The scientific literature on Coronaviruses, COVID-19 and its associated safety-related research dimensions: A scientometric analysis and scoping review

A Worldwide Bibliometric Analysis of Published Literature Assessing Fear of COVID-19

Many people experience intense fear of COVID-19. The purpose of this study was to provide a comprehensive visual overview of the published literature from 2020 to 2022 assessing fear of COVID-19. From 2020 to 2022, we employed the Scopus database to conduct a bibliometric analysis. We used the VOSviewer program to perform the author co-citation analysis, Mapchart to produce a worldwide map, and Wordart to make a word cloud image. From the 1769 records examined, 1654 (93.50%) were articles, with English being the most common language (96.31%). From 2020 to 2022, annual citations experienced significant growth (R2 = 99.91%; p = 0.0195). The Institut National de la Santé et de la Recherche Médicale (INSERM, France) and China led in terms of publication output (n = 36; n = 255). M. D. Griffiths authored the highest number of articles (n = 21). The most active journal was the International Journal of Environmental Research and Public Health (n = 146), and the most prevalent keyword was "human/s" (11.51%). This bibliometric analysis evaluates the quality of the research on fear of the pandemic and the crisis management of COVID-19, which can provide managers and researchers with crucial insights for future decision making.

Bibliometric study of the scientific productivity of the COVID-19 impact on constructs affecting happiness in university students

COVID-19 has caused a wide range of psychological problems, such as panic disorders, anxiety, and depression. Knowing what others have researched on, what constructs they have focused on, will (a) summarize published information, (b) help identify research gaps, and (c) encourage future research that addresses these gaps. The aim of the study was to analyze the bibliometric indicators of scientific productivity of the impact of COVID-19 on constructs affecting undergraduate happiness. A bibliometric study was conducted. The PubMed database was used. Data summarized were: authors, year of publication, journal name, country, language of publication, and subtopic addressed. A total of 16 English-language studies were identified between April 2022 and December 2022. There were 12 countries that have published on the impact of COVID-19 on constructs affecting college students' happiness. Most of the studies were developed in the United States (n = 4, 25%) and China (n = 2, 12.5%). Thirteen journals publishing these topics were detected. The subtopics considered were organized into nine categories (e.g., a: Psychological impact, b: Adverse childhood experiences, c: Stress, d: Personality traits, e: Perception of the educational environment, f: Spiritual health, g: Distress, h: Uncertainty and socioemotional learning, i: Satisfaction with life). This study suggests that the number of countries and scientific journals that have published on the impact of COVID-19 on constructs affecting college students' happiness is small. In addition, the most discussed subtopics during the pandemic were related to constructs such as psychological impact and stress affecting college students' happiness.

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

AIM

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

DESIGN

bibliometric analysis.

METHODS

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

RESULTS

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

CONCLUSION

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

COVID-19 Response of the Journal Public Health Reports (PHR), March 2020-March 2023

OBJECTIVE

Publication science is the scholarly study of various aspects of the academic publishing process. Its applications to COVID-19 literature have been limited. Here, we describe COVID-19 submissions to, and resulting articles published by, the journal Public Health Reports (PHR), an important resource for US public health practice.

METHODS

We reviewed PHR's COVID-19 submissions and articles published between March 27, 2020, and March 27, 2023. We coded each article for article type, author affiliation, the categories listed in PHR's call for COVID-19 papers, and the public health emergency preparedness and response capabilities from the Centers for Disease Control and Prevention (CDC).

RESULTS

During the study period, PHR received 1545 COVID-19 submissions and published 190 of those articles in a collection, COVID-19 Response. The COVID-19 Response collection included 102 research articles, 29 case study/practice articles, and 24 commentaries. The corresponding author of more than half (52.1%; n = 99) of the articles was affiliated with academia. By the categories listed in PHR's call for COVID-19 papers, 51 articles addressed health disparities, 38 addressed public health surveillance, and 34 addressed COVID-19 vaccination. By the CDC public health emergency preparedness and response capabilities, 87 articles addressed public health surveillance and epidemiologic investigation, 38 addressed community preparedness, and 32 addressed community recovery. The percentage of articles focused on policy/law was higher early in the pandemic (2020-2021) than later (2022-2023) (9.5% vs <3.0%). During the latter period, articles largely focused on vaccination (12.8%) and contact tracing (10.6%).

CONCLUSIONS

Articles published in PHR's COVID-19 Response collection covered a broad range of topics and were authored by contributors from diverse organizations. Our characterization of the COVID-19 output of a representative US public health practice journal can help academic publishing better address informational needs of public health responders.

COVID-19 resilience index in European Union countries based on their risk and readiness scale

Addressing risks and pandemics at a country level is a complex task that requires transdisciplinary approaches. The paper aims to identify groups of the European Union countries characterized by a similar COVID-19 Resilience Index (CRI). Developed in the paper CRI index reflects the countries' COVID-19 risk and their readiness for a crisis situation, including a pandemic. Moreover, the study detects the factors that significantly differentiate the distinguished groups. According to our research, Bulgaria, Hungary, Malta, and Poland have the lowest COVID-19 Resilience Index score, with Croatia, Greece, Czechia, and Slovakia following close. At the same time, Ireland and Scandinavian countries occupy the top of the leader board, followed by Luxemburg. The Kruskal-Wallis test results indicate four COVID-19 risk indicators that significantly differentiate the countries in the first year of the COVID-19 pandemic. Among the significant factors are not only COVID-19-related factors, i.e., the changes in residential human mobility, the stringency of anti-COVID-19 policy, but also strictly environmental factors, namely pollution and material footprint. It indicates that the most critical global environmental issues might be crucial in the phase of a future pandemic. Moreover, we detect eight readiness factors that significantly differentiate the analysed country groups. Among the significant factors are the economic indicators such as GDP per capita and labour markets, the governance indicators such as Rule of Law, Access to Information, Implementation and Adaptability measures, and social indicators such as Tertiary Attainment and Research, Innovation, and Infrastructure.

