There I was, thinking I was typing into the void...and it turns out the comment notification had got turned off so I hadn't seen them. As well as lots of unread comments, there were quite a few stuck in moderation (it's off by default, but I think that goes on automatically after a period of time).
I am having a look back but if I've missed anything specific please copy and post again so I notice. For the most part it looks like you've answered each other which is helpful :-)
Ha, and there was me thinking you just didn't care :-)
ReplyDeleteI thought it was my comments in response to someone else. I figured, oops, went too far in the name calling department.
ReplyDeleteI also thought that something got turned on. My EuroMOMO Week 18 comment just went poof, but now it's back. :)
Also btw I think blogger turned offc notification globally. If there's an on switch I haven't found it. I only get nots if I comment myself.
ReplyDeleteIt's notifying now - I switched it on in settings. Now I think about it, it was misbehaving a while ago and I switched it off and on again a few times to try to fix it. Maybe left it off. At that point I was hardly posting anyway.
ReplyDeleteOddly, I didn't get auto-emailed this post though...
Oooh yes it is under Settings -> Email. I'd been looking under "comments". Duh. Well I've turned mine on now.
ReplyDeletehttps://www.medrxiv.org/content/10.1101/2020.05.13.20101253v1
ReplyDeleteI’ll just point out that this new meta-analysis agrees well with my estimates of IFR stated here and elsewhere. The number is 0.01%-0.4%. Naturally, it will be highly variable depending on the age structure of those exposed.
I’ve taken a lot of abuse on this issue both here from the usual suspects from the usual anonymous bullies. Some of them should apologize for all their insults and sneering. I note that the rudest are wearing hoods perhaps white in color.
“Infection fatality rates ranged from 0.03% to 0.50% and corrected values ranged from 0.01% to 0.40%. Conclusions The infection fatality rate of COVID-19 can vary substantially across different locations and this may reflect differences in population age structure and case-mix of infected and deceased patients as well as multiple other factors. Estimates of infection fatality rates inferred from seroprevalence studies tend to be much lower than original speculations made in the early days of the pandemic.”
Will James admit that he might have been wrong?
I tried to comment on the Euromomo to rub Sarg and Mal's noses in their content free errors, but it seems to keep disappearing.
ReplyDeleteBefore posting any more of Ioannidis' dross, I suggest you spend 5 minutes on twitter reading up on why it's bunk.
ReplyDeleteSince multiple large regions of the world have had total mortality in excess of 0.1% (I think London is around that now), some by a substantial margin despite lockdowns, anyone pretending that the IFR can be be less than 0.2% is simply lying at this point.
Why are you lying?
"Will James admit that he might have been wrong?" Will David Young even read criticism of something he would like to be true? So tent hospitals in Central Park happen in bad flu seasons? That might be kind of thing that rings a few alarm bells. Let's see how this fares in peer-review.
ReplyDeleteYou are better than this James. Twitter is a garbage forum. Your game here is very old. Politically motivated outsiders with no expertise smear top researchers and their scores of collaborators on Twitter. There is an entire book about this called Merchants of Doubt.
ReplyDeleteYou cite meaningless statistics when we have no idea how many have actually been infected. It’s called Infection fatality rate because it’s not the same as Case fatality rate.
Phil, Your meaningless observation is noted.
ReplyDeleteTwitter has some garbage but the poster was retweeted by Bergstrom which is a pretty strong recommendation. And a good number of other epidemiologists too.
ReplyDeleteAs for the Ioannidis junk...his IFR of 0.07% for Scotland would mean that about 80 million of the UK's 67 million population has been infected. He's not even trying to do a proper analysis any more, just chumming the water.
THE LIAR can not even copy-n-paste what the abstract sez ...
ReplyDelete"Infection fatality rates ranged from 0.03% to 0.50% and corrected values ranged from 0.01% to 0.40%."
... should be ...
"Infection fatality rates ranged from 0.03% to 0.50% and corrected values ranged from 0.02% to 0.40%."
You LYING sack-o-shit.
Of course, Dr. Buzzard Beaknose is a cretin, so for example, no modeling at all. Factor of 20 is more like a factor of 100 (0.02% to 2.0%).
Should read his own 'everything is GIGO' paper even.
What someone here totally fails to understand is mortality rate, meaning that mortality rate sets an absolute minimum for CFR or IFR.
