
CA governor projecting 25.5M COVID19 cases in CA in 8 weeks [pdf] - jader201
https://www.gov.ca.gov/wp-content/uploads/2020/03/3.18.20-Letter-USNS-Mercy-Hospital-Ship.pdf
======
jdminhbg
As pointed out below[0], this is a sensationalist headline and should be
changed. This is the projection if _no measures_ were taken.

Which makes sense: if 56% of the population is going to contract coronavirus
in the next eight weeks, then the lockdown is pointless. You're nearly to herd
immunity at that point, why cripple the economy if it doesn't even make a dent
in the transmission rate.

[0]:
[https://news.ycombinator.com/item?id=22634268](https://news.ycombinator.com/item?id=22634268)

~~~
jader201
> As pointed out below[0], this is a sensationalist headline and should be
> changed.

The title was based on the entirety of the linked content — the letter from
the CA governor to the president — which included no context around the
numbers being based on no measures being taken.

~~~
jdminhbg
Understandable, but since there's been clarification, I think that should be
reflected in the title.

~~~
jader201
I would disagree that the title should be changed, since the linked content
does not reflect the additional context you’re referring to.

I suppose a more fully-qualified title might append “in letter to the
president”.

But appending “if no measures are taken” is not accurate, since this article —
his letter to the president — doesn’t include this context.

Saying the title is sensationalist is equivalent to saying the letter is
sensationalist.

And if that is the case, the most you could say is a sensationalist title
accurately represents a sensationalist letter.

~~~
jdminhbg
Generally the HN style has been to actively editorialize to tone down
sensationalism, even if the linked title or content is sensationalist.

~~~
sneak
I think GP was suggesting that the letter is itself not sensationalist, and
thus neither is the title as it accurately reflects the content linked, and
thus it is fine as-is.

I agree, it is a reasonable statement and reasonable projection (within an
order of magnitude) that reflects the gravity of the situation. A lot of
people don’t seem to realize just how big this is about to become.

~~~
_jahh
i think the measures most places have taken are going to reduce the spread
significantly(USA, 2000 instead of 2 million deaths), i pray.

------
eganist
Swag maths on the business-as-usual scenario incoming, bound to be very wrong:

3.4% mortality rate among those presenting symptoms. (via WHO)

As low as 17.9% of cases asymptomatic:
[https://www.forbes.com/sites/brucelee/2020/03/18/what-
percen...](https://www.forbes.com/sites/brucelee/2020/03/18/what-percentage-
have-covid-19-coronavirus-but-do-not-know-it/#42991ddf7e90)

Of the symptomatic cases, 80.9% are mild ([https://www.sciencealert.com/large-
chinese-study-finds-most-...](https://www.sciencealert.com/large-chinese-
study-finds-most-coronavirus-infections-are-mild)) and we're assuming only the
ones that present risks are being tested.

So if the 25.5m figure stands correct, we're looking at what, a range of
195,000 to 695,000 possibly passed on in california before June depending on
whether you apply it to not-mild (19.1%) cases v. all symptomatic (82.1%)
cases?

I can't find any concrete sources on how anyone is calculating current
mortality rates for the bug, but:

1\. that swing is _unfathomable_ to me

2\. those numbers are _unfathomable_ to me. Especially once extrapolated to
the whole country assuming 56% of the nation contracts it.

~~~
njarboe
This article[1] states that our best natural experiment for COVID-19 is the
Diamond Princess cruise ship and its quarantine passengers. From that he
estimates the the mortality rate is between 0.05% and 1%. That is, we don't
really know what the rate is. The WHO giving a number with two significant
digits implying some reasonable certainty about the number, is very deceiving
and very likely just plain wrong.

[1][https://www.statnews.com/2020/03/17/a-fiasco-in-the-
making-a...](https://www.statnews.com/2020/03/17/a-fiasco-in-the-making-as-
the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-
data/)

By:John P.A. Ioannidis professor of medicine, of epidemiology and population
health, of biomedical data science, and of statistics at Stanford University
and co-director of Stanford’s Meta-Research Innovation Center.