Trends in Robotics Research in Occupational Safety and Health: A Scientometric Analysis and Review

Robots have been deployed in workplaces to assist, work alongside, or collaborate with human workers on various tasks, which introduces new occupational safety and health hazards and requires research efforts to address these issues. This study investigated the research trends for robotic applications in occupational safety and health. The scientometric method was applied to quantitatively analyze the relationships between robotics applications in the literature. The keywords "robot", "occupational safety and health", and their variants were used to find relevant articles. A total of 137 relevant articles published during 2012-2022 were collected from the Scopus database for this analysis. Keyword co-occurrence, cluster, bibliographic coupling, and co-citation analyses were conducted using VOSviewer to determine the major research topics, keywords, co-authorship, and key publications. Robot safety, exoskeletons and work-related musculoskeletal disorders, human-robot collaboration, and monitoring were four popular research topics in the field. Finally, research gaps and future research directions were identified based on the analysis results, including additional efforts regarding warehousing, agriculture, mining, and construction robots research; personal protective equipment; and multi-robot collaboration. The major contributions of the study include identifying the current trends in the application of robotics in the occupational safety and health discipline and providing pathways for future research in this discipline.

Socioeconomic impacts of COVID-19 pandemic on foodborne illnesses in the United States

Foodborne diseases continue to impact human health and the economy. The COVID-19 pandemic has dramatically affected the food system from production to consumption. This project aims to determine the impact of the COVID-19 pandemic on the spread of foodborne diseases and the factors that may have contributed, including environmental, behavioral, political, and socioeconomic. Data for this study were collected from The Foodborne Diseases Active Surveillance Network (FoodNet) for 2015-2020. FoodNet personnel located at state health departments regularly contact the clinical laboratories in Connecticut (CT), Georgia (GA), Maryland (MD), Minnesota (MN), New Mexico (NM), Oregon (OR), Tennessee (TN), and selected counties in California (CA), Colorado (CO), and New York (NY). Data were analyzed using SAS to determine the changes in rates of foodborne pathogens reported in FoodNet before and during the COVID-19 pandemic in the ten reporting states. Results of the study showed a significant decline in the incidences of foodborne diseases ranging between 25% and 60%. A geographical variation was also observed between California and states with the highest decline rate of foodborne illnesses. Policies and restrictions, in addition to environmental and behavioral changes during the COVID-19 pandemic, may have reduced rates of foodborne diseases.

Hydrostatic Penetration Testing of Protective Glove Materials Using Water and Synthetic Blood to Evaluate Hole Size and Screen Mesh Using an Automated Pressure Delivery System

There are several international standards that address the resistance of chemical protective clothing materials to the penetration by liquids. The hydrostatic pressure has been documented to discriminate between protective clothing material performance and correlates with visual penetration results that are obtained with human factors validation. The same methodology, based on hydrostatic pressure equipment, is referenced also in other standards addressing penetration resistance of protective clothing and glove materials against synthetic blood or blood-borne pathogens. In this study, we present an automated hydrostatic penetration testing that integrates testing procedures from several standards to evaluate the resistance of materials to penetration by liquids under pressure. The automated control system allows the user to select a specific test method and automatically sets a stepped pressurization protocol to test the material. A pass or a fail result is produced at a certain time and pressure. As an example of application, the penetration of synthetic blood was assessed through gloves made from different materials with ISO 16603, method B, one of the five possible penetration methods and protocols available in the test equipment. The results indicate that the developed system facilitates the application of test methods used to evaluate the barrier effectiveness against liquids of materials used for protective clothing and gloves and show up that the characteristics of the retention grid used have a decisive influence on the test results. In some of the tested glove materials, holes were intentionally performed with needles with different gauges. The capacity of pinhole detection in gloves was evaluated according to the test method selected and compared with results obtained with the classic water leak test method for gloves described in EN ISO 374-2.

Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data

With the spread of the deadly coronavirus disease throughout the geographies of the globe, expertise from every field has been sought to fight the impact of the virus. The use of Artificial Intelligence (AI), especially, has been the center of attention due to its capability to produce trustworthy results in a reasonable time. As a result, AI centric based research on coronavirus (or COVID-19) has been receiving growing attention from different domains ranging from medicine, virology, and psychiatry etc. We present this comprehensive study that closely monitors the impact of the pandemic on global research activities related exclusively to AI. In this article, we produce highly informative insights pertaining to publications, such as the best articles, research areas, most productive and influential journals, authors, and institutions. Studies are made on top 50 most cited articles to identify the most influential AI subcategories. We also study the outcome of research from different geographic areas while identifying the research collaborations that have had an impact. This study also compares the outcome of research from the different countries around the globe and produces insights on the same.

The effects of COVID-19 on safety practices in construction projects

The coronavirus (COVID-19) pandemic was recognized as a worldwide epidemic and classed as a high risk in early 2020, affecting people's health, economies, and business sectors considerably. This pandemic has had an impact on people's lifestyles and work processes in a multitude of sectors. The construction industry is one such industry that has had a substantial influence on it. However, this influence needs to be measured in different areas. This study aims to measure the effects of the COVID-19 on the 7 core safety elements and their 24 procedures that are derived from the recommended practices for safety and health programs in construction that is issued by OSHA to see whether their priorities have been changed or not. The data were collected and then analyzed using Relative Importance Index (RII) to study the changes in their priorities; and using t-test to study the significance of the changes before and after COVID-19 pandemic.

Nexus between drivers of COVID-19 and country risks

COVID-19 has disrupted all spheres of life, including country risk regarding the exposure of economies to multi-dimensional risk drivers. However, it remains unexplored how COVID-19 has impacted different drivers of country risk in a probabilistic network setting. This paper uses two datasets on country-level COVID-19 and country risks to explore dependencies among associated drivers using a Bayesian Belief Network model. The drivers of COVID-19 risk, considered in this paper, are hazard and exposure, vulnerability and lack of coping capacity, whereas country risk drivers are economic, financing, political, business environment and commercial risks. The results show that business environment risk is significantly influenced by COVID-19 risk, whereas commercial risk (demand disruptions) is the least important factor driving COVID-19 and country risks. Further, country risk is mainly influenced by financing, political and economic risks. The contribution of this study is to explore the impact of various drivers associated with the country-level COVID-19 and country risks in a unified probabilistic network setting, which can help policy-makers prioritize drivers for managing the two risks.

