Dr. Levitt: Your words have power. Use them carefully

Quoting: "I’m concerned that people interpret your conjectures as facts.". Harris the author is a Phd candidate in biology at Stanford who is calling out Levitt, a Nobel Prize winning structural biologist at Stanford, for his evidently non-scientifically based popular COVID advice "in keeping with your hostility to epidemiology". Harris maintains Levitt is doing damage, real damage to public health, to his reputation, and the reputation of Stanford. I am just some random, but I was persuaded by her reasoned and pointed argument. Her article took some guts to write. I hope it is constructively received. I would be curious to understand what is driving Levitt.

EDIT: adding a link to an interview w/ Levitt from 8/20: https://www.stanforddaily.com/2020/08/02/qa-michael-levitt-o...

I have been following Dr. Levitt since the beginning of the pandemic, and I have now count loss of how many of his predictions turned out to be wrong. Also he never fleshes out how he is doing his calculations. At this point, any reasonable person with some self-reflection would just shut up.

Mallory Harris is critiquing Dr. Levit because he is not agreeing with the scientific consensus. She is also holding him accountable for re-interpretations of his twitter stream. If this is true, then anyone with any authority or rank should stop using twitter or say anything at all; there is always a chance that someone else can twist your words and use your authority to back their case.

For a comparable case, Ian Plimer, an AGW denialist geologist, of repute in his own field, but now notorious for making completely outrageous statements to his side of belief in the climate science.

He's off-piste, outside his competency, arguing outside of the peer review process.

Why do senior scientists do this? Is this some form of relevance deprivation syndrome?

Reading between the lines, I'm able to ease out just a tiny little bit of information...

A 21st-century struggle session. “Agree with the consensus or else.”

Once the political climate around epidemiology settles down and allows for hard questions to be asked (and answered), there are some questions about a perceived loss of credibility that I would like to see be addressed.

When a lay person first encounters an epidemic, the first questions are something like: 1. How does it spread? 2. How likely am I to catch it if I’m exposed to it? 3. How can I prevent the spread? How effective is it? 4. What should I consider if I have to risk an exposure?

I think about HIV and these questions. With HIV, each question has an extremely clear answer, often with statistics attached (eg: condoms prevent transmission with 99% effectiveness), is clearly communicated and understood. For non-experts, the mental model developed by doing even a little bit of reading is sufficiently accurate to make reasonable guesses on how to behave to reduce risks with HIV.

As a lay person who wants to understand how to reduce risks around covid-19, the epidemiology community has not been helpful. Even now, it’s hard to find straightforward answers from peer reviewed publications for questions like “Does covid spread through touch?” in a way that lets me model risks in my head. “Use hand sanitizers just to be safe” isn’t good enough from a field dedicated to figure out how infections spread and at what rates.

It’s December 2020. A year since Covid-19 appeared on the world stage. What I want is a table that lists vectors of transmission, effectiveness of transmission along that vector.

Something like

  | Vector.           |  Effectiveness |
  ——————————————————————————————————————
  | Breathing 10ppm   |                |
  | air for 5 mins.   |                |
  | Breathing 100ppm  |                |
  | air for 5 mins.   |                |
  ...

Throw in some graphs, confidence intervals and what variables to adjust for (temperature, time of exposure etc)

With the right data, it should be blindingly obvious that masks work or that 5 covid positive people breathing out viral particles inside a Costco can increase the viral concentration inside to dangerous levels in 40 mins (I’m making up all the numbers here).

Instead, we have public announcements that 23 mutations in a new strain result in a 71% more transmissible virus with implications that some expert in the field without any data or details on how the 71% number was derived. Do the new mutations cause an increase in viral particles being exhaled by an infected person? How much increase? Are the viral particles somehow smaller and able to penetrate masks more effectively or survive longer in the air and thus travel greater distances downwind? What measurements have you made, what variables did you control for, what scrutiny has your observations seen?

When LIGO announced the first observations of gravity waves, everyone believed that the people behind the announcement had done due diligence before making the announcement. The physics community holds itself to a very high code of conduct, and this lends them credibility. Even mistakes like the faster-than-light neutrinos are forgiven because of the credibility the physicists maintain.

The absence of that credibility has been a disaster. I’m not going to forget the announcements that masks don’t work and shouldn’t be used earlier this year. That’s an irreparable damage to the credibility of epidemiology - and when covid is over, I would like to see a real post-mortem with actionable steps to fix the code of conduct and credibility.

I find it fascinating that people always object to others' speech not because they might be misled by it, but because they are concerned that others might. It's patronizing and arrogant.