ReplyDeleteSo currently, NYC (the five boroughs) has a mortality rate of ~2510 deaths per million or 0.251%.
Estimating the Global Infection Fatality Rate of COVID-19
"COVID-19 has become a global pandemic, resulting in nearly three hundred thousand deaths distributed heterogeneously across countries. Estimating the infection fatality rate (IFR) has been elusive due to the presence of asymptomatic or mildly symptomatic infections and lack of testing capacity. We analyze global data to derive the IFR of COVID-19. Estimates of COVID-19 IFR in each country or locality differ due to variable sampling regimes, demographics, and healthcare resources. We present a novel statistical approach based on sampling effort and the reported case fatality rate of each country. The asymptote of this function gives the global IFR. Applying this asymptotic estimator to cumulative COVID-19 data from 139 countries reveals a global IFR of 1.04% (CI: 0.77%,1.38%). Deviation of countries' reported CFR from the estimator does not correlate with demography or per capita GDP, suggesting variation is due to differing testing regimes or reporting guidelines by country. Estimates of IFR through seroprevalence studies and point estimates from case studies or sub-sampled populations are limited by sample coverage and cannot inform a global IFR, as mortality is known to vary dramatically by age and treatment availability. Our estimated IFR aligns with many previous estimates and is the first attempt at a global estimate of COVID-19 IFR."
https://www.medrxiv.org/content/10.1101/2020.05.11.20098780v1
Young,
ReplyDeleteRather than thrash around, answer the basic question:
How can the IFR possibly be lower than the recorded mortality rate in several regions, and indeed, entire countries?
The answer of course is very easy. IFR will be very dependent on the age structure of those infected as I mentioned above. That's the reason Ioannidis' numbers have such a large range. In places like New York City (which has just admitted that half its fatalities were in nursing residents) it is likely that many older folks and those already very ill were infected. In Florida they did a much better job with nursing homes so their IFR is lower. That is confirmed by the serologic data for these two areas.
ReplyDeleteI am assuming that people who comment can actually read. You can read the preprint yourself if you are really interested.
Sarg, you are a hateful old man. Calling people nasty names is what haters do.
What I really hate is when the prey is cornered and all they have to show is a Giant Douche or a Turd Sandwich.
ReplyDeleteNEWSFLASH: We have known from the get go that the elderly are very disproportionately affected. Seriously. Knew. That. Already.
I also tend to hate really stupid people. Arguments from authority notwithstanding.
So, Dr. Stache NoLockdown is the only author on that so-called paper? Everyone else has since run for them their hills so to speak. As in, they now know better then to coauthor with Dr. Disco.
I'd also say that Dr. No looks as if they have already been in a one year lockdown of their own doing, kind of needs a major makeover rather badly. Really needs to ditch dat 'do. With regards to that 'do the 70's are calling and they want it back. With regards to that 'stache the '80's are calling and they also want it back. With regards to those suits, see '70's request above.
Oh and have a nice day.
This part of that POS paper is rich ...
ReplyDelete"Moreover, even in these locations, the IFR for non-elderly individuals without predisposing conditions may remain very low. E.g. in New York City only 0.6% of all deaths happened in people <65 years without major underlying conditions.29"
The latest reference 29 (2020-05-16 dated 2020-05-17) ...
https://www1.nyc.gov/assets/doh/downloads/pdf/imm/covid-19-daily-data-summary-deaths-05172020-1.pdf
S-o-o-o-o-o-o-o-o-o-o-o, it would appear that 99.4% of NYC is already sick with things like ...
1Underlying illnesses include Diabetes, Lung Disease, Cancer, Immunodeficiency, Heart Disease, Hypertension, Asthma, Kidney Disease, GI/Liver Disease, and Obesity.
Hypertension (HTN or HT), also known as high blood pressure (HBP) ...
https://en.wikipedia.org/wiki/Hypertension
So hypertension is a so-called "major underlying condition"? I don't think so!
I smell a rat, a buzzard beaknosed rat, they certainly present themselves as ratlike in appearance, Dr. Arat Face. Heck, I expect 50+ percent of the US to present with one of those so-called "major underlying conditions". Such a joke of an idiot is being foisted on the US via Fixed Noise, this person is nothing more than a fraud and a liar.
Dr. P. Nuthead does it again, classic crap straight from its own pooper.