Impact of COVID-19 on distance learning practical design courses

This paper explores the impact of COVID-19 on higher education practical design courses in Egypt. Because of inadequate resources and preparedness, Egyptian colleges have struggled to adopt digital teaching methods during the COVID-19 pandemic. This paper examines strategies that are the most feasible for teaching practical courses during or after a pandemic through distance learning (on online platforms). An action research project was set up to deliver two studio-based design courses, one on architectural drawing and the other on furniture design via distance learning (online mode). This approach used a suite of technologies and synchronous and asynchronous delivery mechanisms, such as Zoom and Google Classroom. Student perceptions about the impact of these changes were evaluated using questionnaires. A psychological effect of the conditions caused by the pandemic on students has been the loss of interest in academics. The research results partially support the use of online platforms to teach practical courses. However, more needs to be done to improve the delivery of online courses in Egypt. Further, holding competitions was found to boost students' motivation levels. A future strategy for teaching practical courses in applied arts and engineering is proposed in this paper.

COVID-19-The Role of Artificial Intelligence, Machine Learning, and Deep Learning: A Newfangled

The absolute previously infected novel coronavirus (COVID-19) was found in Wuhan, China, in December 2019. The COVID-19 epidemic has spread to more than 220 nations and territories globally and has altogether influenced each part of our day-to-day lives. As of 9th March 2022, a total aggregate of 44,78,82,185 (60,07,317) contaminated (dead) COVID-19 cases were accounted for all over the world. The quantities of contaminated cases passing despite everything increment essentially and do not indicate a controlled circumstance. The scope of this paper is to address this issue by presenting a comprehensive and comparative analysis of the existing Machine Learning (ML), Deep Learning (DL) and Artificial Intelligence (AI) based approaches used in significance in reacting to the COVID-19 epidemic and diagnosing the severe impacts. The paper provides, firstly, an overview of COVID-19 infection and highlights of this article; Secondly, an overview of exploring various executive innovations by utilizing different resources to stop the spread of COVID-19; Thirdly, a comparison of existing predicting methods of COVID-19 in the literature, with focus on ML, DL and AI-driven techniques with performance metrics; and finally, a discussion on the results of the work as well as future scope.

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.

Coronavirus 2019 disease: Are corticosteroids the key treatment? A retrospective case-control study in Brazil

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is the putative cause of coronavirus disease 2019 (COVID-19), a serious disease that has severely impacted the world. Although vaccines have been developed, it will take time to inoculate the global population. Current guidelines have focused on the treatment of severe cases in hospital settings; however, a void has been created regarding appropriate measures for those in the initial stage of COVID-19 and those experiencing moderate disease severity progressing to desaturation. We assessed clinical outcomes in patients with COVID-19 with pneumonia at initial presentation treated with corticosteroids.

Methods

Data of 177 consecutive high-risk patients with COVID-19, monitored by telemedicine, were collected and analyzed. Of those, 68 patients were in the initial inflammatory phase of the disease without desaturation and received corticosteroids. The outcomes were evaluated after a follow up of 14 days. Four patients were immediately referred to the hospital because they had explicit desaturation at presentation.

Results

After 14 days, all patients in the inflammatory phase at presentation who were treated with corticosteroids before desaturation were alive and without complications. However, of the four patients with desaturation, one died at the hospital.

Conclusion

In this study, the use of corticosteroids during the initial pulmonary phase of COVID-19 before desaturation, in addition to daily monitoring of patients, prevented disease progression, decreased the risk of complications and incidence of hospitalization and death. However, additional studies with larger number of patients are needed to confirm these findings.

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Use of corticosteroids in COVID-19 patients before desaturation increased survival.

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Patients who reached desaturation needed hospitalization.

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Approximately 25% mortality was observed in hospitalized patients.

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The use of corticosteroids before desaturation prevented hospitalization and death.

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Corticosteroids can be used to decrease the risk of complications of COVID-19.

Evolution Model and Simulation Study of the Public Risk Perception of COVID-19

The evolution of the public perception of the risk in public health emergencies is closely related to risk response behavior. There are few systematic explanations and empirical studies on how the individual receiving the risk information affects the change in the individual risk perception through internal mechanisms in the context of COVID-19. Based on the understanding of the existing research, this paper constructs the evolution model of the public risk perception level based on the limited memory theory and a simulation analysis is performed. The results are as follows: memory rate, association rate, information reception and information stimulation in a single period of time have significant indigenous effects on the risk perception; when the amount of information received and the information stimulus remain unchanged, the public's risk perception follows a monotonic upward trend, but there is an upper limit function, and the upper limit is determined by the memory rate and association rate, and the influence of the association rate is higher than that of the memory rate; When the amount of information received and the information stimulus changes, the public's risk perception will also change, and there is a lag effect, which is determined by the memory rate. The impact of the acceptance of the information on the risk perception is greater than that of the information stimulus.

Macro-level literature analysis on pedestrian safety: Bibliometric overview, conceptual frames, and trends

Due to the high volume of documents in the pedestrian safety field, the current study conducts a systematic bibliometric analysis on the researches published before October 3, 2021, based on the science-mapping approach. Science mapping enables us to present a broad picture and comprehensive review of a significant number of documents using co-citation, bibliographic coupling, collaboration, and co-word analysis. To this end, a dataset of 6311 pedestrian safety papers was collected from the Web of Science Core Collection database. First, a descriptive analysis was carried out, covering whole yearly publications, most-cited papers, and most-productive authors, as well as sources, affiliations, and countries. In the next steps, science mapping was implemented to clarify the social, intellectual, and conceptual structures of pedestrian-safety research using the VOSviewer and Bibliometrix R-package tools. Remarkably, based on intellectual structure, pedestrian safety demonstrated an association with seven research areas: "Pedestrian crash frequency models", "Pedestrian injury severity crash models", "Traffic engineering measures in pedestrians' safety", "Global reports around pedestrian accident epidemiology", "Effect of age and gender on pedestrians' behavior", "Distraction of pedestrians", and "Pedestrian crowd dynamics and evacuation". Moreover, according to conceptual structure, five major research fronts were found to be relevant, namely "Collision avoidance and intelligent transportation systems (ITS)", "Epidemiological studies of pedestrian injury and prevention", "Pedestrian road crossing and behavioral factors", "Pedestrian flow simulation", and "Walkable environment and pedestrian safety". Finally, "autonomous vehicle", "pedestrian detection", and "collision avoidance" themes were identified as having the greatest centrality and development degrees in recent years.

