing on symptoms and 11.17% on treatment and outcomes. Further, the majority (n = 229) were short videos of under 10 min duration. Videos provided by government and health care professionals comprised 6.87% and 5.74% % of the sample, respectively. News channels uploaded 71.63% of videos.

CONCLUSIONS

YouTube may provide a significant resource for disseminating of information on public health issues like outbreaks of viral infections and should be utilized by healthcare agencies for this purpose. However, there is currently no way to determine whether a video has been produced or verified by authorized healthcare professionals. This limitation needs to be addressed so that the vital distribution services offered by platforms like YouTube can be fully utilized for increasing public understanding of healthcare science, particularly during a crisis such as a pandemic.

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.

COVID-19 enabled co-authoring networks: a country-case analysis

In this paper we seek to examine the co-authoring pattern of a select group of researchers that are affiliated with a specific country. By way of making use of standard bibliometric analysis, we explore the publication evolution of all COVID-19-related peer reviewed papers that have been (co)-authored by researchers that are affiliated with Greek institutions. The aim is to identify its advancement over time, the institutions involved and the countries with which the co-authors are affiliated with. The timeframe of the study spans from the moment that WHO Director-General declared the novel coronavirus outbreak a public health emergency of international concern (WHO, 2020. Archived: WHO timeline-covid-19. Retrieved from Archived: Who Timeline-COVID-19. https://www.who.int/news/item/27-04-2020-who-timeline---covid-19. Accessed on 10 May 2020., Archived: WHO timeline-covid-19), January 2020, to October 2020. Findings indicate that there is a steady increase in the number of publications as well as the number of scientific collaborations over time. At a cross-country level, results suggest that the affiliated institutional sectors such as the Higher Education Sector (HES) and the Government Sector (GOV) contributed the most in terms of scientific output. On an international scale, the evolution of the scientific collaboration is imprinted and distributed as a chain of affiliations that linked nations together. Such chains are represented as clusters of countries, in which the scientific connections between different countries can be visualised. It can be reasoned that a significant amount of publications (20%) is affiliated with countries having “traditionally” major scientific impact on the field of Medicine.

Analyzing knowledge entities about COVID-19 using entitymetrics

COVID-19 cases have surpassed the 109 + million markers, with deaths tallying up to 2.4 million. Tens of thousands of papers regarding COVID-19 have been published along with countless bibliometric analyses done on COVID-19 literature. Despite this, none of the analyses have focused on domain entities occurring in scientific publications. However, analysis of these bio-entities and the relations among them, a strategy called entity metrics, could offer more insights into knowledge usage and diffusion in specific cases. Thus, this paper presents an entitymetric analysis on COVID-19 literature. We construct an entity–entity co-occurrence network and employ network indicators to analyze the extracted entities. We find that ACE-2 and C-reactive protein are two very important genes and that lopinavir and ritonavir are two very important chemicals, regardless of the results from either ranking.

A scientometric overview of CORD-19

As the COVID-19 pandemic unfolds, researchers from all disciplines are coming together and contributing their expertise. CORD-19, a dataset of COVID-19 and coronavirus publications, has been made available alongside calls to help mine the information it contains and to create tools to search it more effectively. We analyse the delineation of the publications included in CORD-19 from a scientometric perspective. Based on a comparison to the Web of Science database, we find that CORD-19 provides an almost complete coverage of research on COVID-19 and coronaviruses. CORD-19 contains not only research that deals directly with COVID-19 and coronaviruses, but also research on viruses in general. Publications from CORD-19 focus mostly on a few well-defined research areas, in particular: coronaviruses (primarily SARS-CoV, MERS-CoV and SARS-CoV-2); public health and viral epidemics; molecular biology of viruses; influenza and other families of viruses; immunology and antivirals; clinical medicine. CORD-19 publications that appeared in 2020, especially editorials and letters, are disproportionately popular on social media. While we fully endorse the CORD-19 initiative, it is important to be aware that CORD-19 extends beyond research on COVID-19 and coronaviruses.

