Coronovirus IV

[doddg]

The 1st link below show deaths per million population (column on far right) in countries.
I realize political agendas distort number of deaths attributed to CV and are manipulated over/under in reporting, but it is about the only thing we have for comparative purposes.

Reported: US has 500 deaths per million rate.

Wouldn't dividing the 500 deaths by 1 million give you the % of deaths for 1 million of the population of the US (0.0005)?
Then, that number (.0005) would be applicable for all 331 million population for the US?

This is the table that I used online:
Decimal to percent Conversion
Enter decimal number: 0.0005
Convert
Percent result: .05% (This would be 5 hundreths of 1%)

This seems way too low.
Not a math person, but I don't know what I'm doing wrong.
A friend was telling me the death rate of CV in the US was less than 1% but this is way beyond "less than 1%."

Reported deaths by each country due to CV:
https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/


I was also looking at death rates per states in the US (link below).
He lives in a state incredibly low & he gives me grief b/c I wear a mask when around others.
IN has 45 deaths so far, much lower than some other states.
Most surrounding states are a little higher than IN.

I told him Indy was the 13 largest city in the US so my experience/attitude is different, plus my wife is high risk & I can't be bringing home something from an asymptomatic person.
He knows of noone who has had CV, but in my different circles I do, although fortunately, like I've read on INGO, it has been mild, not unlike other viruses.

Deaths by each state in US due to CV:
https://www.cdc.gov/covid-data-tracker/#cases

 

[Ingomike]

Don't be obtuse; the FDA determines that, like always.

They are politicized now, look at HQC...

 

[HoughMade]

By using deaths per 1,000,000 of population, you are using a statistic that most do not use.

What we usually see is deaths compared to positive tests, in other words, not the deaths compared to everyone, but the deaths compared to who is confirmed to have the virus, a much, much lower number. .05% may well be accurate as a percentage of the entire population (I have not looked), but I think how many people die who actually get the virus is more useful.

For instance, I will just use Indiana.

Population: 6,732,000

COVID-19 positives: 74,992

COVID-19 deaths: 2,838

.042% of the population has died of COVID-19

3.78% of those who have tested positive have died.

Deaths as a percentage of the population, to me, isn't that useful. Deaths as a percentage of positive tests tell us whether we are making progress on treatment (among other things).

 

[T.Lex]

Wouldn't dividing the 500 deaths by 1 million give you the % of deaths for 1 million of the population of the US (0.0005)?
Then, that number (.0005) would be applicable for all 331 million population for the US?

This is the table that I used online:
Decimal to percent Conversion
Enter decimal number: 0.0005
Convert
Percent result: .05% (This would be 5 hundreths of 1%)

This seems way too low.
Not a math person, but I don't know what I'm doing wrong.
A friend was telling me the death rate of CV in the US was less than 1% but this is way beyond "less than 1%."

No, that math is correct. A bit simpler - there's about 300M people in the US and about 160k deaths attributed to CV. 160000/300000000 = 5.3333e-4 or .000533333 or .053333% of the overall population.

ETA:
I agree with HM that this stat is of limited utility, but can be good to compare across countries, if one accepts that the totals might use different criteria.

 

[chipbennett]

Population-based statistics are useful for discussion of public policy based on the pandemic.

 

[HoughMade]

Population-based statistics are useful for discussion of public policy based on the pandemic.

I agree.

...if i was involved in making public policy, such statistics would interest me more.

 

[Ingomike]

By using deaths per 1,000,000 of population, you are using a statistic that most do not use.

What we usually see is deaths compared to positive tests, in other words, not the deaths compared to everyone, but the deaths compared to who is confirmed to have the virus, a much, much lower number. .05% may well be accurate as a percentage of the entire population (I have not looked), but I think how many people die who actually get the virus is more useful.

For instance, I will just use Indiana.

Population: 6,732,000

COVID-19 positives: 74,992

COVID-19 deaths: 2,838

.042% of the population has died of COVID-19

3.78% of those who have tested positive have died.

Deaths as a percentage of the population, to me, isn't that useful. Deaths as a percentage of positive tests tell us whether we are making progress on treatment (among other things).

I belive just the opposite. They are playing the figures lie and liars figure game. Just like the Kansas chart. Just tell me the deaths relative to the population. That is one of the few stats with meat on it, the rest are nothingburgers. Actually the overall death rate is interesting, last I heard it was down for the year, a time of a deadly pandemic...

 

[HoughMade]

I belive just the opposite. They are playing the figures lie and liars figure game. Just like the Kansas chart. Just tell me the deaths relative to the population. That is one of the few stats with meat on it, the rest are nothingburgers. Actually the overall death rate is interesting, last I heard it was down for the year, a time of a deadly pandemic...

What stats one pays attention to depends upon what information one is trying to learn.

 

[BugI02]

I am genuinely starting to wonder, so yeah its a REAL question.....