Crowd dynamics research in the era of Covid-19 pandemic: Challenges and opportunities

With the issues of crowd control and physical distancing becoming central to disease prevention measures, one would expect that crowd research should become a focus of attention during the Covid-19 pandemic era. However, I will show, based on a variety of metrics, that not only has this not been the case, but also, the first two years of the pandemic have posed an undisputable setback to the development and growth of crowd science. Without intervention, this could potentially aggravate further and cause a long-lasting recession in this field. This article, in addition to documenting and highlighting this issue, aims to outline potential avenues through which crowd research can reshape itself in the era of Covid-19 pandemic, maintain its pre-pandemic momentum and even further expand the diversity of its topics. Despite significant changes that the pandemic has brought to human life, issues related to congregation and mobility of pedestrians, building fires, crowd incidents, rallying crowds and the like have not disappeared from societies and remain relevant. Moreover, the diversity of pandemic-related problems itself creates a rich ground for making novel scientific discoveries. This could provide grounds for establishing fresh dimensions in crowd dynamics research. These potential new dimensions extend to all areas of this field including numerical and experimental investigations, crowd psychology and applications of computer vision and artificial intelligence methods in crowd management. The Covid-19 pandemic may have posed challenges to crowd researchers but has also created ample potential opportunities. This is further evidenced by reviewing efforts taken thus far in pandemic-related crowd research.

Beyond the Right to Have Freedom: Religion and Belief in the Context of COVID-19 Health Emergency Regulation in Indonesia

This article argues that the right to have and express freedom can be restricted for several reasons, including a public safety emergency. In line with this idea, this article discusses government regulations in response to the COVID-19 pandemic, which had a crucial impact on the discourse on the right to freedom in Indonesia. Methodologically, this study uses critical qualitative analysis to overview the focus issue of this research in academic work and mainstream media coverage. At this point, this study uses relevant and recently published information regarding the intersection between Indonesian government regulations related to COVID-19 and the manifestation of the right to freedom, especially freedom of religion. This article provides an essential finding that restrictions on the right to have freedom are justified in consideration of public health due to the COVID-19 pandemic. International human rights conventions explain this mechanism. This article is a timely and contextual academic review with two contributions. First, this article theoretically adds information to academic discussions around the intersection between human rights, religion, and state regulation. Second, this study will help the state and religion build a constructive response to the COVID-19 pandemic and future crises. This contribution can be elaborated more profound and comprehensive in future research.

Clinical and epidemiological aspects of SARS-CoV-2 infection among pregnant and postpartum women in Mozambique: a prospective cohort study

Background

Although there is a significant increase of evidence regarding the prevalence and impact of COVID-19 on maternal and perinatal outcomes, data on the effects of the pandemic on the obstetric population in sub-Saharan African countries are still scarce. Therefore, the study aims were to assess the prevalence and impact of COVID-19 on maternal and neonatal outcomes in the obstetric population at Central Hospital of Maputo (HCM), Mozambique.

Methods

Prospective cohort study conducted at teaching and referral maternity, HCM, from 20 October 2020 to 22 July 2021. We collected maternal and perinatal outcomes up to 6 weeks postpartum of eligible women (pregnant and postpartum women—up to the 14th day postpartum) screened for COVID-19 (individual test for symptomatic participants and pool testing for asymptomatic). The primary outcome was maternal death, Severe Acute Respiratory Syndrome (SARS) and Intensive Care Unit (ICU) admission. We estimated the COVID-19 prevalence and the unadjusted RR (95% CI) for maternal and perinatal outcomes. We used the chi-square or Fisher's exact test to compare categorical variables (two-sided p-value < 0.05 for statistical significance).

Results

We included 239 participants. The overall prevalence of COVID-19 was 9.2% (22/239) and in the symptomatic group was 32.4% (11/34). About 50% of the participants with COVID-19 were symptomatic. Moreover, the most frequent symptoms were dyspnoea (33.3%), cough (28.6%), anosmia (23.8%), and fever (19%). Not having a partner, being pregnant, and alcohol consumption were vulnerability factors for SARS-CoV-2 infection. The risk of adverse maternal and neonatal outcomes (abortion, foetal death, preterm birth, Apgar, and NICU admission) was not significantly increased with COVID-19. Moreover, we did not observe a significant difference in the primary outcomes (SARS, ICU admission and maternal death) between COVID-19 positive and COVID-19 negative groups.

Conclusion

The prevalence of COVID-19 in the obstetric population is higher than in the general population, and fifty percent of pregnant and postpartum women with COVID-19 infection are asymptomatic. Not having a partner and alcohol consumption were factors of greatest vulnerability to SARS-COV-2 infection. Moreover, being pregnant versus postpartum was associated with increased vulnerability to COVID-19. Data suggest that pregnant women with COVID-19 may have a higher frequency of  COVID-19 infection, reinforcing the need for universal testing, adequate follow-up for this population, and increasing COVID-19 therapy facilities in Mozambique. Moreover, provide counselling during Antenatal care for COVID-19 preventive measures. However, more prospective and robust studies are needed to assess these findings.

The epidemiological pattern of the COVID-19 pandemic in Africa is heterogeneous, and many African countries are still struggling to establish efficient testing policy, guarantee sufficient laboratory supply and achieve or maintain adequate testing capacity. In addition, evidence suggests that sexual and reproductive health services were the most affected by the pandemic; this scenario might have devastating effects on maternal and perinatal health. Moreover, data from non-sub-Saharan countries the SARS-CoV-2 infection among pregnant and postpartum women is associated with an increased risk of adverse maternal and neonatal health (preterm birth, preeclampsia and maternal death).

Although there is a significant increase of evidence regarding the prevalence and impact of COVID-19 on maternal and perinatal health, data on the effects of this condition on the obstetric population in low-income countries are scarce. Therefore, the study objective were to assess the prevalence and impact of COVID-19 on maternal and neonatal health at referral maternity in Maputo, Mozambique.

