Look at the "Deaths incidence" tab of the graphs at the bottom to see actual deaths with the curve-fit model.
EDIT: Meant to include in my initial "highlights" comment:
Estimated "peak" daily infections was 23 March, with 500k infections. Estimate for daily infections as of 10 May closer to 10k; estimated country-wide Rt at 0.75, still well below 1.
Bonus highlights: Method seems to be from this 2009 paper, "Bayesian modeling to unmask and predict influenza A/H1N1pdm dynamics in London":
Not equipped to evaluate their method, really; but if it's reasonably accurate, then the UK is not currently really headed towards "natural herd immunity".
As a 55 and over with a dad who's 85 and over one can excuse me for not being on the herd immunity train.
I also have friends who've gotten sick and suffered impaired health. Figure the 80/20 rule. 80 people suffer impaired health for every 20 that die. We're talking about 1 in 50 having damaged health.
> I'm not sure I call something like 10,000 dead a highlight.
Not on an individual level of course, but on a population scale, it can be. That level would be comparable with driving, with the flu and so on for that demographic.
The world will never be risk-free, and "exceeds expectations" can be a highlight even if the expectations were low.
That isn’t likely to change the deaths under 45’s by much if it all as the ONS figures only a additionally include out of hospital deaths primarily form care homes and hospices in which the average age will be well above 45.
If you remove comorbidities in the under 45 pool the rate drops even further for the most part if you are under 45 and healthy your chances of dying from covid-19 are exceedingly small.
Looks optimistic when large scale serological testing in Spain, which has a higher per capita death rate[1] suggest prevalence under 5%, and under 12% in the epicentre of the disease in Madrid.
If you take the low end of the prevailing IFR estimates (~0.5%), the 5700-odd deaths would mean an infection rate of ~12% in London (population ~9M). If you assume 40% of deaths are not properly reported as COVID-19, that gets you to around 20%. But NYC, with a similar population, has had three times as many confirmed deaths, and antibody tests there suggest a total infection rate of 20%. LA antibody tests indicated something like 4%. I'm betting that when antibody tests are done, London will be lower than 20%, and the other areas are likely at the low end, or below, this estimate of 5-14%.
Yes, it would be one thing if this was an antibody/serotological testing result and we could add it to the mix of similar studies, like the ones suggesting ~1.1% rate in Spain (with 5% infected) or ~0.8-1.0% rate in NYC (with 25% infected). But this is not empirical data; it's pure modeling.
It's worth pointing out that the overall IFR is estimated at between 0.49% and 0.83%, with 0.63% being the median. That's only a bit lower than your NYC quote, and still about twice the IFR from the study from Germany (0.34%).
Potentially, but it's not unheard of for a disease to be differently severe in different places for inscrutable reasons. (Of course, that also does suggest those of us outside of England shouldn't generalize the findings too far.)
It's not necessarily all that inscrutable either. We know that a lot of deaths are in places like nursing homes, and that measures which reduce spread amongst the general population aren't necessarily going to be as effective at preventing spread in nursing homes since those obviously have to be staffed, etc.
Without having a source to back it up, I'm guessing that a month ago tests were more scarce. So you had to have a strong clinical indication to get tested.
As evidenced in this epidemic, epidemiological modeling is either not very good or overconfident. I mean, all models are wrong, but theirs have also been useless. Why trust a model if you can do a serology study instead?
> Why trust a model if you can do a serology study instead?
I think the earlier tests were pretty bad, and the newer tests are expensive, but also this kind of modelling is used for other respiratory illness deaths (flu, flu and pneumonia, rhinovirus, adenovirus) so they want to start developing the models to be used in those annual respiratory illness death reports.
It would be really cool if we could confirm some of these estimates. Like maybe if we used tests? The government could run a program to test people. Then they’d know. And they wouldn't need to keep guessing. It wouldn't even need to be everyone, just an appropriate sample.
Nah, fuck it, let's just keep testing MPs and guessing about what to do next.
Currently around 500 deaths/ million. If you need ~60% for "herd immunity", that implies they'd get around 2500/1m, or 0.25% of the population. Pretty gruesome.
Meant to include in my initial "highlights" comment:
Estimated "peak" daily infections was 23 March, with 500k infections. Estimate for daily infections as of 10 May closer to 10k; estimated country-wide Rt at 0.75, still well below 1.
Method seems to be from this 2009 paper, "Bayesian modeling to unmask and predict influenza A/H1N1pdm dynamics in London":
Not equipped to evaluate their method, really; but if it's reasonably accurate, then the UK is not currently really headed towards "natural herd immunity".