Is the only approved study, for you as a person, a BugI02 approved study? I mean do you apply the same rigor to every product you use or are there some where you'll say, "I will just trust the experts on this one". Not just for you Bug but for anyone who keeps tossing up and out studies.

The REAL answer is I make my own assessment of risk about pretty much everything. I try to mine the web for numerical data and use that to inform my decisions, but gut instinct plays a part. For example, I'm not interested in flying anytime soon for the same reason I'm not interested in dining in or going to a pub. I think being in an enclosed space, for a significant period of time, with people of unknown infectivity increases the likelihood of infection if one of them is positive and I don't believe any quick, non-invasive tests have a very good record at determining who might be a problem. I think ad hoc masking is drastically overrated in terms of efficacy and in fact wonder if, by pushing the size of exhaled droplets closer to the aerosol threshold, they might not actually make things worse in an enclosed space

The airflow in a pressurized aircraft is primarily top to bottom and secondarily front to back, but the rate of exchange beyond that necessary to maintain pressurization is controlled by the flight crew and to increase that rate of flow requires the use of more engine power and thus more fuel (because the pressurized air is taken via a bleed valve from the compressor section ahead of the combustor and requires the engine to do more work). I know the airlines are financially on their knees and thus expect that regardless of their official pronouncements, they are seeking to minimize cash burn in any way they can. Thus I conclude that flight crews will be under pressure to control fuel expenses and the rate of exchange in the cabin is likely to be closer to the minimum necessary to maintain pressurization and may in fact be worse than simply being in an well ventilated enclosed space like a restaurant. I also know that airlines have fallen back heavily on the hub and spoke system, that hub airports are a good place to be exposed to a much wider variety of people and infections and that airlines are seeking to fly every flight at the highest density possible

Those judgements, coupled with no pressing need to fly anywhere, inform my decision that I don't need to fly anytime soon

I consider myself a scientist and competent to evaluate data for myself, and I act according to my personal interpretations

 

[Ingomike]

What stats one pays attention to depends upon what information one is trying to learn.

True, I just don't get the members here that go on about stats that have been proven to be unreliable at best and possibly fraudulent...

 

[BugI02]

If you read enough medical journals (and before COVID-19, unless you are a medical professional, a lawyer who does health law or another health-related profession, why would you?) you start to be able to tell good journals from not-so-good journals and, more importantly, good research and content from less reliable content.

It's like how a vet can spot another vet, or a stolen valor guy. There are tells. Some are more obvious than others.

...this is why the Lancet article got called out and also why the Wakefield vaccine article got called out.

Now, one concept that may be difficult to grasp is that an article that results from a conceptually sound study, honest research and sound process may be found to have faults. This can be, for instance, because what turned out to be an important variable was unknown and thus, not accounted for (or for other reasons). This is why peer review often involved replication. This is just how science works when it is done honestly. Even with sound technique and research, you sometimes come to realize there are those unknown, unknowns. After all, if we had all the answers to begin with, we wouldn't need the research.

I believe The Lancet article's problems were only called out because people who wanted to access the dataset used were rebuffed and on derilling down other scientists realized that to have the numbers of patient records claimed Surgisphere would have had to have had the cooperation of virtually every US hospital, but when they contacted 4 large systems (representing something over 25% of all us patients, I believe) none of them had cooperated with Surgisphere. The Lancet itself was very reluctant to take down the paper even in light of demonstrable evidence of numerical irregularites in the data set. That paper was used as an excuse to rapidly terminate clinical trials with HCQ, and those permissions have never been restored despite the retraction

I'm all for research and peer review, so what of the Henry Ford Health System study? I don't see that being used as a data point informing the decisions of those who believe HCQ isn't effective. What about the censoring of the frontline doctors video because it was 'misleading'

As jamil says, 'If it looks like you're hiding something, ima believe you're hiding something'. The less anything is just straight forward science willing to adjust hypotheses to accomodate new data, the more scrutiny any claims will be subjected to by me. From where I sit, there is just as much non-scientific effort being invested in 'proving' HCQ is ineffective as there is in the obverse. As I've stated elsewhere, were I to become symptomatic my judgement is that I would immediately seek a prescription for the HCQ/zinc/antibiotic regimen

 

[nonobaddog]

I am genuinely starting to wonder, so yeah its a REAL question.....

Is the only approved study, for you as a person, a BugI02 approved study? I mean do you apply the same rigor to every product you use or are there some where you'll say, "I will just trust the experts on this one". Not just for you Bug but for anyone who keeps tossing up and out studies.

The field of "experts" has been terribly polluted by those willing to sell their integrity to politics. There was a time when trusting the experts was a valid, albeit easy, way out of being responsible for your own decisions but these days trusting "experts" is foolish and dangerous.

 

[foszoe]

Thanks for that answer.

I watched a CEO of an airline on CNBC within the last month or so claim that air in a airplane is safer than your "average air". Can't remember the exact details, but I think he compared it to bars/restaurants/indoor shops.