Our findings suggest that the prevalence of COVID-19 in the obstetric population is higher than the general population, and most pregnant and postpartum women are asymptomatic. Being pregnant, not having a partner and alcohol consumption were factors of greatest vulnerability to SARS-COV-2 infection. Moreover, the risk of COVID-19 among pregnant was seven-fold higher than in postpartum women. Pregnant women with COVID-19 may have a higher frequency of adverse gestational outcomes (foetal death and abortion). Although the risk of adverse maternal outcomes (death, Severe Acute Respiratory Syndrome and Intensive Care Unit admission) did not differ significantly between the COVID-19 and COVID-19 negative groups, universal screening for COVID-19 should be implemented to ensure adequate management of pregnant women and newborns.

What, Where, When and How of COVID-19 Patents Landscape: A Bibliometrics Review

Two years after COVID-19 came into being, many technologies have been developed to bring highly promising bedside methods to help fight this epidemic disease. However, owing to viral mutation, how far the promise can be realized remains unclear. Patents might act as an additional source of information for informing research and policy and anticipating important future technology developments. A comprehensive study of 3741 COVID-19-related patents (3,543 patent families) worldwide was conducted using the Derwent Innovation database. Descriptive statistics and social network analysis were used in the patent landscape. The number of COVID-19 applications, especially those related to treatment and prevention, continued to rise, accompanied by increases in governmental and academic patent assignees. Although China dominated COVID-19 technologies, this position is worth discussing, especially in terms of the outstanding role of India and the US in the assignee collaboration network as well as the outstanding invention portfolio in Italy. Intellectual property barriers and racist treatment were reduced, as reflected by individual partnerships, transparent commercial licensing and diversified portfolios. Critical technological issues are personalized immunity, traditional Chinese medicine, epidemic prediction, artificial intelligence tools, and nucleic acid detection. Notable challenges include balancing commercial competition and humanitarian interests. The results provide a significant reference for decision-making by researchers, clinicians, policymakers, and investors with an interest in COVID-19 control.

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.

What Country, University, or Research Institute, Performed the Best on Covid-19 During the First Wave of the Pandemic?: Bibliometric analysis of scientific literature - analysing a 'snapshot in time' of the first wave of COVID-19

In this article, we conduct data mining and statistical analysis on the most effective countries, universities, and companies, based on their output (e.g., produced or collaborated) on COVID-19 during the first wave of the pandemic. Hence, the focus of this article is on the first wave of the pandemic. While in later stages of the pandemic, US and UK performed best in terms of vaccine production, the focus in this article is on the initial few months of the pandemic. The article presents findings from our analysing of all available records on COVID-19 from the Web of Science Core Collection. The results are compared with all available data records on pandemics and epidemics from 1900 to 2020. This has created interesting findings that are presented in the article with visualisation tools.

Supplementary information

The online version contains supplementary material available at 10.1007/s40745-022-00406-8.

Spotlight on Early COVID-19 Research Productivity: A 1-Year Bibliometric Analysis

Coronavirus disease 2019 (COVID-19), one of the most serious public health crises in over a century, has led to an unprecedented surge of publications across all areas of knowledge. This study assessed the early research productivity on COVID-19 in terms of vaccination, diagnosis, treatment, symptoms, risk factors, nutrition, and economy. The Scopus database was searched between January 1, 2020 and December 31, 2020 to initially examine the research productivity on COVID-19, as measured by total publications by the 20 highest-ranked countries according to gross domestic product. The literature search was then refined, and research productivity was assessed across seven major research domains related to COVID-19: vaccination, diagnosis, treatment, symptoms, risk factors, nutrition, and economy. The initial literature search yielded 53,348 publications. Among these, 27,801 publications involved authorship from a single country and 22,119 publications involved authorship from multiple countries. Overall, the United States was the most productive country (n = 13,491), with one and a half times or more publications than any other country, on COVID-19 and the selected domains related to it. However, following adjustment for population size, gross domestic product, and expenditure for research and development, countries of emerging economies such as India along countries of lower population density such as Switzerland, Indonesia, and Turkey exhibited higher research productivity. The surge of COVID-19 publications in such a short period of time underlines the capacity of the scientific community to respond against a global health emergency; however where future research priorities and resource distribution should be placed on the respective thematic fields at an international level, warrants further investigation.

Assessing the impact of mobility on the incidence of COVID-19 in Dublin City

COVID-19 has had a major impact on the transport systems around the world. Several transport-related policies were implemented in short period of time to contain the spread of the pandemic. These policies had a major influence on travel behavior and people's perception towards the safety of different modes of transport, especially public transport, thus affecting several sustainable mobility initiatives. To build a resilient and sustainable transport system and to rebuild trust in public transport, it is important to understand the role of mobility in the spread of COVID-19 pandemic. The present study investigates the relationship between mobility and reported COVID-19 infections using data from Dublin city. Different modes of transport including traffic volume, bus passengers, pedestrians and cyclists were considered in the study during a forty week period. Multiple scenarios involving two-week lag and three-week lag of mobility data and COVID-19 infections were considered in building statistical models. Results showed that, 36.2% of the reported COVID-19 infections after a two-week lag and 33% of the infections after a three-week lag. Our research examines the links between movements and COVID-19 numbers, but clearly this was not the only reason for increased case numbers as many other events impacted on increased numbers. The study further discusses the policy implications and strategies for ensuring a resilient and sustainable transport system.

Exploring machine learning: a scientometrics approach using bibliometrix and VOSviewer

Machine Learning has found application in solving complex problems in different fields of human endeavors such as intelligent gaming, automated transportation, cyborg technology, environmental protection, enhanced health care, innovation in banking and home security, and smart homes. This research is motivated by the need to explore the global structure of machine learning to ascertain the level of bibliographic coupling, collaboration among research institutions, co-authorship network of countries, and sources coupling in publications on machine learning techniques. The Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) was applied to clustering prediction of authors dominance ranking in this paper. Publications related to machine learning were retrieved and extracted from the Dimensions database with no language restrictions. Bibliometrix was employed in computation and visualization to extract bibliographic information and perform a descriptive analysis. VOSviewer (version 1.6.16) tool was used to construct and visualize structure map of source coupling networks of researchers and co-authorship. About 10,814 research papers on machine learning published from 2010 to 2020 were retrieved for the research. Experimental results showed that the highest degree of betweenness centrality was obtained from cluster 3 with 153.86 from the University of California and Harvard University with 24.70. In cluster 1, the national university of Singapore has the highest degree betweenness of 91.72. Also, in cluster 5, the University of Cambridge (52.24) and imperial college London (4.52) having the highest betweenness centrality manifesting that he could control the collaborative relationship and that they possessed and controlled a large number of research resources. Findings revealed that this work has the potential to provide valuable guidance for new perspectives and future research work in the rapidly developing field of machine learning.