~~~
bugzz
0.05% is just ridiculous. That's half the death rate of the flu, so the only
way he can justify a number like that is if he believes we are missing the
VAST majority of all cases (due to them being mild) and only seeing the severe
ones / deaths. But there's a simple check to this - how many deaths does Italy
have per day in a bad flu season vs how many Covid-19 deaths per day are they
having now? Worst flu year on record I could find for Italy was 25,000 deaths
(average year ~15,000 deaths). Spread those over 3 months for flu season, and
that's 277 deaths per day. Italy had 475 deaths yesterday from Covid-19. Even
if you assumed EVERY Italian has contracted Covid-19, death rate would have to
be at least 2x the flu. Now, think about how the majority (80%?) of deaths in
Italy are in the Lombardy region, which has maybe 1/4 the population, and thus
1/4 the flu deaths per year. Now it's clear Covid-19 must have fatality rate
at least 5-6 times worse than the flu, even assuming every Italian has it...

Edit:

Flu mortality stats for Italy:
[https://www.sciencedirect.com/science/article/pii/S120197121...](https://www.sciencedirect.com/science/article/pii/S1201971219303285)

Covid-19 deaths per day in Italy:
[https://www.worldometers.info/coronavirus/country/italy/](https://www.worldometers.info/coronavirus/country/italy/)

~~~
609venezia
I think Ioannidis included that very low number as an example of how
ridiculous the statistics can look when using the Diamond Princess as a sample
and factoring in the relevant sources of uncertainty.

<<Projecting the Diamond Princess mortality rate onto the age structure of the
U.S. population, the death rate among people infected with Covid-19 would be
0.125%. But since this estimate is based on extremely thin data — there were
just seven deaths among the 700 infected passengers and crew — the real death
rate could stretch from five times lower (0.025%) to five times higher
(0.625%). It is also possible that some of the passengers who were infected
might die later, and that tourists may have different frequencies of chronic
diseases — a risk factor for worse outcomes with SARS-CoV-2 infection — than
the general population. Adding these extra sources of uncertainty, reasonable
estimates for the case fatality ratio in the general U.S. population vary from
0.05% to 1%.>>

Mainly I think he wants more testing, but people are cherry picking his
argument to try to downplay the risk.

His key point from the overall piece is something like "we need more testing,
including randomly sampled data. Let's not give up on testing while we ratchet
up the countermeasures."

Evidence:

Second graph- <<At a time when everyone needs better information, from disease
modelers and governments to people quarantined or just social distancing, we
lack reliable evidence on how many people have been infected with SARS-CoV-2
or who continue to become infected. Better information is needed to guide
decisions and actions of monumental significance and to monitor their
impact.>>

in the middle- <<The most valuable piece of information for answering those
questions would be to know the current prevalence of the infection in a random
sample of a population and to repeat this exercise at regular time intervals
to estimate the incidence of new infections. Sadly, that’s information we
don’t have.>>

concluding graph- <<If we decide to jump off the cliff, we need some data to
inform us about the rationale of such an action and the chances of landing
somewhere safe.>>

\---

Coming from a different angle, the latest estimate from Wuhan is 1.4% (.9-2.1)

[https://www.nature.com/articles/s41591-020-0822-7?mod=articl...](https://www.nature.com/articles/s41591-020-0822-7?mod=article_inline)

~~~
bugzz
Well given how widely people have carried his "0.05%" as lower bound, I'd
imagine he'd have said something if he didn't really think it was a
"reasonable estimate for the case fatality ratio in the general U.S.
population", as he said.

I do agree though that more data is critical. Although we have far more than
enough evidence now to know that we need to act strongly at least for now.

------
fyp
Why did we give up on containment?

China and South Korea have shown that it's possible. China capped out at only
100k infected for a population of 1.4 billion.

Aiming to let 56% of your population get infected of which more than 3% will
die is NOT the solution.

