# What are sane reasons that Covid data is treated as reliable?

I feel like this is one of those questions that's somehow too basic to ask. Or maybe too political. Like wondering this stuff implies I'm siding with something.

I'd really like to just set all the politics aside, simply name my ignorance, and hear some truthful answers. Because seeing this not even *discussed* is part of what's giving me a sense of "Fuck it, no one actually knows anything, everyone is just making random shit up that fits their social identities."

People keep talking confidently about incidence rates for different Covid variants, about their death rates and likelihood of hospitalization, how we have such clear data on vaccine efficacy and safety, etc.

But all the info streams I see look *extremely* dubious. I don't just mean one *could* doubt them. I mean, I've witnessed powerful evidence of blatant bias, and aside from brief mentions of the existence of those biases *no one seems to care*.

I'll give some examples below that inspire my confusion. I want to emphasize that I'm honestly asking here. Less Wrong is one of the few places (the only place?) where I feel like I can seek epistemic cleaning and clarity here.

So, example confusion sources:

*   I've personally known many people who have had serious medical problems that sure looked clearly like vaccine reactions. On par with "Well now I can't get out of bed and can't think anymore" or "Oh shit, heart attack" kinds of reactions. But *all* these people I've known who tried to report their reactions were told "No, your reaction can't have been due to the vaccine, because the vaccine is safe and effective." I've heard lots of similar reports. Because this is about *rejecting data collection*, I don't see how anyone could possibly know how common/rare this is.
*   I've never known anyone who has been tested for a variant of any kind. I don't know anything about how variant tests look different from a generic Covid test. So where are these numbers for variant spread coming from? Maybe hospitals do have special genetic tests and reliably do those? But then isn't there going to be a pretty strong bias based on the fact that these are only for people who are getting hospitalized?
*   There was, best as I could tell, active (if unintentional) data destruction quite early on in the pandemic. Maybe it's still going on? Hospitals had financial incentives to find reasons why people who died had died of Covid. Lots of bodies got cremated before autopsies could happen. So how strong was that bias? I never heard any curiosity about the implications of this for our sense of how deadly the virus actually was. (Plenty of hand-wringing and finger-pointing though.)

I get that we can deduce something about the virus's spread based on (a) how many hospitalizations for Covid different areas are getting plus (b) some assumptions about the exponential-flavored spread of the infections. That lets us use math to peer into how many non-hospitalized infection cases there must be, and roughly how long the incubation-to-infectious timing should be.

But how in the bajeezus can anyone possibly extrapolate from there to how long it takes to become *symptomatic?* In need of hospitalization, sure, but how is anyone getting not-heavily-biased data on symptom strength below the hospitalization threshold?

I don't care about symptomatic-ness per se. This is just one of a ton of examples about info passing through the info commons that people — including here! — seem bizarrely (to me) super confident in despite the devastation and weaponization of said info commons.

I could believe there's some solid clear reasoning going on in the background here, grounded in hard-to-refute data, that makes all these assertions about Covid's variants and death rates and vaccine safety and so on actually quite solid. And it's just not obvious because the main social messaging is about authority and duty and "Sacrifices to the Gods" as Zvi puts it.

If so…

…could y'all help me see the sane thing?