Coronavirus-A Crippling Affliction to Humans

Coronaviruses hold idiosyncratic morphological features and functionality. The members of this group have a remarkable capability of infecting both animals and humans. Inimitably, the replication of the RNA genome continues through the set of viral mRNA molecules. Coronaviruses received the least attention until 2003 since they caused only minor respiratory tract illnesses. However, this changed exclusively with the introduction of zoonotic SARS-CoV in 2003. In 2012, MERS-CoV emerged and confirmed this group of viruses as the major causative agents of severe respiratory tract illness. Today, Coronavirus Disease 2019 (i.e., COVID-19) has turned out to be a chief health problem that causes a severe acute respiratory disorder in humans. Since the first identification of COVID-19 in December 2019 in Wuhan, China, this infection has devastatingly spread all around the globe leading to a crippling affliction for humans. The strain is known as the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and WHO (the World Health Organization) has termed this new pandemic disease as Coronavirus Disease (COVID-19). COVID-19 is still spreading, with an estimated 136 million confirmed cases and more than 2.94 million deaths worldwide so far while the pandemic is still going on. In the current scenario, there is no particular treatment for COVID-19, however remarkable efforts for immunization and vaccine development can be observed. Therefore, the execution of precautions and proper preventive measures are indispensable to minimize and control the community transmission of the virus. This review summarizes information about the pathophysiology, transmission, symptoms, and the host defense mechanism as well as immunization and vaccine development against COVID-19.

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.

Emerging technologies and their roles during the COVID-19 pandemic and safety challenges of frontline medical staff: a rapid review

Purpose

The coronavirus 2019 (COVID-19) pandemic has rapidly spread worldwide, with an ever-increasing number of confirmed positive cases and mortality rate. Moreover, frontline medical staff fighting with the COVID-19 infection have been infected and show psychological effects of the pandemic. This study presents an overview of the emerging literature on the safety challenges of frontline medical staff and how technology is being used to control the COVID-19 pandemic.

Methods

This study conducts a rapid review of available studies by following the “preferred reporting items for systematic reviews and meta-analyses” (PRISMA) guidelines. Sixty-three articles were selected for this rapid review paper from three popular digital data repositories.

Results

The majority of the studies chosen focused on the discussion of COVID-19 with regard to China, Singapore, Italy, and the USA. A previously proposed framework is used to synthesize the findings of this study. The results throw light on the several challenges faced by medical staff during the COVID-19 pandemic. Eleven major technologies have been identified in this paper.

Conclusion

This work concludes that technology helps in the prevention and detection of the COVID-19 infection, where it specifically helps in reducing the safety challenges of frontline medical staff and monitoring the COVID-19 patients.

Safety assessment for temporary hospitals during the COVID-19 pandemic: A simulation approach

Amid the devastating effects caused by the pandemic of the new Coronavirus (COVID-19), health leaders around the world are adding efforts to search efficient and effective responses in the fight against the disease. Conventional health centers, such as hospitals and emergency departments have been registering an increase in demand and atypical patterns due to the high transmissibility of the virus. In this context, the adoption of Temporary Hospitals (THs) is effective in trying to relieve conventional hospitals and direct efforts in the treatment of suspected and positive patients for COVID-19. However, some requirements should be considered regarding the processes performed by THs to maintain the health and safety of patients and staff. Based on the literature, we evaluated aspects related to patient safety in THs, especially linked to biosafety of medical facilities, and patient transport and visit. We highlight the analysis of flows and layouts, hospital cleaning and patient care. We described two case studies to demonstrate the proposed approach. As result, simulation tests improved safety metrics, such as waiting time for procedures, movement intensity in each area, length of stay and TH capacity. We conclude that the approach allows us to provide better THs that prevent cross-contamination, provide suitable care, and meet the demand.

Optimization of COVID-19 face mask waste fibers and silica fume as a balanced mechanical ameliorator of fat clay using response surface methodology

The balanced amelioration of mechanical characteristics of fat clay with an additive refers to the attainment of high strength without compromising ductility, which is unattainable by solitary usage of a cementing additive. For this purpose, an amalgamated binary admixture (ABA) is proposed by assimilating shredded face mask (FM) waste, which is posing serious environmental concerns these days, with a cementitious waste material, i.e., silica fume (SF). However, for such ABA, the optimization of mix design is desirable because an excessive amount of one component could disturb the required balance. To address this issue, response surface methodology (RSM) is used in the current study, which is a strong technique used during the process of production to develop, improve, and optimize product inputs. Several experiments are designed and conducted to evaluate mechanical responses, i.e., unconfined compressive strength (qu), brittleness index (IB), deformability index (ID), and California bearing ratio (CBR) value, of treated fat clay by varying mix designs of ABA. Based on the test results, mathematical models are developed which are found to be statistically valid to predict the subjected responses using SF and FM as inputs. Afterward, an optimized mix design is determined by integrating developed models with a desirability function model and setting maximization of strength and ductility as the optimization goals. An ABA having 7.9% SF and 1.2% FM is observed to provide the highest strength and ductility for multiple applications, i.e., road and buildings, with desirability factor close to unity; responses of which are also validated by performing tests. Furthermore, analysis of cleaning aspect shows that the use of optimized ABA in place of cement for subgrade improvement of 1 km two-lane road could avoid CO2 emission of around 79,032 kg of C, save 42,720 kWh and 1174.8 GJ of electrical and thermal energy, respectively, and clean 43 Mg of FM waste; however, astute protocols of COVID-19 FM waste handling and disinfection are needed to be established and followed.

