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.