Comments of Harvard University Prof, Martin Kulldorff via the Daily Skeptic
On the scientific community’s denial of natural immunity…
We’ve known about natural immunity since 430 BC during the Athenian plague. So this is not a new concept. It would have been shocking if the immunity from the vaccine was better than the immunity from having recovered from Covid. So by pushing these vaccines on those who already had Covid, was both unnecessary and unethical, but it also diminishes the trust in public health authorities and diminishes the trust in vaccines. […] These vaccine fanatics (e.g., Canada's low-IQ PM, Justin Trudeau) who insisted that everybody should be vaccinated, including those who already have immunity from having recovered from Covid, I think they have destroyed the confidence in vaccines in general, to an extent that a small group of pre-Covid, so-called anti-vaxxers had never succeeded.
On the reaction to the Great Barrington Declaration…
The difference was that it came from three people other than one person. All of the three of us have worked on infectious disease technology. […] All of us came from reasonably respectable universities: Oxford, Harvard and Stanford. So it was impossible to ignore. We were attacked, including by the NIH Director Collins and Anthony Fauci and Jeremy Farrar at the Wellcome Trust here and Christian Drosten in Germany who called us pseudo-scientists. But I think the key thing was to show the public that there was not scientific consensus for lockdowns.
On whether he was supported by Harvard after speaking out…
No, I didn’t get much defence from the university, no. […] I got private emails from many of the faculty members, many of whom I’d never heard of before. So there was support, yes, from individuals. […] I think that’s a huge problem for science as we move forward, because science can only thrive with discussions. It’s a process. And if we don’t have open discourse about science, science is going to die.
On the problems with epidemiological modelling…
I think these models where you predict a certain number of people are going to die, are pretty useless. And the key thing is what is the optimal strategy to use? So in the case of Covid, in the beginning, we didn’t know exactly what was the infection-fatality rate, which is what’s the risk of dying if you get infected, because we didn’t know how many people had got infected. The optimal strategy doesn’t depend on if it’s 0.1%, or 1% because the optimal strategy depends on the difference, the relative risk in the difference by age or some other factor. So in terms of deciding what is the optimal thing to do, these models that Imperial College developed, I think were very useless.
On the effects of mishandling the pandemic…
I think there will be an enormous distrust in public health agencies. I think there will be an enormous distrust in science, in the scientific community. I think that will take decades to repair, if it can be repaired, I don’t know. I’m sure there will be consequences, political consequences as well. They’re obviously enormous public health consequences from the collateral damage, which I mentioned. I think there’s also economic consequences of these lockdowns that we’re starting to see now. So I think the consequences are profound. And maybe we are in a tipping balance in terms of whether we accept this as the standard way of doing things, which I think would be terrible, or maybe we go in a different direction, where we say, this was a fiasco, let’s make sure it doesn’t happen again.