Preparedness of Public Hospitals for the Coronavirus (COVID-19) Pandemic in Lahore District, Pakistan

Background

Pakistan reported more than a million cases during the coronavirus disease 2019 (COVID-19) pandemic, shuffling the already resource-constrained health system that is known for its high vulnerability and lack of adaption.

Objective

To find out the level of preparedness of public hospitals for the novel COVID-19 pandemic in Lahore district.

Methods

A descriptive cross-sectional study was conducted from April to July 2021 among all 18 public hospitals under Specialized Health Care and Medical Education (SHC&ME) in Lahore by administering World Health Organization (WHO) and SHC&ME modified and pre-tested interviewer based and observation checklist. The level of preparedness was assessed for 11 domains, and each domain was scored as a dichotomous variable (Yes and No). Hospital preparedness was labeled as ‘acceptable,’ ‘insufficient,’ and ‘unacceptable.’ Descriptive statistics were run by using SPSS version 26 (IBM Corp., Armonk, NY), and data are presented in the form of tables and bar graphs.

Results

Out of 18 hospitals, only three (17%) had an acceptable level of preparedness for COVID-19 (>70%). An unacceptable level of preparedness (<35%) was seen in one hospital (5%). Fourteen hospitals (78%) were insufficiently prepared (35-70%).

Conclusion

The study highlights the suboptimal preparedness in 83% of the public hospitals with a consistent pattern of deficiencies in surge capacity, logistics and resource management, essential services, including diagnostics, infection prevention, and control.

Decision-making framework for a resilient sustainable production system during COVID-19: An evidence-based research

This work presents a decision-making framework for integrating resilience and sustainability in managing production systems during COVID-19. An operationalization scheme manifested via a case study at a manufacturer in the food production sector supports the proposed framework. The focus is laid on the tactical and operational decisions within the production system. Through the discussion of the introduced changes to mitigate risks emanating from COVID-19, a set of findings related to the deployment of digital solutions, new dimensions of sustainability and resilience, the introduction of new workforce scheduling rules, the importance of alignment and coordination across supply chain members, and the approach of risk management are identified. This work contributes to a better understanding of the decision-making process during the pandemic and to building up knowledge for the management of resilient and sustainable production systems.

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.

A Bibliometric Analysis on Global Psychological and Behavioral Research Landscape on COVID-19 Pandemic

The COVID-19 pandemic outbreak in December 2019 has spread globally. The ongoing psychological and behavioral effects of the COVID-19 pandemic, which poses a major challenge to humanity, are of concern to researchers. To understand the academic community’s attention, focus and research collaboration on psychological and behavioral research during the COVID-19 pandemic, we conducted a macro analysis using a bibliometric approach. Using the topic selection strategy of TS = (“COVID-19” OR “coronavirus disease 2019” OR “SARS-CoV-2” OR “2019-nCoV”) AND TS = (“behavio*”) AND TS = (“psycholog*”), 2096 high-quality research articles and reviews were downloaded as data from the Web of Science core collection on 16 November 2021. Through analysis and visualization, the following conclusions are drawn in this study: (1) The popularity and importance of psychological and behavioral research under COVID-19 has increased significantly and needs further attention; (2). Related research focuses on eight hotspots, with quarantine, health care workers, the elderly, students, pregnant women, family, consumers, social media and emergency preparedness knowledge as the focus of the research object; and (3) Research collaboration is relatively high at the author, organizational and national levels. However, low-income countries need to get more attention. Furthermore, this article would help researchers make decisions for the research of psychological and behavioral issues under COVID-19 and planning for future prospects to contribute to academic development and applied methodology.

Prioritizing Multidimensional Interdependent Factors Influencing COVID-19 Risk

COVID-19 has significantly affected various industries and domains worldwide. Since such pandemics are considered as rare events, risks associated with pandemics are generally managed through reactive approaches, which involve seeking more information about the severity of the pandemic over time and adopting suitable strategies accordingly. However, policy-makers at a national level must devise proactive strategies to minimize the harmful impacts of such pandemics. In this article, we use a country-level data-set related to humanitarian crises and disasters to explore critical factors influencing COVID-19 related hazard and exposure, vulnerability, lack of coping capacity, and the overall risk for individual countries. The main contribution is to establish the relative importance of multidimensional factors associated with COVID-19 risk in a probabilistic network setting. This study provides unique insights to policy-makers regarding the identification of critical factors influencing COVID-19 risk and their relative importance in a network setting.

COVID-19, Influenza, and Other Acute Respiratory Viral Infections: Etiology, Immunopathogenesis, Diagnosis, and Treatment. Part 2. Other Acute Respiratory Viral Infections

The first part of this paper presented the current knowledge on two very significant respiratory diseases with high pandemic potential, COVID-19 and influenza. The second part reviews other pathogens that cause acute respiratory viral infections, ARVI, including parainfluenza viruses, adenoviruses, pneumoviruses and specifically respiratory syncytial virus, enteroviruses, rhinoviruses, bocaviruses, and seasonal coronaviruses. The review presents modern data on the structure and replication of viruses, epidemiology and immunopathogenesis of diseases, diagnostics, preventive vaccination, and antiviral drugs. Topical issues regarding ARVI vaccination and the search for new broad-spectrum antiviral drugs are discussed.

An Investigation into Art Therapy Aided Health and Well-Being Research: A 75-Year Bibliometric Analysis

Considering the physical, and psychological impacts and challenges brought about the coronavirus disease 2019 (COVID-19), art therapy (AT) provides opportunities to promote human health and well-being. There are few systematic analysis studies in the fields of AT, which can provide content and direction for the potential value and impact of AT. Therefore, this paper aims to critically analyze the published work in the field of AT from the perspective of promoting health and well-being, and provides insights into current research status, hotspots, limitations, and future development trends of AT. This paper adopts a mixed method of quantitative and qualitative analysis including bibliometric analysis and keyword co-occurrence analysis. The results indicate that: (1) the current studies on AT are mostly related to research and therapeutic methods, types of AT, research populations and diseases, and evaluation of therapeutic effect of AT. The research method of AT mainly adopts qualitative research, among which creative arts therapy and group AT are common types of AT, and its main research populations are children, veterans, and adolescents. AT-aided diseases are trauma, depression, psychosis, dementia, and cancer. In addition, the therapeutic methods are mainly related to psychotherapy, drama, music, and dance/movement. Further, computer systems are an important evaluation tool in the research of AT; (2) the future development trend of AT-aided health and well-being based on research hotspots, could be focused on children, schizophrenia, well-being, mental health, palliative care, veterans, and the elderly within the context of addressing COVID-19 challenges; and (3) future AT-aided health and well-being could pay more attention to innovate and integrate the therapeutic methods of behavior, movement, and technology, such as virtual reality and remote supervision.

