I hope he ends up being correct and also not destroyed for being correct.

John Ioannidis is among the more impressive scientists we have.  His 2005 study, Why Most Published Research Findings Are False, was a blockbuster opening fifteen years of research showing just how shoddy has been much of out scientific research.  Sociology and Psychology have been especially bad but the disease has seeped into the harder sciences as well.  

By bringing this to light in a credible and systematic way, Ioannidis has made an outsized contribution of improvement in our sciences.

In the Covid-19 pandemic, he has been a vocal and harsh critic of what he called the global response to Covid-19 a "once-in-a-century evidence fiasco".  A position with which I strongly concur.  He has been a huge thorn in the side of the government policy and has attracted an enormous amount of personal and bitter criticism.

He now has a new paper out, Reconciling estimates of global spread and infection fatality rates of COVID-19: an overview of systematic evaluations.  His approach is beyond my capacity for effective assessment but it leads him to report:

Background: Estimates of community spread and infection fatality rate (IFR) of COVID-19 have varied across studies. Efforts to synthesize the evidence reach seemingly discrepant conclusions. 

Methods: Systematic evaluations of seroprevalence studies that had no restrictions based on country and which estimated either total number of people infected and/or aggregate IFRs were identified. Information was extracted and compared on eligibility criteria, searches, amount of evidence included, corrections/adjustments of seroprevalence and death counts, quantitative syntheses and handling of heterogeneity, main estimates, and global representativeness. 

Results:  Six systematic evaluations were eligible. Each combined data from 10-338 studies (9-50 countries), because of different eligibility criteria. Two evaluations had some overt flaws in data, violations of stated eligibility criteria, and biased eligibility criteria (e.g. excluding studies with few deaths) that consistently inflated IFR estimates. Perusal of quantitative synthesis methods also exhibited several challenges and biases. Global representativeness was low with 78-100% of the evidence coming from Europe or the Americas; the two most problematic evaluations considered only 1 study from other continents. Allowing for these caveats, 4 evaluations largely agreed in their main final estimates for global spread of the pandemic and the other two evaluations would also agree after correcting overt flaws and biases. 

Conclusions: All systematic evaluations of seroprevalence data converge that SARS-CoV-2 infection is widely spread globally. Acknowledging residual uncertainties, the available evidence suggests average global IFR of ~0.15% and ~1.5-2.0 billion infections by February 2021 with substantial differences in IFR and in infection spread across continents, countries, and locations. 

As big a fan as I am, if this turns out to be true, that global IFR is ~0.15%, then it torpedoes most governments policy response to the pandemic.  There is plenty of other evidence to suggest that the forecasts for lethality were way overblown.  But 0.15% IFR is very low.  It might be true.  And the more true it turns out to be the more it will become apparent just how much of a failure were both our institutional authorities and our experts. 

We are a long way from that yet and I am uncomfortable that the IFR is so dramatically low.  I expected it to be low but not that low.   Ioannidis may be methodologically wrong or the data not sufficiently robust.  Certainly his critics will charge him with irrelevant errors as well as possible valid criticisms.  

I guess it is some ways just a prelude.

We know that there has been massive expert and institutional failures, too massive to continue hiding.  All the enforces of narrative are in the same boat though and Ioannidis looks awfully exposed.  I hope he ends up being correct and also not destroyed for being correct.  We'll see.