The speed of the news cycle around the Covid-19 pandemic is not slowing down. Just last week, the UK announced that the alarming mark of 200,000 virus-related deaths had been reached. And as the current wave of infections, fueled largely by the Omicron BA.5 strain, begins to subside, fears are mounting that another, more virulent strain of Sars-CoV-2 may be at hand, in the form of BA.2.75.
There is perhaps no example of a scientific issue that has captured the public’s attention to such an extent – and for so long. In fact, a large part of all articles published in the last two years have been devoted to this epidemic. It’s also one of the most discussed topics on social media, with people from all walks of life participating in passionate, if sometimes venomous, debates about the correct meaning of the latest scientific publication.
The great interest shown by the public in the science of Covid-19 is one of the weakest aspects of this epidemic. However, the continuous, slow progress of science, by repeating, or on the other hand, contradicting the first findings, is put under severe pressure. Many people find it difficult to accept that a published finding may be false. The scientific method of preparation is also unable to adapt to the life conditions of news broadcasting.
Before an article is read, digested and dissected by experts in the field, it has often been widely published in the news and shared by millions of people on social media. And the publications that attract the most attention are often those that report unexpected, extreme results, which may also be negative findings.
Just look at the staggering number of Covid articles written. There are now about 5 million publications on Covid recorded in the Google Scholar database. There is a scientific article to support any conceivable claim and report about Covid-19, however absurd or unattainable. This allows anyone to make the most amazing claims and back them up with published scientific evidence, which is a serious problem for productive discussions on social media.
This also means that the Covid-19 news cycle and social media are fueled by a combination of scientific facts, inaccuracies and misunderstandings, as well as scientific assumptions that often do not work out. to extensive evidence. A common misunderstanding is that “science” is a body of absolute, immutable, irrefutable and verifiable facts. On the contrary, science is a messy process that eventually turns to reality through trial and error.
Many scientific articles are wrong – because they were based on insufficient data or analysis, but often the results are simply false, assuming a significant statistical association is not appropriate. In fact, every time a statistical test is performed, there is a small chance that it will pick up a sample even if it doesn’t exist. Such false positives are more likely to occur in studies with smaller samples, as those are inherently noisier.
The problem is exacerbated because studies reporting positive results are more likely to be documented and published. (Those that fail to detect a statistical effect often remain unpublished.) Articles reporting negative results are also very common among early studies, a pattern known as the “winner’s curse”.
There have been several instances during the pandemic where early studies showed results that could not be replicated by other, often larger, studies. One example was the antibiotic ivermectin. Several preliminary studies on a small number of patients have reported promising results, leading many to believe that it is a miracle cure for Covid-19. It was only once data from large clinical trials became available that ivermectin could be confidently excluded as an effective antiviral drug.
Recently, a preliminary publication reported that the latest circulating generations of Omicron (BA.1.12, BA.4 and BA.5) may return to a virulence level comparable to previous strains. of Delta, mainly on the basis of experimental infection in hamsters. Those first results caused a lot of panic but were not replicated in other hamster experiments. They also disagreed with much of the real-world evidence from many countries that did not show an increase in hospitalizations or death rates for infections caused by current problems.
Among the many types of doomsday for Covid-19 that have been predicted on the basis of preliminary and limited evidence, few have swept the world. Although some did: both the Alpha and Delta variants were more transmissible and associated with higher rates of hospitalization and death than any other pre-existing gene. see. And the Omicron brand has spread around the world very quickly, mainly because it could bypass the existing human protection provided by vaccines and initial infection, but fortunately, its depth is much lower being the generations of the first epidemic and any subsequent variation.
The truth is that it is still difficult to predict what the next Sars-CoV-2 will spread around the world will look like. BA.2.75 might be it, though it’s possible that it might come out. This great uncertainty, combined with the high level of predictability of the next Sars-CoV-2 strain, makes it difficult to find the right balance between public awareness and encouragement.
There is no easy solution to these problems. Despite the great efforts of the scientific community during this pandemic, we have not been able to fully address the fact that science is a slow and adaptive process by nature. I don’t blame the public – it’s understandable that they, the media and policy makers all want certainty and confidence, but this is not something that science can generally provide.
A society in which science is done openly, with commitment from, and under the eyes of the public, is actually an educated, fair, democratic society. Although one point that we scientists have failed to convey to the public during this epidemic is that science is more about dealing with uncertainty than providing unchanging, absolute truths.
One cannot “follow science”. The best you can hope to achieve is for science to tend to the truth, even if that process can be difficult and sometimes wrong.
Francois Balloux is director of the Center for Genetics at University College London
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