Critical appraisal of clinical practice guidelines for the management of COVID-19: protocol for a systematic review

BACKGROUND

In December 2019, a novel coronavirus, severe acute respiratory syndrome coronavirus 2 was identified as the cause of an acute respiratory disease, coronavirus disease 2019 (COVID-19). Given the lack of validated treatments, there is an urgent need for a high-quality management of COVID-19. Clinical practice guidelines (CPGs) are one tool that healthcare providers may use to enhance patient care. As such, it is necessary that they have access to high-quality evidence-based CPGs upon which they may base decisions regarding the management and use of therapeutic interventions (TI) for COVID-19. The purpose of the proposed study is to assess the quality of CPGs that make management or TI recommendations for COVID-19 using the AGREE II instrument.

METHODS

The proposed systematic review will identify CPGs for TI use and/or the management of COVID-19. The MEDLINE, EMBASE, CINAHL, and Web of Science databases, as well as the Guidelines International Network, National Institute for Health and Clinical Excellence, Scottish Intercollegiate Guidelines Network, and the World Health Organization websites, will be searched from December 2019 onwards. The primary outcome of this study is the assessed quality of the CPGs. The quality of eligible CPGs will be assessed using the Appraisal of Guidelines, Research and Evaluation II (AGREE II) instrument. Descriptive statistics will be used to quantify the quality of the CPGs. The secondary outcomes of this study are the types of management and/or TI recommendations made. Inconsistent and duplicate TI and/or management recommendations made between CPGs will be compared across guidelines. To summarize and explain the findings related to the included CPGs, a narrative synthesis will also be provided.

DISCUSSION

The results of this study will be of utmost importance to enhancing clinical decision-making among healthcare providers caring for patients with COVID-19. Moreover, the results of this study will be relevant to guideline developers in the creation of CPGs or improvement of existing ones, researchers who want to identify gaps in knowledge, and policy-makers looking to encourage and endorse the adoption of CPGs into clinical practice. The results of this review will be published in a peer-reviewed journal and presented at conferences.

SYSTEMATIC REVIEW REGISTRATION

International Prospective Register for Systematic Reviews (PROSPERO)- CRD42020219944.

Forecasting the spread of the third wave of COVID-19 pandemic using time series analysis in Bangladesh

During the third wave of the coronavirus epidemic in Bangladesh, the death and infection rate due to this devastating virus has increased dramatically. The rapid spread of the virus is one of the reasons for this terrible condition. So, identifying the subsequent cases of coronavirus can be a great tool to reduce the mortality and infection rate. In this article, we used the autoregressive integrated moving average-ARIMA(8,1,7) model to estimate the expected daily number of COVID-19 cases in Bangladesh based on the data from April 20, 2021, to July 4, 2021. The ARIMA model showed the best results among the five executed models over Autoregressive Model (AR), Moving Average (MA), Autoregressive Moving Average (ARMA), and Rolling Forest Origin. The findings of this article were used to anticipate a rise in daily cases for the next month in Bangladesh, which can help governments plan policies to prevent the spread of the virus. The forecasting outcome indicated that this new trend(named delta variant) in Bangladesh would continue increasing and might reach 18327 daily new cases within four weeks if strict rules and regulations are not applied to control the spread of COVID-19.

Assessment of COVID-19 induced travel pattern changes in Dhaka City

In response to Coronavirus 2019 (COVID-19) pandemic, Bangladesh enforced social distancing measures to mitigate the virus transmission rate through lockdowns. However, it is challenging for people to follow through and stay home in developing nations where socio-economic conditions are divergent from developed countries. This research aims to investigate COVID-19 induced travel pattern changes of residents and significant demographic factors affecting the trip generation in Dhaka City, the most densely populated Bangladeshi city. A questionnaire survey was used to extract information on demographic characteristics of respondents in Dhaka City and their travel patterns in the pre-pandemic era and during the pandemic. Analyses reveal striking differences in work trips except for workers and craftsmen. The use of telemedicine facilities is noticeable. Preference for public transport has decreased yet a decent percentage (9%) of people use buses during the pandemic. However, non-motorized modes are also very popular (19.93%) in the pandemic. The findings offer major implications for transportation planners and policymakers on how to dynamically plan for such crisis by combining a range of strategies so that safe and sustainable urban mobility and reduction of unnecessary travel demand can be ensured.

Quality of early evidence on the pathogenesis, diagnosis, prognosis and treatment of COVID-19

Since the initial description of the SARS-CoV-2 outbreak and its declaration as a worldwide pandemic, the number of publications on the novel virus has increased rapidly. We studied the trends and quality of evidence in early SARS-CoV-2 publications. A comprehensive search of MEDLINE and EMBASE was performed for papers published between 1 January 2020 and 21 April 2020. Two reviewers independently screened titles and abstracts and subsequently full texts for eligibility in this systematic review. The search yielded 2504 citations published between January and February 2020 or an unspecified date, 109 of which remained for extraction after screening. Data extracted included study design, year of publication, country of basis, journal of publication, impact factor of publishing journal, study sample size, number of citations and topic of investigation. Study design-specific critical appraisal tools were used to evaluate the scientific rigour of all included papers: the Joanna Briggs Institute checklist was used for case series, Scale for the Assessment of Narrative Review Articles scale for narrative reviews, Newcastle-Ottawa scale for cohort studies and AMSTAR 2 for systematic reviews. The overall quality of the literature was low-moderate. Of 541 papers that reported clinical characteristics, 295 were commentaries/expert opinions and 36 were case reports. There were no randomised clinical trials, 45 case series studies, 58 narrative reviews, 1 cohort study and 5 systematic reviews. We encourage clinicians to be attentive to these findings when utilising early SARS-CoV-2 evidence in their practices.