Published research on COVID-19 since January 2020 has reached more than 23,000 papers and is doubling every 20 days, making it one of the biggest explosions of scientific literature ever.
By Health Analytics Asia
As researchers across the world try to understand COVID-19 – its epidemiology, structure, economic and political consequences, development of vaccines, antibodies and treatments, Avinash Dixit from the Princeton University recently made an interesting observation: If any pandemic spreads faster than COVID-19, it is that of research about COVID-19.
By the author’s own admission, the paper was written: “because at times like this we could all do with a laugh.” It is based on a random sample of 10 papers from the first three pages of results on a search for COVID-19 on Google Scholar search. “For each, I recorded the number N of citations it had attracted to the date (May 18), and the number M of references listed in the paper. I attributed the citations to all the references plus the paper itself, so the calculated rate of “infection” R equals N/ (M+1). Averaging this over the data sample, the estimate of R0 for the COViD-19- research pandemic is 34.”
Too much of a good thing?
According to ScienceMag.org, by one estimate, the COVID-19 literature published since January 2020 has reached more than 23,000 papers and is doubling every 20 days, making it one of the biggest explosions of scientific literature ever.
With COVID-19, there has been an infodemic. In other words, an over-abundance of information. With numerous research papers being published, it has led to growing confusion. The latest controversy was about a dubious study published in The Lancet that led to pause in research on the use of hydroxychloroquine for the treatment of COVID-19.
The World Health Organisation (WHO) announced that it had temporarily suspended its trial of the antimalarial drug to combat the deadly coronavirus over safety concerns. The suspension spurred French drugmaker Sanofi and others to temporarily halt recruitment for their own trials of the drug. In no time, the governments of France, Italy, and Belgium halted the use of hydroxychloroquine for COVID-19 patients.
It was later discovered that The Lancet study published last month has used hospital records procured by a little-known data analytics company called Surgisphere to conclude that coronavirus patients taking chloroquine or hydroxychloroquine were more likely to show an irregular heart rhythm – a known side-effect thought to be rare – and were more likely to die in the hospital.
Nearly 150 doctors signed an open letter to The Lancet calling the article’s conclusions into question and asking to make public the peer review comments that preceded publication. Soon, WHO resumed its trial of hydroxychloroquine, after the Data Safety Monitoring Board decided that there was no reason to discontinue the international trial after reviewing available data on the drug.
To tame the flood of papers, many teams are turning to advanced computational tools, says an insightful report in ScienceMag.org. The White House, for instance, has asked data scientists to develop tools to analyse the data set, in a bid to help researchers answer 10 high-priority, pandemic-related research questions identified by the U.S. National Academy of Sciences and the WHO.