If I'm reading it right, they report an IFR from 0.49% to 0.81% (95% credible interval). Ballpark population of England is 50 million. Herd immunity at ~70% means over 200,000 deaths at median IFR of 0.63%. Extrapolating to US population of ~350 million is around 1.5 million deaths.
Their normal death rate is ~1%, right? Are we sure that there would be little to no overlap between these groups and they'd end up with a death rate of 1.25%?
There's a ton of information to poke around at the link; but here's their [EDIT] median estimated IFR by age range:
15-24: 0.0032%
25-44: 0.018%
45-64: 0.28%
65-74: 1.8%
75+: 16%
The last one looks similar to the measured death rates by age group in Germany -- i.e., the COVID-19 deaths of 80+ in Germany divided by people tested positive in Germany was around 18% when I looked before, IIRC.
So nearly the entirety of the "1-3% fatality" comes from the fact that it's so incredibly deadly to the elderly.
The overall death rate for 2020 will probably be even below 1%. The old will still die, but the young are no longer driving, smoking, etc and social distancing is preventing other diseases like the flu.
Readit News
Death rate for under-45 is under 0.024%
Look at the "Deaths incidence" tab of the graphs at the bottom to see actual deaths with the curve-fit model.
EDIT: Meant to include in my initial "highlights" comment:
Estimated "peak" daily infections was 23 March, with 500k infections. Estimate for daily infections as of 10 May closer to 10k; estimated country-wide Rt at 0.75, still well below 1.
Bonus highlights: Method seems to be from this 2009 paper, "Bayesian modeling to unmask and predict influenza A/H1N1pdm dynamics in London":
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3215054/
Not equipped to evaluate their method, really; but if it's reasonably accurate, then the UK is not currently really headed towards "natural herd immunity".
I also have friends who've gotten sick and suffered impaired health. Figure the 80/20 rule. 80 people suffer impaired health for every 20 that die. We're talking about 1 in 50 having damaged health.
https://www.ons.gov.uk/peoplepopulationandcommunity/populati...
Figure 8 you can highlight the age group (0-45) and get a summary figure: 37,980,275 people aged 45 or less * 0.00024 = ~9,100
I'm not sure I call something like 10,000 dead a highlight.
Not on an individual level of course, but on a population scale, it can be. That level would be comparable with driving, with the flu and so on for that demographic.
The world will never be risk-free, and "exceeds expectations" can be a highlight even if the expectations were low.
> I'm not sure I call something like 10,000 dead a highlight.
Given that people before were saying the death rate was 2-5%, yes, it is a good thing.
I find it really strange that people in this thread are trying to be mad about a low death rate...
The rate of death for people under 45 is very low. It's going to be more than 0.024% because:
> Deaths which have COVID-19 on the death certificate are included in ONS figures but not here; we are looking into their inclusion.
If you remove comorbidities in the under 45 pool the rate drops even further for the most part if you are under 45 and healthy your chances of dying from covid-19 are exceedingly small.
[1]yes, caveats apply
The positive rate for those tested in the Bay Area started at 10% 2 months ago, but new test in past week are under 2%:
https://www.sccgov.org/sites/covid19/Pages/dashboard.aspx#ca...
Dead Comment
I think the earlier tests were pretty bad, and the newer tests are expensive, but also this kind of modelling is used for other respiratory illness deaths (flu, flu and pneumonia, rhinovirus, adenovirus) so they want to start developing the models to be used in those annual respiratory illness death reports.
Because studies require a lot more time and money, while a model is just on a computer and can be constantly and quickly updated as things change?
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Nah, fuck it, let's just keep testing MPs and guessing about what to do next.
Deleted Comment
Estimated "peak" daily infections was 23 March, with 500k infections. Estimate for daily infections as of 10 May closer to 10k; estimated country-wide Rt at 0.75, still well below 1.
Method seems to be from this 2009 paper, "Bayesian modeling to unmask and predict influenza A/H1N1pdm dynamics in London":
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3215054/
Not equipped to evaluate their method, really; but if it's reasonably accurate, then the UK is not currently really headed towards "natural herd immunity".
Seriously, click the link and look around -- there's a lot of interesting stuff to see.
15-24: 0.0032%
25-44: 0.018%
45-64: 0.28%
65-74: 1.8%
75+: 16%
The last one looks similar to the measured death rates by age group in Germany -- i.e., the COVID-19 deaths of 80+ in Germany divided by people tested positive in Germany was around 18% when I looked before, IIRC.
So nearly the entirety of the "1-3% fatality" comes from the fact that it's so incredibly deadly to the elderly.
Deleted Comment