Category Archives: Science

Even science has lost credibility

The pandemic has been devastating to the credibility and trust placed in public health and epidemiology.

That loss of trust extends to science itself.

In the UK, their SAGE Committee employed a subteam of psychologists skilled in behavior manipulation (notably based on fear) and propaganda as part of their Covid-19 response. A UK politician has said they should employ the same methods for climate change policy.

Here in the U.S., there has long been a major focus on fear – even news reports that “experts” felt we must exaggerate the fears.

Continue reading Even science has lost credibility

Experts I listen to

I previously published this list within another post. I am elevating this so that I can link directly to it, as needed, in the future.

Some experts I trust:

  • Monica Gandhi, MD, MPH Infectious diseases MD at UCSF
  • John Campbell, PhD retired nursing lecturer, and nurse practitioner
  • Michael Mina, MD, immunologist, epidemiologist, Harvard Public Health
  • Trevor Bedford, PhD, virus researcher, Fred Hutchinson Cancer Research Center aka Fred Hutch
  • Florian Krammer, PhD, virologist, Professor at Mount Sinai med school
  • Tracy Høeg, MD, PhD, sports doctor and epidemiologist
  • Scott Gottlieb, MD, former FDA Commissioner
  • Vincent R. Racaniello, PhD, virologist and professor, Columbia University
  • Jennifer Nuzzo, DrPH, S.M., Johns Hopkins (her June 2, 2020 “protests more important than fighting a virus” posts were idiotic but she seems sensible before and after that)
  • There are likely many others but those are the ones I follow on social media.

I do not necessarily agree with what they say (but do most of the time) and if I disagree its probably because I have seen something they have not seen or I cannot reconcile the discrepancy. But I trust the above experts as working hard to do the best they can.

Experts I routinely ignore because they have been wrong – repeatedly – and seem focused on incorrect but scary fear porn and gaining celebrity status:

  • Michael Osterholm, PhD, Univ of Minnesota
  • Christopher Murray, MD, PhD, University of Washington, IHME (and anything out of IHME)
  • Eric Feigl-Ding, PhD, nutritionist
  • Neil Ferguson, PhD, Imperial College London (wake me when he learns how to write actual software)
  • I lean towards putting Anthony Fauci, MD on this list. After 16 months of doing everything asked of us, 15 days to flatten the curve is now 16 months, and nearly 600,000 are said to have died “of” Covid-19, which means there is little evidence all we did made any difference. In the winter he forecast a “surge upon surge” due to the holidays, which I have shown is not supported by the data (specifically in California). In March he predicted we could not remove restrictions until daily new cases are under 10,000 or things would get really bad; states removed restrictions anyway and cases continued dropping. He’s the public face of all that went wrong, his fault or not.

Those who are not trustworthy, however, have received the most publicity from the media – which biases the public’s opinion against all experts.

I have lost trust in epidemiology, public health and even science itself. And especially the use of models (and I’ve taught university courses in the design, implementation and use of models). The perpetrators of this nonsense are oblivious to the damage they have done to all institutions. I do not see how public health can restore trust and credibility within my life time – it’s that bad.

Read the whole thread

The researchers appear to lack basic understanding of research design and interpretation. Read the whole thread from this university professor.

Face masks forever!!!!! “L.A. County urges masks for all as delta variant spreads – what does that mean for Bay Area?”

Source: L.A. County urges masks for all as delta variant spreads – what does that mean for Bay Area?

I have no idea if the Delta variant is worse, spreading faster or if there is any evidence that masks would have impact.

I do know that public health experts have cried wolf so many times now – scaring us about “super spreader events” that had no impact, predicting “Surges upon surges” that did not happen, predicting  “Holiday surges” that did not happen and scaring us about past variants that did nothing – that I no longer believe one word coming from public health or epidemiology.

Not. One. Word.

My lack of trust in their work and messaging has spread to other fields of “Science”. As soon as I see “New study says…” or “Trust the science” that a load of bull shit is incoming at high speed.

