Hacker News Reader

Comment by rocqua | Hacker News Reader

Scary thing is. Milder disease is a constant factor improvement in hospitalization. But faster spreading (higher R value) is an exponential worsening in hospitalization.

It's probably better to have a 50% hospitalization rate and an R value of 0.8 than a 5% hospitalization rate and an R value of 2. After 3 'generations' of spreading the second situation already has more hospitalizations.

View on HN

The CDC has estimated the overall hospitalization rate since the start of the pandemic at about 5%. Now with vaccines and other improved outpatient therapies the hospitalization rate is dropping.

https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/burd...

The Omicron variant R0 value appears to be somewhere in the 7 - 10 range.

https://www.thelancet.com/journals/lanres/article/PIIS2213-2...

> It's probably better to have a 50% hospitalization rate and an R value of 0.8 than a 5% hospitalization rate and an R value of 2. After 3 'generations' of spreading the second situation already has more hospitalizations.

Sure, but those aren’t the only choices. Over the last 30 days the daily case average has increased by 500%. During that same time the daily average hospitalized has risen 100%.

And the test positivity rate has increased to almost 30%, which implies an almost comical undercount in actual cases.

The contagiousness and severity are diverging in an extraordinary way. We’re likely undercounting cases by 1/5 or 1/10th.

The testing positivity rate is relatively useless at this point. For example, in my State, there is no way to report a positive test from a rapid result. Only PCR tests administered by a medical professional are considered valid for statistical purposes, even though the government is giving out free rapid tests.

I don't think it's useless. I think it's a pretty good indication that there are many multiples of actual cases for every confirmed case. If covid cases have risen 5,000% in 30 days, but hospitalizations have only risen 100%, that's an extraordinarily positive outcome.

This is for good reason. Rapid tests are substantially less sensitive and often give false negatives, especially for asymptomatic cases. There are also a lot of rapid "at home" tests out there that have high false positive rates, so even if non-PCR tests were added to the data the only reasonable approach would be to still require them to be administered by a medical professional to make sure the test is correctly administered and that the test itself is relatively high quality.

The idea that rapid tests are less sensitive and therefore not valuable is summer-2020 thinking and outdated.

Rapid tests are perfectly fine and should be counted by health departments.

Case in point. My family of 4 all tested positive on rapid tests. 3/4 of us had symptoms. None of us received PCR tests because the next available appointments (other than a 6 hour wait at a state run testing center) were a week away.

Thats 4 people not counted. And we were part of an outbreak that included 3 other families that all tested positive via rapid tests.

Unknown cases don't use up ICU and hospital beds and don't result in deaths, so who cares?

It's pretty important to determine actual severity rates.

An R value of .8 would quickly go extinct.

Exactly!

Maybe but “exponential growth” is a conspiracy theory promoted by epidemiologists. In reality, growth follows the S-curve, so a milder, faster spreading disease will also saturate the population (flatten the S-curve) much sooner, so overall the impact will be much less.

You want to keep the number of cases in a range that the health care system still can deal with. Reaching the the flat part of an S-curve (i.e. infecting everyone as fast as possible) is NOT desirable because that leads to many cases in very short term.

That what I hope for. It looks like uk is like this. But is USA like this?

I've seen this argument elsewhere and I don't get it. From my understanding the limitation on exponential growth, the flattening of the top part of the S-curve, comes from total population. There is no one left to infect, basically.

If the rising part of the S-curve is steep, that means people get infected within a shorter timespan and a corresponding higher load on hospital beds and healthcare personnel, which is what we are trying to avoid with the lockdowns.

What am I missing?

Also, calling exponential growth a 'conspiracy theory' seems unnecessary

A conspiracy theory lol. When they talk about exponential growth, they are talking about an R0 > 1. Yes, after some point it drops under 1 and flattens out because there are fewer and fewer people to infect.

Reply on news.ycombinator.com