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Using science mapping analysis approach and co-word analysis, the present study explores and visualizes research fields and thematic evolution of the coronavirus. Based on this method, one can get a picture of the real content of the themes in the mentioned thematic area and identify the main minor and emerging themes.

This study was conducted based on co-word science mapping analysis under a longitudinal study (from 1988 to 2020). The collection of documents in this study was further divided into three subperiods: 1988–1998, 1999–2009 and 2010–2020. In order to perform science mapping analysis based on co-word bibliographic networks, SciMAT was utilized as a bibliometric tool. Moreover, WoS, PubMed and Scopus bibliographic databases were used to download all records.

In this study, strategic diagrams were demonstrated for the coronavirus research for a chronological period to assess the most relevant themes. Each diagram depended on the sum of documents linked to each research topic. In the first period (1988–1998), the most centralizations were on virology and evaluation of coronavirus structure and its structural and nonstructural proteins. In the second period (1999–2009), with due attention to high population density in eastern Asia and the increasing number of people affected with the new generation of coronavirus (named severe acute respiratory syndrome virus or SARS virus), publications have been concentrated on “antiviral activity.” In the third period (2010–2020), there was a tendency to investigate clinical syndromes, and most of the publications and citations were about hot topics like “severe acute respiratory syndrome,” “coronavirus” and “respiratory tract disease.” Scientometric analysis of the field of coronavirus can be regarded as a roadmap for future research and policymaking in this important area.

The originality of this research can be considered in two ways. First, the strategic diagrams of coronavirus are drawn in four thematic areas including motor cluster, basic and transversal cluster, highly developed cluster and emerging and declining cluster. Second, COVID-19 is mentioned as a hot topic of research.

The present article's primary purpose is the topic modeling of the global coronavirus publications in the last 50 years.

The present study is applied research that has been conducted using text mining. The statistical population is the coronavirus publications that have been collected from the Web of Science Core Collection (1970–2020). The main keywords were extracted from the Medical Subject Heading browser to design the search strategy. Latent Dirichlet allocation and Python programming language were applied to analyze the data and implement the text mining algorithms of topic modeling.

The findings indicated that the SARS, science, protein, MERS, veterinary, cell, human, RNA, medicine and virology are the most important keywords in the global coronavirus publications. Also, eight important topics were identified in the global coronavirus publications by implementing the topic modeling algorithm. The highest number of publications were respectively on the following topics: “structure and proteomics,” “Cell signaling and immune response,” “clinical presentation and detection,” “Gene sequence and genomics,” “Diagnosis tests,” “vaccine and immune response and outbreak,” “Epidemiology and Transmission” and “gastrointestinal tissue.”

The originality of this article can be considered in three ways. First, text mining and Latent Dirichlet allocation were applied to analyzing coronavirus literature for the first time. Second, coronavirus is mentioned as a hot topic of research. Finally, in addition to the retrospective approaches to 50 years of data collection and analysis, the results can be exploited with prospective approaches to strategic planning and macro-policymaking.

Signs saturate and surround society. This article illuminates the significant roles played by documentation within the context of the coronavirus pandemic. It centres, what it terms as, “COVID-19 signage” as essential extensions of nonpharmaceutical interventions (NPIs) into society. It posits that this signage helps materialize, mediate and articulate the pandemic from an unseen phenomenon into tangible objects with which people see and interact.

This article presents a documentary typology of COVID-19 signage to provide a conceptual framework in which to situate, approach and analyse this diverse documentation and its implications for social life and traffic. Further, this article offers a case study of Malta's COVID-19 signage that helped materialize, mediate and articulate the pandemic across the European island nation during its national lockdown in the first half of 2020. This case study helps contextualize these signs and serves as a dual contemporary and historical overview of their creation, implementation and use.

The coronavirus pandemic cannot be seen with the naked eye. It is, in many respects, an abstraction. Documents enable the virus to be seen and the pandemic to be an experienced reality. Specifically, COVID-19 signage materializes the disease and pandemic into tangible items that individuals interact with and see on a daily basis as they navigate society. From personal to environmental to community signs, these documents have come to mediate social life and articulate COVID-19 during this extraordinary health crisis. A material basis of a shared “pandemic social culture” is consequently established by and through this signage and its ubiquity.

This article can serve as a point of departure for analyses of other kinds of COVID-19 signage in various contexts. It can serve as an anchor or example for other investigations into what other signs were used, including why, when and how they were produced, designed, formatted, implemented, enforced, altered and/or removed. For instance, it could be used for comparative studies between different NPIs and their associated signage, or of the signage appearing between different cities or countries or even the differences in signage at various political and socio-temporal points of the pandemic.

It is dually hoped that this article's documentary typology, and historical snapshot, of COVID-19 signage could help inform how current and future NPIs into society are or can be used to mitigate the coronavirus or other potential health crises as well as serve as both a contemporary and historical snapshot of some of the immediate and early responses to the pandemic.

