
Cambridge research team estimates 12% of England has been infected already - gwd
https://www.mrc-bsu.cam.ac.uk/now-casting/
======
gwd
Other highlights:

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/](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".

~~~
gerdesj
0.024% is 9,100 people.

[https://www.ons.gov.uk/peoplepopulationandcommunity/populati...](https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/articles/overviewoftheukpopulation/august2019)

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.

~~~
arcticbull
> 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.

~~~
gerdesj
The 10,000 are likely to be mostly additional deaths, over and above driving
casualties, 'flu sufferers etc.

We are already getting "additional death" scores here which is a sort of
measure by proxy of the effect of SARS-CoV-2. There is a standard way of
counting this, at least across Europe (and pre-Brexit UK!) There is of course
a fair amount of variation but having COVID-19 is something to avoid if you
can.

It is going to take some really funky stats to work out the real effect
because there is less 'flu already in say Aus due to less travel and N
hemisphere residents bringing it down south as they head into autumn/winter.
Air quality is up nearly everywhere so COPD might be mitigated somewhat. Less
road travel means less accidents. However suicides might be up and at least
here in the UK there is a fairly well documented lack of people going to A&E
(ER) when they should out, of fear or being stoic. Many other treatments have
been put on hold.

SARS-CoV-2 has turned the world upside down. I do look for bright sides eg the
huge social WFH experiment seems to be a huge success and opportunity.
However, additional people are dying in rather unpleasant ways that they would
not have done less than six months ago.

------
notahacker
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.

[1]yes, caveats apply

~~~
joshuahedlund
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.

~~~
gwd
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%).

------
redis_mlc
This is interesting ...

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...](https://www.sccgov.org/sites/covid19/Pages/dashboard.aspx#cases)

~~~
Ovah
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.

------
buboard
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?

~~~
tree3
> Why trust a model if you can do a serology study instead?

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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hanoz
Sounds more plausible than the 50% estimate put out _two months ago_ by
Oxford.

------
LatteLazy
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.

------
martythemaniak
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.

~~~
luckylion
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%?

~~~
gwd
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.

------
hacker_9
Shame we can't prove it until they start randomised testing.

~~~
exdsq
I was part of a randomised testing survey in Oxfordshire which involved an
antibody serology test and swab tests. Hopefully the results come out soon (I
took part last week).