China's strategy seems simple enough. Close off borders of a region, stamp out
all existing cases with aggressive testing, then keep the region at 0 cases by
requiring mandatory 2 week quarantine before letting anyone in. Do this one
region at a time until your country is all clean. Now their biggest problem is
teaching the rest of the world this strategy.

~~~
jmcgough
We have an extreme wealth disparity with many having no savings and no social
safety net. We can't force everyone to stay home for months, the economy would
collapse.

China maintained draconian levels of control - citizens had cards with their
risk level, and were tested frequently when they went to a public space. Have
symptoms or some reason to believe you might be infected? You were quarantined
from your family and not released until 4+ hours later. If they needed to be
kept overnight, they had special hotels to quarantine people in. Citizens
there actually listen to what the government tells them to do, and dissent is
stamped out. In the states, a lot of people openly don't trust the government.

If we tried to control peoples' lives like that, our citizens would riot.
You'd have armed citizens refuse to leave their homes.

They also did things that are unimaginable here - they built an entire
hospital in 10 days. They have infrastructure and equipment from SARS that
they were able to mobilize.

We aren't China, and we can't accomplish what they've done. Not in eight
weeks. We are not prepared for this.

~~~
threeseed
> We can't force everyone to stay home for months, the economy would collapse.

You could. Just pay everyone $1000/month until it ends.

~~~
rnotaro
And what do you pay the businesses that are closed?

~~~
bb88
We've long been pursuing the supply side economics for far too long. Massive
tax cuts and bailouts. Banks came back rather quickly after 2008. The
citizens, well, it took a while.

I'm beginning to think that if businesses can't survive for 6 months in a
catastrophe, maybe it's better that they die. Moral hazard, you know.

If businesses die, you still have the people to build more businesses. If
people die, you'll have neither.

~~~
RHSeeger
That's an awful lot of people's life savings in their small business that goes
poof. A lot of the businesses that can't survive are leaving behind people
that are not capable of bringing them back, and people that won't be employed
there afterwords.

~~~
bb88
So a lot of people's life savings have gone poof, not just small businesses.

------
partiallypro
I'm not trying to throw a ton of water on this, but this is a political
document. Is it possible that they've put out this large number to justify
their heavy handed response when it falls well short of that? Because people,
once the economic impact if fully felt, are going to want a justification for
their sacrifice.

~~~
rectang
Take a look at the graphs on this page, particularly "World, Confirmed Cases"
and "US States, Confirmed Cases Per Million Inhabitants":

[http://nrg.cs.ucl.ac.uk/mjh/covid19/](http://nrg.cs.ucl.ac.uk/mjh/covid19/)

We are not near an inflection point yet.

~~~
cheerlessbog
Great link thank you - it looks like if the US follows China, is it nearly two
months from the peak, with Washington state about 10 days closer. If China is
even comparable. We will know more when Italy reaches its peak.

------
ComputerGuru
I don’t think it’s honest for these reports _that accompany executive decrees_
to not take into account the reality on the ground.

This report assumes “business as usual” whereas the reality is people
absolutely _are_ social distancing. Therefore any data submitted to the public
as the rationale behind a decision should reflect that: the numbers report
should indicate the projection based off of the current Bay Area shutdown and
the general self-isolation and self-distancing that is in effect to make its
point.

------
tanilama
This doesn't make sense right? As of today, California has 1000 cases.

Even assume the infections double every 4 days, in 8 weeks that gives us: 16.4
millions.

And currently Santa Clara county is in a virtual lockdown, I am wrapping my
head how could we reach this number really?

~~~
jkachmar
I’m concerned that there is a vast disparity between the number of confirmed
cases and the actual number of contracted cases (esp. asymptomatic).

NY has tested the largest number of people out of all states and has >4000
confirmed cases as of March 19th, and it’s _still_ being undertested for
relative to countries like South Korea.

------
dis-sys
There is something I really don't understand - if most people just stay at
home and cut all non essential public activities to the minimum, how 50% of
the population could still get infected?