This documentary typology can be applied to approaches and analyses of other kinds of COVID-19 signage and related documentation. By serving as a conceptual framework in which situate, approach and analyse these documents, it is hoped that this article can help create a sense of clarity in reflections on sign-saturated environments as well as be practically employed for examining and understanding the effective implementation of NPIs in this pandemic and other health crises.

This paper aims to examine the impact of health and other exogenous shocks on stock markets in Africa. Particularly, the authors examined the resilience of the major stock markets in 12 African economies during the recent global pandemic.

This paper uses the recent panel vector autoregressive model, which enables us to capture the response of stock markets to shocks in COVID-19, commodity markets and exchange rate. For robustness, the authors also analysed the panel Granger causality test. Data was obtained for the period ranging from 2 January 2020 to 31 December 2020.

The results show that the growth in COVID-19 cases and deaths do not have any substantial impact on the stock market returns of these economies. In terms of commodity markets, the authors find that gold price has a negative contemporaneous effect on stock returns, but the effect fizzles out around the fifth day while crude oil price, on the other hand, has a significant positive simult aneous impact on stock returns and also converges around the fifth day. The authors further find that the exchange rate has a contemporaneous and nonlinear effect on stock returns and seems to be more dramatic when compared with the other variables. Overall, the results show that stock markets in Africa appear to be flexible and resilient against the COVID-19 outbreak but are affected by other exogenous shocks such as volatile commodity prices and the foreign exchange market. The effect is, however, short-lived – between one to five days.

Following the study’s findings, policies should be put in place to support financial markets by way of hedging against commodity instability and securing domestic currency financing. Policymakers are also recommended to concentrate on managing the uncertainties around their exchange rate markets and develop robust and efficient domestic financial markets to encourage local and foreign investors.

Several studies have been carried out on the effects of disasters (such as the COVID-19 pandemic) on stock markets, but only a few studies have examined the resilience of stock markets to health and other exogenous shocks. This study’s attempt is not only to examine the impact of COVID-19 health shocks on stock markets but also to analyse the resilience of the sampled stock markets. The authors also analyse the resilience of stock markets to commodity markets and exchange rates shocks.

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

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

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

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

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

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

The purpose of this study to investigate the effects and possible future prediction of COVID-19. The dataset considered in this study to investigate the effects and possible future prediction of COVID-19 is constrained as follows: age, gender, systolic blood pressure, HDL-cholesterol, diabetes and its medication, does the patient suffered from heart disease or took anti-cough agent food or sensitive to cough related issues and any other chronic kidney disease, physical contact with foreign returns and social distance for the prediction of the risk of COVID-19.

This work implemented a meta-heuristic algorithm on the aforementioned dataset for possible analysis of the risk of being infected with COVID-19. The authors proposed a simple yet effective Risk Prediction through Nature Inspired Hybrid Particle Swarm Optimization and Sine Cosine Algorithm (HPSOSCA), particle swarm optimization (PSO), and sine cosine algorithm (SCA) algorithms.

The simulated results on different cases discussed in the dataset section reveal which category of individuals may happen to have the disease and of what level. The experimental results reveal that the proposed model can predict the percentage of risk with an overall accuracy of 88.63%, sensitivity (87.23%), specificity (89.02%), precision (69.49%), recall (87.23%), f_measure (77.36%) and Gmean (88.12%) with 41 and 146 true positive and negative, 18 and 6 false positive and negative cases, respectively. The proposed model provides a quite stable prediction of risk for COVID-19 on different categories of individuals.

The work for the very first time developed a novel HPSOSCA model based on PSO and SCA for the prediction of COVID-19 disease. The convergence rate of the proposed model is too high as compared to the literature. It also produces a better accuracy in a computationally efficient fashion. The obtained outputs are as follows: accuracy (88.63%), sensitivity (87.23%), specificity (89.02%), precision (69.49%), recall (87.23%), f_measure (77.36%), Gmean (88.12%), Tp (41), Tn (146), Fb (18) and Fn (06). The recommendations to reduce disease outbreaks are as follow: to control this epidemic in various regions, it is important to appropriately manage patients suspected of having the disease, immediately identify and isolate the source of infection, cut off the transmission route and prevent viral transmission from these potential patients or virus carriers.

This study examines the economic crisis caused by coronavirus on the global tourism industry in general and the Indian tourism industry in particular. This paper highlights the strategies that tourism companies should implement in times of crisis to reduce the negative impact. It also discovers the business opportunities which can be offered amid this deadly pandemic.

The study is based on a systematic literature review. The literature has been explored by utilizing the keywords “economic crises,” “coronavirus,” “Indian tourism industry,” “Global tourism industry” on the three most popular databases namely Scopus, Web of Science and Google Scholar. In this study, statistics, current events, published research papers and a synthesis of news transmitted by various media sources were used to assess the economic crisis caused by coronavirus.