In Dr. A. Nal's mind "Underlying Conditions" become so-called 'major underlying conditions' how much movement of the goal posts will this ilkster do to satisfy their own confirmation biases. Not a question, mind you, just a statement of fact.
Adult Obesity Facts
ReplyDeleteObesity is a common, serious, and costly disease
The prevalence of obesity was 42.4% in 2017~2018. [Read CDC National Center for Health Statistics (NCHS) data brief]
https://www.cdc.gov/obesity/data/adult.html
Facts About Hypertension
ReplyDeleteNearly half of adults in the United States (108 million, or 45%) have hypertension defined as a systolic blood pressure ≥ 130 mm Hg or a diastolic blood pressure ≥ 80 mm Hg or are taking medication for hypertension.3
https://www.cdc.gov/bloodpressure/facts.htm
Diabetes Quick Facts
ReplyDeleteMore than 34 million people in the United States have diabetes, and 1 in 5 of them don’t know they have it.
https://www.cdc.gov/diabetes/basics/quick-facts.html
Chronic Kidney Disease in the United States, 2019
ReplyDelete15% of US adults—37 million people—are estimated to have CKD.
https://www.cdc.gov/kidneydisease/publications-resources/2019-national-facts.html
Asthma
ReplyDeleteNumber of adults aged 18 and over who currently have asthma: 19.2 million
Number of children under age 18 years who currently have asthma: 5.5 million
https://www.cdc.gov/nchs/fastats/asthma.htm
Heart Disease Facts
ReplyDeleteAbout 18.2 million adults age 20 and older have Coronary Artery Disease (about 6.7%).
https://www.cdc.gov/heartdisease/facts.htm
Chronic Diseases in America
ReplyDelete6 in 10 Adults in the US have a chronic disease
The remaining 40% are morbidly obese just like Small Hands. OK I made that one up.
4 in 10 Adults in the US have two or more chronic diseases
https://www.cdc.gov/chronicdisease/resources/infographic/chronic-diseases.htm
Young,
ReplyDelete"The answer of course is very easy. IFR will be very dependent on the age structure of those infected as I mentioned above"
But this is no answer at all. Regardless of the age structure infected, the total mortality is a lower bound on the IFR.
Sure, there are different mortality rates according to age.
But nevertheless, the recorded mortality is a lower bound.
Ionaddis' tortured attempts to argue out of this in the paper don't show your hero in a good light.
RE EFS: "global IFR of 1.04% (CI: 0.77%,1.38%)."
ReplyDeletehttps://www.medrxiv.org/content/10.1101/2020.05.11.20098780v1
US and UK will likely be higher, due to age distribution and fraction of overweight and obese.
Why are you still modeling with 0.75%?
Aha! I see your medrxiv paper and raise you a medrxiv meta-analysis!
ReplyDeletehttps://www.medrxiv.org/content/10.1101/2020.05.03.20089854v2
"The meta-analysis demonstrated a point-estimate of IFR of 0.75% (0.49-1.01%)"
It was, I admit, something of a coincidence that their result (posted in early May) came out to within a gnat's crotchet of our prior of 0.75% (0.5-1.0%) that I adopted back at the start of April. I like to think I've just got impeccable judgment but I fear that chance might have played a role :-)
Another answer is that since I am demonstrating for the purposes of forecasting, I wanted to stick with my state of knowledge as it was rather than going back and nudging the model towards the answers I wanted. No cheating through post-hoc model nudging to make it look good! I could change it now as I've written it up into a paper. Maybe I should go for 1%, it was my original instinct. Though unless I use case data it really doesn't matter at all until we get close to herd immunity.
JA,
ReplyDeleteYou were right in the assertion of delay vs action wrt lockdowns according to this CU study ...
