Why can’t some scientists just admit they were wrong about Covid? | Devi Sridhar

As Britain slowly emerges from the pandemic, after two bruising years, Covid camps are one of the lasting legacies. What I mean by Covid camps are people or groups with particular pandemic positions taken early on that they then continually reinforce by selectively sourcing information, eventually building a base of followers that organise around that position and defend it viciously.

It’s unsurprising: similar camps developed around Brexit and other key issues. However, the emergence of scientists also dividing themselves into camps over Covid is more novel.

These camps include those who have always compared Covid to seasonal flu and advocated a “let it rip” approach; those who have argued for maximum suppression (and still do); and those who have changed their stance based on emerging data, including around vaccines and variants. There are also camps for those who have always been against masks, noting the lack of evidence over effectiveness; those who have argued for masks regardless of age and context; and those who analyse their cost and benefit in different situations and age groups.

The essence of science is asking questions, forming hypotheses for possible answers, and then revising these based on new data. Covid has been a constantly changing situation. One only has to look at the emergence of variants and how policy response had to modify with a steep rise in Delta cases – which was more severe than the original Sars-CoV-2 – and then again with Omicron (which is milder than previous variants). There were also early hypotheses suggesting that many people may have prior immunity from other coronaviruses against Sars-CoV-2.

The pandemic has been like seeing something coming through the fog – but being unsure of the contours or exact characteristics of what was approaching. Humility and flexibility in responding were two hallmarks of effective policy response. For example, delaying infections through pursuing maximum suppression or a zero-Covid response were optimal in a pre-vaccine, pre-antiviral era. Every infection averted was giving someone a chance to have access to scientific tools – and live many more healthy years of life. Early in the pandemic we also didn’t understand the full impact of the virus and so had to take a more cautious approach.

“Living with Covid”, now that science has largely defanged it, involves ensuring widespread vaccination, as well as creating schemes such as the US government’s “test to treat”. The latter involves Americans going to pharmacies to get tested for Covid and if positive, immediately receiving antivirals on the spot, free of charge. Testing, treatments and vaccines mean that governments can find their “exit” from the pandemic and manage Covid as another one of the many infectious diseases they have to deal with.

But instead of evolving their position based on new data, some, instead, keep trying to show how they were still right in early 2020, digging themselves an even deeper hole. A case in point is Stanford professor John Ioannidis, who, in March 2020, argued that governments were overreacting to the threat of Covid. He mocked those who worried that the “68 deaths from Covid-19 in the US as of 16 March will increase exponentially to 680, 6,800, 68,000, 680,000”. He estimated that the US might suffer only 10,000 deaths. He also was cynical that vaccines or treatments could be developed in any timeframe that would affect the trajectory of the pandemic.

Two years later, the current US death toll stands at 969,000, with almost 250,000 of those being people under 65. These numbers would have once been seen as outlandish. In addition, in less than a year we had developed safe and effective vaccines – and a year after that, safe and effective antivirals. One would expect these facts to prompt an academic to reconsider their initial assumptions – but instead, Ioannidis has continued to publish articles solidifying his starting position.

Why is this the case? Why can’t academics just admit that they might have got their assumptions wrong at the start, or reassess their positions? I think it’s a mix of playing to a fanbase that has formed over two years (in this case, an anti-lockdown, “Covid-as-flu” base), and the idea that moving with new data is a sign of backtracking and weakness, instead of the basic scientific virtue of reflection and re-analysis. The overall need is to be proven “right” for oneself and a small group of followers, rather than right for society.

Governments (and the public) have expected scientists to be oracles who can predict the future – and have put them in the spotlight in a previously unusual way. Social and mainstream media have amplified extreme positions – for the sake of debate and the impulse to show “two sides” – instead of trying to find a sensible middle ground. The move in society and workplaces towards largely virtual communication during the pandemic has made this polarisation even worse, with so many primarily communicating via Zoom and social media platforms. In this way, extreme positions have received disproportionate exposure in comparison to the “silent majority” who seem to understand the complexity of the situation – and the need to rely on expertise grounded in data.

I have respect and admiration for scientists who have admitted what they got wrong, and also understand that each stage of the pandemic has required a different response, based on the latest data, tools and analysis.

“Experts” and influential people stuck in these Covid camps continue to influence the narrative. In some ways, this keeps us stuck reliving and relitigating arguments from early in the pandemic at the very moment we should be focused on the best evidence and policies to help us “exit” the pandemic safely. This should involve the equitable distribution of vaccines and therapeutics around the globe, protecting those vulnerable to severe disease and rapid-response public health plans based around surveillance. In these moments it’s important to remember the two principles of humility and flexibility in response – and how these don’t fit easily with the new world of media.

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