Game Over for Marion (translated from X)

For those who are not on X.

Jay Bhattacharya:

Is it just me, or are all the senior @WHO officials and scientists who forced the world into lockdown in 2020 now flat out claiming they never recommended a lockdown? In any case, I have no confidence that they wouldn't recommend the world go back into lockdown if given the chance.

Marion Koopmans:

I'm going to try this once. I watch your inflammatory tweets with amazement. You're probably putting me in the box of those in favor of lockdowns. I wonder if you have ever had an advisory role in a public health crisis, on a hospital outbreak management team or as an employer responsible for health protection.

Let me explain how this works: there is a developing crisis, with a lot of uncertainty, but with a looming risk of serious consequences. This means that there is an immediate and urgent need for detailed data on the evolving situation. Let's start there: Outbreaks usually start chaotically, especially when it comes to a new disease: you can't diagnose it yet, you don't know how big the spread is, you don't know who is at risk, who is contributing to the spread, etc.

Modeling is already starting, based on bits and pieces of information shared by countries/health experts. And that is rarely a perfectly designed episode study with a complete, in-depth laboratory evaluation. So you have to work with what comes in, assess its quality and compare it with experiences from similar outbreaks. COVID-19 seemed to start quite slowly and was perhaps initially a little more similar to SARS than what it ultimately turned out to be, namely clearly more contagious (note that the first variant already emerged when the virus emerged from Asia, so the data collected up to that point would underestimate its transmissibility, as the original virus was less transmissible). What then developed was a rapidly progressing disease outbreak with features that put great strain on public health, healthcare and society and required difficult decisions.

With a higher mortality rate, things are simpler, or at least more priority can be given to the importance of protecting oneself and others from infection. With a virus that appeared to have a fairly high mortality rate compared to seasonal respiratory viruses, and an immunologically naive population, one could see the impact: a large number of cases with a low complication rate can still lead to mass morbidity, mortality and overburdened healthcare systems. Of course, the impact on healthcare depended a lot on how much was invested in healthcare, so then – in public health and in infection prevention programs in hospitals/long-term care – you looked at what could be done to limit that impact. Both by looking at what drives transmission and what can be done to protect the most vulnerable.

To pretend that this was not a challenge is a gross oversimplification of the outbreak response and management of the pandemic. In retrospect it is difficult to judge. Yes, it is crucial that we learn and see what systems we need to have the “gold standard science data” as early as possible. We all have to invest in that. For example, by building trust in sharing information (without being immediately blamed), by seeking to gain deeper insight into early events (without being threatened with pushing political agendas), by commissioning good research and contributing data without sitting on it (which has been done by almost every agency I know), by having systems that make sense of that complexity of non-standardized data, and by having balanced discussions about how to weigh the risks and benefits of whatever is done and where the results are shared through advisory roles with decision makers in government. I've seen great examples of this, and not so great examples, and I completely agree that we need to learn.

But retrospective opinions about everything that went wrong, in my opinion, block that process, because they do NOT contribute to a meaningful discussion, but rather fuel the polarized debate. And I find it extremely disappointing to see this among highly educated professionals in the US. This isn't about scientific debate, it's rejecting social media to create dogwhistles. Go to WHO, educate yourself thoroughly on what has been done, do outbreak simulation exercises (we do those all the time for people from other fields, they are very insightful) and build a way forward out of this crazy, toxic debate. As head of the largest scientific organization in the world, I believe you have a special responsibility. I'm typing this knowing that I'm exposing myself to a barrage of hateful comments, accusations, threats, etc., which many of us have already had enough of.

Science has a job to do, and in my opinion anyone who claims to know exactly how it should have been done is inherently wrong. Because these things are multifactorial, complex, contextual, etc., which is part of dealing with tough problems.

I'm not defending myself, nor the WHO, nor lockdowns, nor anything else.

I stand up for public health, for all the people in public health and healthcare who have gone above and beyond and in some cases are still suffering the consequences to this day. And yes, I agree that assessments should be broader, including, for example, mental health and economic impacts. But in my opinion, the scientific tools to conduct those kinds of assessments in real time with sufficient quality to use for evidence synthesis in a crisis are lacking. And yes, communicating all that complexity in the middle of a crisis is extremely challenging, especially in our current media landscape with its parallel truths and even malicious actors missing their opportunity to spread inflammatory “questions, thoughts.” I would like to learn how we can move past this, because one thing is certain: there will be new pandemics.