Differential Effects of Intervention Timing on COVID-19 Spread in the United States
Assessing the effects of early non-pharmaceutical interventions1-5 on COVID-19 spread in the United States is crucial for understanding and planning future control measures to combat the ongoing pandemic6-10. Here we use county-level observations of reported infections and deaths11, in conjunction with human mobility data12 and a metapopulation transmission model13,14, to quantify changes of disease transmission rates in US counties from March 15, 2020 to May 3, 2020. We find significant reductions of the basic reproductive numbers in major metropolitan areas in association with social distancing and other control measures. Counterfactual simulations indicate that, had these same control measures been implemented just 1-2 weeks earlier, a substantial number of cases and deaths could have been averted. Specifically, nationwide, 61.6% [95% CI: 54.6%-67.7%] of reported infections and 55.0% [95% CI: 46.1%-62.2%] of reported deaths as of May 3, 2020 could have been avoided if the same control measures had been implemented just one week earlier. We also examine the effects of delays in re-implementing social distancing following a relaxation of control measures. A longer response time results in a stronger rebound of infections and death. Our findings underscore the importance of early intervention and aggressive response in controlling the COVID-19 pandemic.
https://www.medrxiv.org/content/10.1101/2020.05.15.20103655v1
I did an analysis demonstrating Ioannidis’ statements about IFR because its quite obvious that apparent values will vary over a large range depending on the risk groups infected. That’s why the estimates from serological studies including demographic information are the best ones.
ReplyDeleteI will start with Ferguson’s age cohort IFR estimates. Virtually every serologic study in the US shows his IFR’s are at least a factor of 2 too high. This gives me the following values. I have combined the 0-9 and 10-19 cohorts and the 20-19 and 30-39 cohorts.
Age cohort. IFR. % of US population
1. 0-19 0.002% 27%
2. 20-49 0.0275% 28%
3. 50-59 0.3% 14%
4. 60-69 1.1% 14%
5. 70-79 2.5% 11%
6. 80-90 4.6% 4.2%
Total IFR: 0.67%
Its now easy to do some calculations on apparent IFR’s depending on the age profile of those infected. For reference, in the US, expected mortality is about 2,840,000 per annum.
Scenario. #0
Age cohort % infected. Fatalities. Infections
1. 10% 2282 8,900,000
2. 20%. 5,082 18,500,000
3. 30%. 41,580 13,900,000
4. 40%. 203,280 18,500,000
5. 60%. 544,500 21,780,000
6. 80%. 510,048 11,088,000
Totals 1,306,772 92,668,000
Apparent IFR: 1.41%
Scenario. #1
Age cohort % infected. Fatalities. Infections
1. 10% 2282 8,900,000
2. 20%. 5,082 18,500,000
3. 30%. 41,580 13,900,000
4. 35%. 177,870 16,200,000
5. 40%. 370,260 14,520,000
6. 45%. 255,042 5,544,000
Totals 852,116. 77,564,000
Apparent IFR: 1.10%
Scenario. #2
Age cohort % infected. Fatalities. Infections
1. 40% 7128 35,640,000
2. 30%. 7,623 27,720,000
3. 20%. 27,720 9,240,000
4. 15%. 69,300 6,300,000
5. 10%. 90,750 3,630,000
6. 5%. 31,878 693,000
Totals 234,399. 76,593,000
Apparent IFR: 0.31%
This also demonstrates the imperative to protect nursing homes from infection. It appears in the US that 40% of all fatalities have taken place in residents of these homes. Some governors like DeSantos in Florida did a good job. Others in New Jersey, New York, and Pennsylvania did a terrible job and cost tens of thousands of lives. This also explains the apparently higher IFR in these locales and the much lower IFR in Florida.
CFR’s are much more uncertain because of massive differences in rates of testing. That’s why I doubt Sarg’s hateful old man reference, despite the use of a “novel” statistical method.
Ioannidis is aware of all this and is attempting to correct his numbers based on the available data on age structure of those tested. So far the only critique I’ve seen was on the garbage twitter forum. More work needs to be done. However, I tend to trust someone with no political motivation and with scores of collaborators and a sterling reputation more than outsiders who know little or anonymous internet hacks such as those who often comment here and on other blogs.
I'd be happy to correct these figures if there are arithmetic errors.
Yes James, others have pointed to this paper. It's vastly inferior to later work. 4 of the studies are model studies. Most of the others are using small early data sets.
ReplyDeleteYoung,
ReplyDeleteAre you still claiming that IFR is lower than total mortality?
Or just evading the question?
Another CFR estimate
ReplyDeletehttps://www.npr.org/sections/health-shots/2020/05/28/863944333/antibody-tests-point-to-lower-death-rate-for-the-coronavirus-than-first-thought
TLDR: between 0.7% and 1.2%
Note that the Indiana's infection fatality rate 0.58% has a significant number of still infected, and death lags infection.