FelonDJT wrote:
"What about H1N1?!?!"
H1N1 - R0 (rate of communicability) of 1.4-1.6, hospitalization rate of 0.4%, death rate of 0.02%
Influenza - 1.28, 1%, 0.1%
Covid-19 - +3.0, 20%, 1%
Imagine 20yrs of influenza hospitalizations happening in 6 weeks.
Let me give an example of how your numbers can be instantly misleading and a perfect example of how selective statistic picking can create unnecessary fear. Sure if I read this number straight up I could convince myself how terrible this is, bunker down in a hazmat suit and be happy that in 8 weeks I survived.
But your numbers are misleading. Where did this 20% number of hospitalizations come from? Not any real data unless you can provide the source. China, with a standard of healthcare and general standard of health and living far lower than the US has experienced a 15% hospitalization rate so not sure where your number of 20% comes from.
Simply picking a data point in time, extrapolating it and making it applicable to an entire population is also flawed logic. Even now if we have a rate of hospitalization and death of 10% and 2% it doesn't mean that this is the "number" moving forwards for the entire US. The US death count as of Friday was 51 people - 31 of these happened in nursing home communities in the Seattle area. So if a certain age and health profile has fueled death numbers is it not also logical to suggest this could also be behind hospitalization numbers?
I mean I just watched a video of Donovan Mitchell saying he feels fine and is quite happy playing video games at home with a few weeks off - not sure if he will be visiting the hospital anytime soon.
Now if your potential hospitalization number is largely dictated by at-risk patients (an age and condition of health candidate), your number looks completely different for the US as a whole. So when you start talking about a shortage of hospital beds you need to make better and more logical calculations. Short example of that
100 people have the virus
10% need a hospital bed = 10 beds
we still have 100 people with the virus
20 are at high risk and 10% will need a hospital bed = 2 beds
20 are at a medium risk and 5% will need a hospital bed = 1 bed
60 are at a low risk and 2% need a hospital bed = 1.2 beds (lets say 1 bed)
You see how this makes a difference? This is more like what we are dealing with here. In this example above I am not even sure if really high risk candidates even make up 20% of the number infected - I don't know. Either way I'm showing how the candidate and circumstances make a difference - in this example it makes a difference of 50%!!!
I'm hearing now that we are proposing a full societal shutdown. Great, cool - for people of privilege like me who earn 6 figures and can "work from home" this is awesome - paid holidays basically. What about less fortunate people who don't have this luxury. People in the service industry who rely on human interaction (tips) for their living? This is where your flawed numbers create situations of unnecessary panic that have impacts on people that are really serious.
So think about that before you drop your (330 million x 3%) x 20% nugget down at your local - wait no, you won't because that's probably shut too shut now too. ^^