The obtained findings demonstrate that coronavirus severely affected the economy of the world and India. The pandemic has hit the economies that are dependent on tourism the worst. These countries are expected to bear the brunt of the crisis's consequences for longer than other economies. This coronavirus outbreak indicates that the tourism industry was unprepared to deal with such a pandemic, which affected and crippled the economy.

This study demonstrates economic crisis, management strategies and business opportunities during any crisis, chaos and disaster, in addition to its academic contribution to the existing body of the literature. Policymakers and industry practitioners might be offered suggestions based on the findings of current study to design futuristic strategies for better economic crisis management. The data given in this study is timely because taking an exact idea of tourism losses through the data is difficult, as the data changes as quickly as the virus spreads.

This paper forms its originality by concentrating on the aspects of economic crisis, strategies to mitigate the negative impact of coronavirus on the tourism economy and detailing the business opportunities which these crises can offer. This paper provides an evaluation of the current status of the tourism economy of the world and India as well.

This paper analyses the COVID-19 situation in Nigeria, its effect on the economy and the structural causes that worsened the coronavirus (COVID-19) crisis.

This paper uses simple descriptive analysis to examine the COVID-19 situation in Nigeria.

The findings reveal that the economic downturn in Nigeria was triggered by a combination of declining oil price and spillovers from the COVID-19 outbreak, which not only led to a fall in the demand for oil products but also stopped economic activities from taking place when social distancing policies were enforced. The government responded to the crisis by providing financial assistance to businesses and a small number of households that were affected by the coronavirus (COVID-19) outbreak. The monetary authority adopted accommodative monetary policies and offered a targeted 3.5 trillion loan support to some sectors. These efforts should have prevented the economic crisis from occurring but it did not. Economic agents could not freely engage in economic activities for fear of contracting the COVID-19 disease that was spreading very fast at the time.

The implication of the study is that policymakers should pay attention to three areas of the economy for economic and structural reform. One, policymakers should introduce economic reforms to diversify the economy and reduce Nigeria's dependence on revenue from crude oil export. Two, policymakers in Nigeria should invest in healthcare infrastructure to improve the ability of the national health system to withstand the outbreak of contagious diseases. Three, there is also a need to build appropriate digital infrastructure to facilitate the transition from “face-to-face” business activities to a “digital or online” business activities, which can help to grow the digital economy. Also, policymakers should use legislation to create a robust social welfare safety net for all citizens particularly for unemployed citizens and poor households.

This is the first paper that looks at the economic implication of COVID-19 in a West African country.

The aim of this study is a semantic comparative analysis between the current pandemic and the Spanish flu. It is based on a bilingual terminological perspective oriented to evaluate and compare the terms used to describe and communicate the pandemic's issues both to biomedical experts and to a non-specialist public.

The analysis carried out is a terminological comparative investigation performed on two corpora, the first containing scientific English articles, the second Italian national newspapers' issues on two pandemics, the Spanish flu and the current Covid-19 disease, towards the detection of semantic similarities and differences among them through the implementation of computational tasks and corpus linguistics methodologies.

Given the cross-fielding representativeness of terms, and their relevance within specific historical eras, our study is conducted both on a synchronic and on a diachronic level to discover the common lexical usages in the dissemination of the pandemic issues.

The study presents the extraction of the main representative terms about two pandemics and their usages to share news about their trends among the population and the integration of a topic modeling detection procedure to discover some of the main categories representing the lexicon of the pandemics with reference to a list of classes created by external thesauri and ontologies on pandemics. As a result, a detailed overview of the discrepancies, as well as similarities, retrieved in two historical corpora dealing with a common subject, i.e. the pandemics' terminology, is provided.

Health-related online fake news (HOFN) has become a major social problem. HOFN can lead to the spread of ineffective and even harmful remedies. The study aims to understand Internet users' responses to HOFN during the coronavirus (COVID-19) pandemic using the protective action decision model (PADM).

The authors collected pandemic severity data (regional number of confirmed cases) from government websites of the USA and China (Studies 1 and 2), search behavior from Google and Baidu search engines (Studies 1 and 2) and data regarding trust in two online fake news stories from two national surveys (Studies 2 and 3). All data were analyzed using a multi-level linear model.

The research detected negative time-lagged relationships between pandemic severity and regional HOFN search behavior by three actual fake news stories from the USA and China (Study 1). Importantly, trust in HOFN served as a mediator in the time-lagged relationship between pandemic severity and search behavior (Study 2). Additionally, the relationship between pandemic severity and trust in HOFN varied according to individuals' perceived control (Study 3).

The authors' results underscore the important role of PADM in understanding Internet users' trust in and search for HOFN. When people trust HOFN, they may seek more information to implement further protective actions. Importantly, it appears that trust in HOFN varies with environmental cues (regional pandemic severity) and with individuals' perceived control, providing insight into developing coping strategies during a pandemic.