The greater you make the danger, the more money you can get

Read full article: The greater you make the danger, the more money you can get

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Great article

Alex Washburne has written a great article partly based on the information that has emerged in relation to the interrogation of Peter Daszak on May 1. It is a very long article, but the content is impressive. And then you are left astonished at what scientists can do uncorrected.

The most important conclusion that can be drawn about the way in which Peter Daszak and apparently many colleagues work is that they greatly exaggerate the threat to people/humanity in order to get a lot of money for their work that claims to be the same humanity. to protect. And if something goes wrong with their work, they do everything they can to mislead the outside world. Helped by colleagues such as Marion Koopmans, with similar interests.

This is best proven in his article, in which Alex quarters the argument of Daszak et al. that approximately 60,000 people become infected every year because Coronaviruses jump from bats. A number that is then used to link the probability of the start of SARS-CoV2 to the market and away from a lab leak.

I have translated that part of his article and simplified it a bit, but when you read it the scales will fall from your eyes.

60,000 per year???

In September 2021, Peter Daszak and a number of others wrote an article in which they showed an approach to estimate how many times per year a human in Southeast Asia was infected by a Coronavirus that jumped from a bat. The result was 60,000 times per year.

Alex Washburne shows how much Daszak has discarded any hint of scientificity to arrive at this very high number and thus also give the impression that an outbreak on the market in Wuhan was much more likely than a lab leak. Plus other scientists then refer to that article.

If you really want to know the fine details of Alex Washburne’s description, then I suggest you go to his article. Below is my attempt at a summary

The calculation method

This was the approach of Daszak et al

1. Estimate the prevalence of bat + SARSr-CoV from bat field samples
2. Estimate where bats lived
3. Estimating where people and bats overlapped
4. Estimate human infections due to bat-human interactions

The first three points are easy and trivial. It really only concerns the fourth point: Realize that the most important barrier to human infection and spillover not the overlap is with bats, but rather the virological barriers: receptor binding and cell entry of a bat SARSr-CoV into a human cell, resulting in a human infection.

When we swim in the ocean, we encounter billions of viruses, yet people rarely get infected by viruses in the ocean because viruses in the ocean cannot enter human cells. We hug our dogs when they have kennel cough and we don’t get sick because that pathogen can’t enter our cells either. Some virus variants may be better able to make the jump, and indeed this is why DARPA’s PREEMPT call sought “jump-capable quasispecies” and prevent these narrow range of jump-capable variants from entering humans.

What about SARS-CoVs? Why haven’t we seen many SARS-CoV spillovers before?

How did the authors get around this lack of evidence for spillover effects by still estimating more than 60,000 spillovers from SARS-CoV every year?

The ideal approach

Before diving into a scientific article, it’s worth asking yourself: how do you estimate the number of people infected annually with SARS-related CoVs directly from bats?

Ideally, we would be able to randomly sample people, either PCR testing of patients presenting with a particular chief complaint or perhaps serosurveys providing immunological evidence of past exposure in a representative set of people in the population. Ideally, the serosurveys would be very specific and conducted in a way that reduces the chance of false positives from exposure to other coronaviruses, as serosurveys can respond to things that are not the target we are looking for, so we need to adapt for these false positives.

It really has to be a coronavirus, because viruses differ greatly in their ability to infect people upon contact and in the ways in which people come into contact with the viruses. Choosing the right species for comparison is always an art of the biological sciences, but we can make a good choice by focusing on the basic ecology (including molecular virology) of the species or ecological interaction of interest.

Sinning against every rule

But none of this. The authors sin against every rule. Make off with figures from other viruses. Use possible false positives to inflate their own numbers. And last but not least: count possible human-to-human infections as contamination by a bat.

Some examples:

• They use the 2 positive tests out of 796 tests performed to do their calculations. But ignore the fact that there is a good chance that these are false positives.
• They start calculating with an Ebola outbreak from 2015, overestimating the figures by a factor of 6 to 7 and also ignoring the fact that some of the infections are caused by a human-to-human transmission instead of from an animal.

But the worst part is this: The highest seroprevalence they estimate – and use in their model to estimate the rate of SARS-CoV spillovers from bats – comes from a serological survey of SARS-CoV-2 AFTER SARS-CoV-2 pandemic caused. Similar to the Ebola virus serosurvey in Congo, one cannot say what proportion of these SARS-CoV-2 seropositive samples were due to spillover from bats and what proportion of these SARS-CoV-2 cases were due to human-human transmission. Alex Washburne then states that he is willing to bet almost all his money on the fact that these 3 SARS-CoV-2 seropositive cases from 12 samples are more likely to be people exposed to the virus circulating in a global human pandemic than 3 independent bat spillovers.

The authors’ estimates of the spread of SARSr-CoV by bats come from serosurveys of many other bat viruses transmitted by very different ecological processes (e.g. fruit dropped by fruit bats, bushmeat consumption for Ebola virus, date palm sap consumption for Nipah virus). The results of the serological studies are a mix of either indistinguishable from a fair percentage of false positive serological tests, over-reported compared to the literature cited without justification, or most likely due to human-to-human transmission such as their serological investigation of SARS-CoV-2 and not due to independent bat spillover events.
There were a total of 31 seropositive tests out of approximately 1500 serological tests performed, or 2% of seropositive people with tests whose specificity is less than 98% for bat viruses whose transmission is caused by entirely different ecological interactions than SARS-CoVs.

From these 31 seropositive tests of questionable relevance for SARSr-CoV spillover, the authors estimate 60,000 SARSr-CoV spillovers per year.

If we were to correct for false positives from non-specific tests and remove viruses whose emergence is due to interactions that never occur with insectivorous microbats, the resulting estimate would be less than 1 SARS-CoV spillover per year, because we do not have empirical documentation of such spillovers, except for one outbreak of SARS-CoV-1 and the Mojiang miners infected with a virus related to RaTG13.

Careful examination of the data suggests that any numbers extracted from the above serosurveys will grossly overestimate the number of SARS-CoV spillovers – actual infections – in the human population each year and the truth is that we have no evidence of 60,000 spillovers per year . That number was constructed by an accumulation of methods, which can be traced back to an inappropriate complication of serosurveys not corrected for low specificity and different ecological causes of infection.

Closing

Alex Washburne concludes: “As you can see, I try to do my due diligence by carefully researching the methods AND additional information of papers I cite. Daszak and his co-authors claim to estimate 60,000 SARSr-CoV spillover events per year, but among the giant pile of methods, the results come entirely from serosurveys that contain no information on SARSr-CoV spillover rates!

When I see people like Baric repeating these numbers without properly reading the articles or the limitations of the statistical methods (methods I helped develop!), it turns my stomach. They repeat these claims as if they are sound and unbiased, without the possibility of deception by people who have the most to lose in the event of a laboratory accident. Who predictably use these overestimations to blow away the evidence of a laboratory accident.

I cannot help but express concern that Baric, a member of the National Academy of Sciences, a body created to provide unbiased scientific assessments to policymakers, is not providing unbiased scientific assessments to policymakers. Forgive me, but I feel a civic duty to report the numbers honestly and not play the scientific phone by parroting the numbers of people who are being investigated as likely to cause a pandemic.”