Using altmetrics for detecting impactful research in quasi-zero-day time-windows: the case of COVID-19

On December 31st 2019, the World Health Organization China Country Office was informed of cases of pneumonia of unknown etiology detected in Wuhan City. The cause of the syndrome was a new type of coronavirus isolated on January 7th 2020 and named Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2). SARS-CoV-2 is the cause of the coronavirus disease 2019 (COVID-19). Since January 2020 an ever increasing number of scientific works related to the new pathogen have appeared in literature. Identifying relevant research outcomes at very early stages is challenging. In this work we use COVID-19 as a use-case for investigating: (1) which tools and frameworks are mostly used for early scholarly communication; (2) to what extent altmetrics can be used to identify potential impactful research in tight (i.e. quasi-zero-day) time-windows. A literature review with rigorous eligibility criteria is performed for gathering a sample composed of scientific papers about SARS-CoV-2/COVID-19 appeared in literature in the tight time-window ranging from January 15th 2020 to February 24th 2020. This sample is used for building a knowledge graph that represents the knowledge about papers and indicators formally. This knowledge graph feeds a data analysis process which is applied for experimenting with altmetrics as impact indicators. We find moderate correlation among traditional citation count, citations on social media, and mentions on news and blogs. Additionally, correlation coefficients are not inflated by indicators associated with zero values, which are quite common at very early stages after an article has been published. This suggests there is a common intended meaning of the citational acts associated with aforementioned indicators. Then, we define a method, i.e. the Comprehensive Impact Score (CIS), that harmonises different indicators for providing a multi-dimensional impact indicator. CIS shows promising results as a tool for selecting relevant papers even in a tight time-window. Our results foster the development of automated frameworks aimed at helping the scientific community in identifying relevant work even in case of limited literature and observation time.

Covid19-IBO: A Covid-19 Impact on Indian Banking Ontology Along with an Efficient Schema Matching Approach

The exponential spread of Covid-19 is not only a serious concern for public health but has also severely affected the global economy. India is not an exception. The banking sector must plan innovatively in a wide range of scenarios focusing upon Covid-19 specific requirements. It becomes essential to examine the impact of Covid-19 on the performance of the Indian banking sector and take focused initiatives at both the tactical and the strategic levels. This paper offers the Covid-19 Impact on Banking Ontology (Covid19-IBO) that provides semantic information about the impact of Covid-19 on the banking sector of India. The developed ontology has been verified and validated and has been made available on the Linked Open Data cloud. It can be utilized to annotate the related data to provide meaningful insights. The Covid-19 ontologies already available have some overlapping information that causes redundancy. Unified integration of these ontologies is required to operate upon them unambiguously. It becomes reasonable to develop a matching approach to link all these ontologies semantically. We, therefore, also provide a schema matching approach with reasonable results to map the Covid-19 ontologies.

Let’s do better: public representations of COVID-19 science

COVID science is being both done and circulated at a furious pace. While it is inspiring to see the research community responding so vigorously to the pandemic crisis, all this activity has also created a churning sea of bad data, conflicting results, and exaggerated headlines. With representations of science becoming increasingly polarized, twisted, and hyped, there is growing concern that the relevant science is being represented to the public in a manner that may cause confusion, inappropriate expectations, and the erosion of public trust. Here we explore some of the key issues associated with the representations of science in the context of the COVID-19 pandemic. Many of these issues are not new. But the COVID-19 pandemic has placed a spotlight on the biomedical research process and amplified the adverse ramifications of poor public communication. We need to do better. As such, we conclude with 10 recommendations aimed at key actors involved in the communication of COVID-19 science, including government, funders, universities, publishers, media, and the research communities.

Sistemas de recuperación de información implementados a partir de CORD-19: herramientas clave en la gestión de la información sobre COVID-19

La investigación sobre el coronavirus ha generado una producción de documentos científicos extraordinaria. Su tratamiento y asimilación por parte de la comunidad científica ha necesitado de la ayuda de sistemas de recuperación de información diseñados específicamente. Algunas de las principales instituciones mundiales dedicadas a la lucha contra la pandemia han desarrollado el conjunto de datos CORD-19 que destaca sobre otros proyectos de similar naturaleza. Los documentos recopilados en esta fuente han sido procesados por distintas herramientas de recuperación de información, a veces prototipos o sistemas que ya estaban implementados. Se ha analizado la tipología y características principales de estos sistemas concluyendo que hay tres grandes categorías no excluyentes entre ellas: búsqueda terminológica, visualización de información y procesamiento de lenguaje natural. Destaca enormemente que la gran mayoría de ellos emplean preferentemente tecnologías de búsqueda semántica con el objeto de facilitar la adquisición de conocimiento s los investigadores y ayudarlas en su ingente tarea. La crisis provocada por la pandemia ha sido aprovechada por los buscadores semánticos para encontrar su sitio.

