What is it about?

- Bibliometric analysis of scientific literature – analysing a ‘snapshot in time’ of the first wave of COVID-19. - 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. With the global focus on the pandemic, the data records are changing dramatically. Since research data records are often categorised by year and not by months, it could be challenging for researchers to find scientific data and to model, with precision, the research response at different stages of the pandemic.

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Why is it important?

Our objectives are to use computable statistical methods, to conduct bibliometric data mining on scientific research records and to answer some emerging questions on COVID-19. In the study, we investigate: 1. What country produced the most research papers on Covid-19 since the pandemic started? 2. What universities and companies are publishing research on Covid-19? 3. Which countries/universities collaborated most in research papers on Covid-19? After identifying the answers to these research questions, we focus on a new set of research questions: 4. What country produced the most research papers on pandemic and epidemics from 1900 to 2020? 5. What universities and companies have published most research on pandemic and epidemics from 1900 to 2020? 6. Which countries/universities collaborated most in research papers on pandemic and epidemics from 1900 to 2020? We use a variety of statistical methods (e.g. three-fields plot, factorial analyse, historical analysis, network map analysis, etc.) to compare the findings from these questions.


- As the scientific research on COVID-19 continues to expand, the publications are becoming more fragmented, which creates challenges in navigating through the accumulation of new knowledge - on global pandemics. - We found individual tools being restrictive, and we propose a multi-tool approach that enables faster results from statistical and graphical packages, aligned to bibliographical databases. - With the use of these statistical methods, we presented visualisations of the research connections between areas and countries, on the emerging patterns from national responses, and we provide scientific insights on the speed of response. - Our aim was to provide statistical ‘snapshot in time’, and to assist other researchers to reassess the response in the initial stages of the pandemic and prepare for future global pandemics. In the end, we have seen that organisations that were preparing for a Disease X event, produced the most output. But during the first wave, most of the output was produced by organisations and institutes that had access to data on the Covid-19 pandemic. This brings into question the value of sharing medical data (at speed and low latency) in preventing and managing future Disease X events.

Dr Petar Radanliev
University of Oxford

Read the Original

This page is a summary of: What Country, University, or Research Institute, Performed the Best on Covid-19 During the First Wave of the Pandemic?, Annals of Data Science, June 2022, Springer Science + Business Media,
DOI: 10.1007/s40745-022-00406-8.
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