@WHO @ScienceMagazine @ECDC_EU @CDCgov @Eurosurveillanc

Respectfully, Marion Koopmans

Jay:

In any case, I think this thread was posted in good faith, so I'll give a substantive response.

Clearly, in times of crisis, leaders are under enormous pressure to take drastic action to address the crisis, and often those decisions turn out to be wrong in retrospect.

In the case of the Covid crisis, the problems were exacerbated by the determined unwillingness of scientific and public health leaders to respond in real time to data showing that the core assumptions underlying the lockdown strategy were incorrect.

Here is a short list of facts about Covid that undermined these leaders' core assumptions:

• Covid is transmitted through the air.
• Covid spreads asymptomatically.
• The mortality rate of Covid infections is << the mortality rate of cases.
• Covid has a sharp age gradient in the risk of death from infection.
• Lockdowns cannot suppress the spread of Covid or protect vulnerable people for long.
• Lockdowns are destroying the lives and well-being of children, the poor, the working class and almost everyone except the laptop class.
• Lockdowns cause a form of psychological terror that ensures they can never last longer than two weeks

The WHO and public health leaders got it wrong in 2020 all these facts, which I think is understandable.

What is not understandable is that these same leaders “scorchingly demolished” even renowned external critics who pointed out that the WHO's core assumptions were wrong, accepting those assumptions as true even as overwhelming data emerged in real time proving otherwise.

What is not understandable is the utter confidence that WHO and public health leaders publicly spoke about these ideas and lockdown measures as the only way to protect the population, even calling for censorship of opposing voices on social media and elsewhere.

The most comparable situation I can think of is the group of “best and brightest” advisors who told President LBJ that victory in the Vietnam War was within reach, based on a whole host of misinformation. Leaders emerging from such situations, having embraced a slew of disastrously failed ideas and policies, have a number of choices about how to deal with the post-crisis period.

1. They can admit their failures in good faith and work to reform systems so that the disaster never happens again. This would be for the best, although I understand why the public would want a new group of leaders to design and implement the reforms. Personally, I am very excited to work with and learn from public health leaders who choose this option.
2. They can pretend they have done nothing wrong, stay in power as long as possible, hope against hope that history will vindicate them, and destroy public confidence in the institutions they lead.
3. They can pretend they never recommended or adopted the disastrously failed policies, hoping the public has a short memory. This is the current strategy of the @WHO.
4. They may appeal to the difficulty of dealing with a crisis under great uncertainty, not in a spirit of reform, but rather as an excuse to avoid responsibility for their failed crisis management. This is the approach Koopmans takes in her thread.

I have little sympathy for the leaders in the Covid crisis who choose option 2, 3 or 4. Their job was to manage uncertainty with wisdom and humanity, but they have failed to do so. They can't turn around at this point and expect the audience to sympathize with them because their job was difficult, or expect the audience to forget their failure. These leaders have destroyed public trust in public health and must make way for a new group of public health leaders to repair the damage they caused.

Michael Verstraeten:

I respectfully disagree with your statement, professor: “The WHO and public health leaders misinterpreted all of these facts in 2020, which I think is understandable.”

This is not understandable and I prove my statement.

Since the report of the Joint Russian-WHO Commission was published on February 28, 2020, the WHO is aware of almost all the elements you mention in your text. Most of these elements come as no surprise. SARS-CoV-2 was not the first epidemic of its kind. In the 1950s and 1960s we had the Hong Kong flu and the Asian flu. In the 19th century there was the Russian flu, which was very similar to SARS-CoV-2.