The REAL answer is I make my own assessment of risk about pretty much everything. I try to mine the web for numerical data and use that to inform my decisions, but gut instinct plays a part. For example, I'm not interested in flying anytime soon for the same reason I'm not interested in dining in or going to a pub. I think being in an enclosed space, for a significant period of time, with people of unknown infectivity increases the likelihood of infection if one of them is positive and I don't believe any quick, non-invasive tests have a very good record at determining who might be a problem. I think ad hoc masking is drastically overrated in terms of efficacy and in fact wonder if, by pushing the size of exhaled droplets closer to the aerosol threshold, they might not actually make things worse in an enclosed space

The airflow in a pressurized aircraft is primarily top to bottom and secondarily front to back, but the rate of exchange beyond that necessary to maintain pressurization is controlled by the flight crew and to increase that rate of flow requires the use of more engine power and thus more fuel (because the pressurized air is taken via a bleed valve from the compressor section ahead of the combustor and requires the engine to do more work). I know the airlines are financially on their knees and thus expect that regardless of their official pronouncements, they are seeking to minimize cash burn in any way they can. Thus I conclude that flight crews will be under pressure to control fuel expenses and the rate of exchange in the cabin is likely to be closer to the minimum necessary to maintain pressurization and may in fact be worse than simply being in an well ventilated enclosed space like a restaurant. I also know that airlines have fallen back heavily on the hub and spoke system, that hub airports are a good place to be exposed to a much wider variety of people and infections and that airlines are seeking to fly every flight at the highest density possible

Those judgements, coupled with no pressing need to fly anywhere, inform my decision that I don't need to fly anytime soon

I consider myself a scientist and competent to evaluate data for myself, and I act according to my personal interpretations

 

[BugI02]

It's more like sharing an multi-hour Uber van ride with 8 - 12 strangers and the windows shut

Edit: I'm lucky in that any family I might need to attend to are within a reasonable drive, farthest away are about 10 1/2 to 11 hours

 

[nonobaddog]

I saw an article on how the air in planes could be made much safer with changes to ventilation and filtration but I doubt if any of that is even on their radar.

 

[nonobaddog]

By using deaths per 1,000,000 of population, you are using a statistic that most do not use.

What we usually see is deaths compared to positive tests, in other words, not the deaths compared to everyone, but the deaths compared to who is confirmed to have the virus, a much, much lower number. .05% may well be accurate as a percentage of the entire population (I have not looked), but I think how many people die who actually get the virus is more useful.

For instance, I will just use Indiana.

Population: 6,732,000

COVID-19 positives: 74,992

COVID-19 deaths: 2,838

.042% of the population has died of COVID-19

3.78% of those who have tested positive have died.

Deaths as a percentage of the population, to me, isn't that useful. Deaths as a percentage of positive tests tell us whether we are making progress on treatment (among other things).

People (like CDC) use population based numbers a lot. It is usually expressed as deaths per 100,000.

If we have 160K deaths in out population of 330M, that is 0.048% of the population.
480 per Million = 0.048
48 per 100K = 0.048% (most common)
4.8 per 10K = 0.048%

This number is kind of like a fuel gauge to see how far along the disease has progressed. For practical purposes this number doesn't go down, it only goes up over time. A common thread is guessing how far it will go up.

One advantage of population based numbers if that the population is pretty well known and somewhat accurate.
Testing based numbers have systemic errors dependent on several variables like availability of tests, motivation to test, execution of test, inaccuracy of the tests themselves, multiple tests on the same individuals counted as separate tests, variability of all other variables between different political entities, etc., etc.

 

[doddg]

I have never given any thought to the % of deaths compared to "confirmed" cases of CV since everyone is not tested the % of deaths relative to only people who have been tested is inflated to the max and is w/o value.

I saw a weekly chart on the % of occupancy of ICU beds (for CV patients) that I thought would be a real indicator of if the virus was increasing or declining what is happening in the real world.

 

[T.Lex]

I saw a weekly chart on the % of occupancy of ICU beds (for CV patients) that I thought would be a real indicator of if the virus was increasing or declining what is happening in the real world.

I would be interested where that ICU bed number was. The worldometers site has a value for critical, but it REALLY isn't clear what that is based on.

I, too, think that would be a really good metric, but I have found no reliable source.

 

[HoughMade]

I would be interested where that ICU bed number was. The worldometers site has a value for critical, but it REALLY isn't clear what that is based on.

I, too, think that would be a really good metric, but I have found no reliable source.

I don't know about the whole country, but Indiana has the total ICU bed availability and the percentages used for COVID, used for other purposes and unused., on its "dashboard".

https://www.coronavirus.in.gov/2393.htm

 

[T.Lex]

I don't know about the whole country, but Indiana has the total ICU bed availability and the percentages used for COVID, used for other purposes and unused., on its "dashboard".

https://www.coronavirus.in.gov/2393.htm

Yes - Indiana is good with those numbers.