The damage these quacks have done is immense and they seem oblivious to the problem.

Yep: “Trust in science has eroded”

And they will blame the public or politicians for this loss of trust, never looking inwards at their own numerous failures:

The pandemic is on its way out, but how many Americans think the U.S. approach succeeded? More than 600,000 Americans died from Covid, and lockdowns have left extensive collateral damage. Trust in science has eroded, and the damage won’t be limited to epidemiology, virology and public health. Scientists in other fields will unfortunately also have to deal with the fallout, including oncologists, physicists, computer scientists, environmental engineers and even economists.

Source: A Covid Commission Americans Can Trust – WSJ

I lost trust in public health and epidemiology and no longer give science a free pass of trust.

Trust in all science is badly eroded for all those paying attention.

More suicide of expertise

Column asks, what if the Wuhan Lab leak hypothesis is true? What would that mean – a lot, probably.

And how did we get here?

Because if the hypothesis is right, it will soon start to dawn on people that our mistake was not insufficient reverence for scientists, or inadequate respect for expertise, or not enough censorship on Facebook. It was a failure to think critically about all of the above, to understand that there is no such thing as absolute expertise. Think of all the disasters of recent years: economic neoliberalism, destructive trade policies, the Iraq War, the housing bubble, banks that are “too big to fail,” mortgage-backed securities, the Hillary Clinton campaign of 2016 — all of these disasters brought to you by the total, self-assured unanimity of the highly educated people who are supposed to know what they’re doing, plus the total complacency of the highly educated people who are supposed to be supervising them.

Source: If the Wuhan lab-leak hypothesis is true, expect a political earthquake | Thomas Frank | The Guardian

Why masks had essentially no effect on Covid-19 spread

Why are masks so ineffective, even if we presume that they are effective? Because almost everybody that is wearing them does not have COVID-19. So in those people, there is no chance that they could provide any benefit, regardless of how effective they are.

Source: It Doesn’t Matter if Masks Work – Ricochet

Last summer I did a “number needed to treat” (NNT) calculation to prevent one new case and one death. Using the County numbers in effect at the time, and assuming masks were 100% effective and that no other mitigations (e.g. social distancing) were in use:

  • 1,000 people would need to wear a face mask to prevent one new case of Covid-19
  • Between 50,000 and 100,000 people would need to wear a face mask to prevent 1 additional death in my county.

Because face masks are treatment for the almost exclusively healthy who do not have Covid (and masks were to provide outbound protection, and virtually no inbound protection), they were an extremely ineffective way to fight a virus.

In the real world, masks were not 100% effective – some studies found them to be 0%, some perhaps 10-20%, and one CDC study found them to be perhaps 1-2% effective. When you throw those into the calculation, the overall effectiveness in the entire population – assuming 100% “Compliance”, is nearly zero percent.

If 1,000 people wore masks which, using the CDC’s reported number, were 2% effective, than 50,000 people had to wear a mask to prevent 4 cases. In my County, with just under 200,000 population and daily cases of 50 to 100 per day, at best, perfect mask usage might prevent 4 new cases.

If we compared this County with an identical County not wearing face masks, we would then see there 54 to 104 cases per day. If we draw these epicurves on the same chart, we see there is essentially no difference in cases between the two counties.

(Note – except for the 50-100 new cases values, which are real world data, all other values are based on assumptions and a simple model. Real world numbers will vary from this. This is a model, not reality.)

If properly fitted N95 masks, used properly and replaced often, were used, we would have seen inbound protection. However, the CDC ordered us not use N95s or certified surgical face masks and said we should use random bits of cloth, using random designs, assembled by person of unknown skill. Couple with extensive re-use without frequent changes and re-washing, these masks were likely useless.

This explains why it is that well after we had high compliance mask mandates in effect, daily new positive tests great by a factor of 10x or more. By the end of January, studies estimated 30% to 55% of persons in California (estimates varied by county) had anti-bodies to Covid-19. Which means the mitigations in effect – and California was considered among the strictest in the nation – had little or no effect.