The problem is that based on a completely unrealistic “worst case scenario” from Imperial College, much of the knowledge about respiratory viruses has been thrown overboard. The scenario was based on assumptions that were completely disconnected from reality. The following elements, among others, have been completely misjudged:

1. The virus does not mutate. This is a worst-case scenario that has not occurred in respiratory viruses for millions of years.
2. The virus will infect 80% of people in a single wave. No respiratory virus has done this in hundreds of years.
3. The reproduction number remains constant. This has never happened before with a respiratory virus.
4. There has been evidence in Wuhan that lockdowns work. This is inconsistent with the WHO's finding in the joint report that this was the first time such a method had been used. Other factors could not be excluded. Scientific conclusions based on such limited facts are methodologically flawed
5. Measures must be the same for everyone. This did not take into account the specific dangers of the virus, as shown in the Wuhan report.
6. The IFR is not much different from the CFR. The WHO made it clear from the start that the IFR was unknown.
7. The measures are carried out outside. However, the original report from Wuhan states that most infections occur within families.
8. The virus disappears with herd immunity. However, the Wuhan report states that it is uncertain whether full immunity is achieved after infection.
9. No asymptomatic infections. The Wuhan report states on p. 12 reported asymptomatic infections, but these are described as relatively rare.
10. None of the models took comorbidities into account. However, the Wuhan report does mention the importance of these comorbidities.

The conclusion can only be that scientists such as Marion Koopman have put their knowledge aside when determining the measures to be taken. They ignored their general knowledge about viruses and the WHO's Wuhan report.

It is therefore a myth that too little was known about the virus in the beginning. That knowledge was indeed available, but was not used. Just like you were pulled over, to be precise.

Marion:

@DrJBhattacharya thanks for your response. A few more comments. I'm happy to agree that we disagree. You mention topics that I consider part of the scientific advice process, and topics that have more to do with the policy arena and how it works. Sorry, long thread, I lost the blue button.

I have read that your criticism is mainly focused on the second argument and I agree that evaluation is important. I think this varies a lot from country to country, although the same trend (scientists feeling left out) is clearly visible in many places. Personally, I believe in the process of evidence synthesis from multiple sources, while maintaining the need for speed. I have seen this happen in various European countries, where an important spokesperson often conveyed the conclusions to policymakers. That may seem bureaucratic, but it doesn't have to be, and it allows for debate and consideration of (partial) evidence, taking into account the local context and uncertainties inherent in the advice process, which I think is important.

In terms of science, you mention a list of topics, each of which could be the subject of a full study on what exactly it is, how it is measured, what it contributes, etc. An example: the topic of “covid is airborne” has – especially on popular platforms – become too simplistic and is presented as a “yes or no” answer, leaving aside the more difficult questions: what is the contribution of different modes of transmission and how does that translate into interventions? That was what the advice was all about.

SARS COV 2 is emitted from different activities, in different sized particles, which behave differently depending on environmental conditions, with virus infectivity decline rates dependent on context, influencing the effect of interventions. I don't want to go into individual studies on this platform, because that will lead to a back and forth of articles that 'prove me wrong', but I do like this study, which used methods from QMRA (common in the field of food safety) to map this complexity.

The topic of airborne spread also showed a clash between scientific disciplines that had not previously interacted, with different methods and discussions leading to different conclusions. That's fine, that's just how science works. But it is another task to take that mix of views into account when giving advice on how to act.

Also consider the question of who is at greatest risk. The clinical impact clearly increased with age and underlying health conditions. A debate also arose in our country, with suggestions to protect those at high risk and let everyone else go about their business. When we looked at how to implement that, it became clear that this was not very realistic, at least not in our country. Many families, households and companies have members who belong to a risk group or who care for someone from a risk group. Separating those groups was a theoretical concept, not an implementable concept, not in our society. Although scientific advice was against closing schools, this was done at the express request of specialists concerned about high-risk children, and of school and teacher councils.

These are not scientific decisions, but social choices and therefore political choices. Those discussions need to happen now: if we were faced with a new pandemic, what would we do differently? Unfortunately, I don't really see that happening. In our country we are testing simulation exercises with a much broader representation, bringing together some scientists with very different points of view. That has taken many meetings to even understand what the common ground is, what the key questions are that science can provide evidence for, what data is needed, where that data is, how good it is, and whether it is actionable (available in real time, etc.). I agree that evaluation is important.

I think we need to get better, especially in explaining the level of (un)certainty and how that translates into a specific recommendation. I would like to see such studies funded.