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.

COVID-19 research in Wikipedia

Wikipedia is one of the main sources of free knowledge on the Web. During the first few months of the pandemic, over 5,200 new Wikipedia pages on COVID-19 were created, accumulating over 400 million page views by mid-June 2020. 1 At the same time, an unprecedented amount of scientific articles on COVID-19 and the ongoing pandemic have been published online. Wikipedia’s content is based on reliable sources, such as scientific literature. Given its public function, it is crucial for Wikipedia to rely on representative and reliable scientific results, especially in a time of crisis. We assess the coverage of COVID-19-related research in Wikipedia via citations to a corpus of over 160,000 articles. We find that Wikipedia editors are integrating new research at a fast pace, and have cited close to 2% of the COVID-19 literature under consideration. While doing so, they are able to provide a representative coverage of COVID-19-related research. We show that all the main topics discussed in this literature are proportionally represented from Wikipedia, after accounting for article-level effects. We further use regression analyses to model citations from Wikipedia and show that Wikipedia editors on average rely on literature that is highly cited, widely shared on social media, and peer-reviewed.

Managing the pandemic from the radiology department’s point of view

The COVID-19 pandemic is forcing our entire society to adopt numerous changes, at least until an effective treatment and/or vaccine becomes widely available. Because COVID-19 is a new disease that has required us to make complex decisions based on scant evidence, the pandemic is having an enormous impact on our health system.

Radiology departments play a fundamental role in the management of COVID-19, both in the diagnosis of the disease and in the posterior management of patients. To ensure the safety of patients and healthcare professionals, it is essential to understand the infection so that safe circuits can be implemented.

This article summarizes the pathophysiology of COVID-19 infection and explains the measures that radiology departments need to adopt during the pandemic.

Managing the pandemic from the radiology department's point of view

The COVID-19 pandemic is forcing our entire society to adopt numerous changes, at least until an effective treatment and/or vaccine becomes widely available. Because COVID-19 is a new disease that has required us to make complex decisions based on scant evidence, the pandemic is having an enormous impact on our health system. Radiology departments play a fundamental role in the management of COVID-19, both in the diagnosis of the disease and in the posterior management of patients. To ensure the safety of patients and healthcare professionals, it is essential to understand the infection so that safe circuits can be implemented. This article summarizes the pathophysiology of COVID-19 infection and explains the measures that radiology departments need to adopt during the pandemic.

Use of Data Mining to Determine Usage Patterns of an Online Evaluation Platform During the COVID-19 Pandemic

MenPas is a psychosocial assessment platform¹ developed by the University of Malaga in 2008. There has been a significant increase in data traffic during the period of confinement by COVID-19 (March and April ’20) compared to the same period in the previous year. The main goal to achieve in this work is to determine the patterns of use of this platform on both period of time. So, we want to respond to the following question: So, we the following question: Has the COVID-19 Pandemic changed the pattern of the Menpas users? In order to respond it, cluster analysis techniques (Data Mining) have been used to classify people taking surveys into quotient sets (cluster). This is a multivariate technique for dividing data into sets to that are as homogeneous as possible within themselves and heterogeneous among themselves. Specifically, the K-Means algorithm has been used for this analysis, which is based on the evaluation of the distance between data and the average of each variable. So, it is recommended to discover patterns or relationships among the data. Specifically, the use of the following questionnaires has been analyzed: Competitive State Anxiety Inventory-2 (CSAI-2), State Trait Anxiety Inventory (STAI), Profile of Mood State (POMS), Resilience Scale (RS), Sport Performance Psychological Inventory (IPED), Maslach Burnout Inventory (MBI) and Self-concept Form-5 (AF-5). The analyses have shown changes in cluster formation between 2019 and 2020 based on the variables gender, age, marital status or physical practice. Therefore, the analyses carried out have been sensitive to determine several profiles of people using the MenPas platform because there are changes in the characteristics of the user groups that have carried out the analyzed tests.

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.