Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/42178
metadata.artigo.dc.title: Data mining and analysis of scientific research data records on Covid-19 mortality, immunity, and vaccine development: in the first wave of the Covid-19 pandemic
metadata.artigo.dc.creator: Radanliev, Petar
De Roure, David
Walton, Rob
metadata.artigo.dc.subject: Covid-19
Mortality
Immunity
Vaccine
Computable statistical analysis
Data mining
metadata.artigo.dc.publisher: Elsevier
metadata.artigo.dc.date.issued: 2020
metadata.artigo.dc.identifier.citation: RADANLIEV, P.; DE ROURE, D.; WALTON, R. Data mining and analysis of scientific research data records on Covid-19 mortality, immunity, and vaccine development: in the first wave of the Covid-19 pandemic. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, [S.l.], v. 14, n. 5, p. 1121-1132, Sept./Oct. 2020.
metadata.artigo.dc.description.abstract: Background and aims Covid-19 is a global pandemic that requires a global and integrated response of all national medical and healthcare systems. Covid-19 exposed the need for timely response and data sharing on fast spreading global pandemics. In this study, we investigate the scientific research response from the early stages of the pandemic, and we review key findings on how the early warning systems developed in previous epidemics responded to contain the virus. Methods We conducted data mining of scientific literature records from the Web of Science Core Collection, using the topics Covid-19, mortality, immunity, and vaccine. The individual records are analysed in isolation, and the analysis is compared with records on all Covid-19 research topics combined. The data records are analysed with commutable statistical methods, including R Studio’s Bibliometrix package, and the Web of Science data mining tool. Results From historical analysis of scientific data records on viruses, pandemics and mortality, we identified that Chinese universities have not been leading on these topics historically. However, during the early stages of the Covid-19 pandemic, the Chinese universities are strongly dominating the research on these topics. Despite the current political and trade disputes, we found strong collaboration in Covid-19 research between the US and China. From the analysis on Covid-19 and immunity, we wanted to identify the relationship between different risk factors discussed in the news media. We identified a few clusters, containing references to exercise, inflammation, smoking, obesity and many additional factors. From the analysis on Covid-19 and vaccine, we discovered that although the USA is leading in volume of scientific research on Covid-19 vaccine, the leading 3 research institutions (Fudan, Melbourne, Oxford) are not based in the USA. Hence, it is difficult to predict which country would be first to produce a Covid-19 vaccine. Conclusions We analysed the conceptual structure maps with factorial analysis and multiple correspondence analysis (MCA), and identified multiple relationships between keywords, synonyms and concepts, related to Covid-19 mortality, immunity, and vaccine development. We present integrated and corelated knowledge from 276 records on Covid-19 and mortality, 71 records on Covid-19 and immunity, and 189 records on Covid-19 vaccine.
metadata.artigo.dc.identifier.uri: https://www.sciencedirect.com/science/article/pii/S1871402120302332
http://repositorio.ufla.br/jspui/handle/1/42178
metadata.artigo.dc.language: en_US
Appears in Collections:FCS - Artigos sobre Coronavirus Disease 2019 (COVID-19)

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