~~~
nostromo
We only have lagging indicators by about a week or more.

It takes people at least a day, and usually a few days to get sick. A little
while longer for them to go to the hospital (if they go at all -- most don't
because it's usually mild). Then testing, if it happens at all, takes a few
days.

------
m0zg
It's pretty clear that the current policies are misguided, IMO. The vast
majority of those dying are the elderly and people with pre-existing
conditions, most of the time, both. THOSE people should be locked down tight
and they should receive testing and resources if we are to minimize the death
toll. We're also fortunate in the sense that only 16% of US population is over
65 years old. Germany and especially Italy are nowhere near this lucky.

Instead, we're spreading limited resources super thin, and fucking up the
economy in the process for everyone. Seems like offering these vulnerable
populations temporary shelter and supported isolation for a month would do a
heck of a lot better job than locking down everything _and not providing any
support to the elderly and those with pre-existing conditions_. And you could
easily offer such isolation: millions of hotel rooms are currently empty, and
hoteliers are hurting for cash, which bodes well for getting those rooms (and
room service to go with it) at cost.

Case in point: as of March 17, only 17 people of those who died in Italy were
under the age of 50. That's out of something like 2800. And the median age of
those dying was 80.5 years. Same stats on the ship: all of the deaths were
among 70-80 year olds. This shows you who's really at risk in a Western-style
medical system in a developed country.

~~~
jkachmar
Please see the Imperial College London report, recently released, for a model
that contradicts what you’re suggesting [0].

In particular, see Figure 3 for a direct refutation of the idea that simply
applying suppression techniques to the infected or primarily-at-risk groups is
adequate.

Anything other than immediate and severe suppression techniques puts us over
ICU capacity in the next few months, and the estimated number of deaths
skyrockets into the millions.

[0] [https://www.imperial.ac.uk/media/imperial-
college/medicine/s...](https://www.imperial.ac.uk/media/imperial-
college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-
modelling-16-03-2020.pdf)

~~~
m0zg
I might be misreading this, but see graph on page 8 of the report. What I'm
proposing is the blue curve.

~~~
jkachmar
Yes, I’m saying that the figures on page 10 imply that the blue curve (on its
own) is not effective enough to avoid critically overwhelming the hospital
system in the UK in the short term.

The guidance towards the measures you see now (nonessential workplace
closures, social distancing, restrictions on movement and activity) are what
seem to be recommended throughout the rest of the report to suppress the
catastrophically high death tolls.

If you read further to Figure 4 (page 12) you’ll see a model for “adaptive
triggering” of suppressive techniques (basically staggering to allow a
resumption of activity before starting again) which would need to be in place
until a vaccine has been successfully verified as safe and inoculation has
started.

EDIT:

“Perhaps our most significant conclusion is that _mitigation is unlikely to be
feasible_ without emergency surge capacity limits of the UK and US healthcare
systems being exceeded many times over. [...]

In addition, even if all patients were able to be treated, we predict there
would still be in the order of 250,000 deaths in GB, and 1.1-1.2 million in
the US. [...]

We therefore conclude that _epidemic suppression is the only viable strategy_
at the current time.”

Emphasis mine.

------
sigsergv
I don't believe they will have 26M tests in 8 weeks.

~~~
ccktlmazeltov
right, if you don't get tested then do you really have coronavirus?

~~~
ingsoc79
Schrödingerona's virus

------
aazaa
If the governor is assuming exponential growth, what's the doubling time? From
the formula:

    
    
        N(t) = N0*2exp(t/Td)
    

where:

\- N(t) is the final count (25.5M)

\- N0 is the initial count (1040 according to Johns Hopkins)

\- t is the time (8 weeks)

\- Td is the doubling time (TBD)

[https://en.wikipedia.org/wiki/Doubling_time](https://en.wikipedia.org/wiki/Doubling_time)

Solving for Td:

    
    
        Td = t/(ln(N(t)/N0)
    

Plugging in the numbers, I get Td = 0.8 weeks, or 5.6 days.

~~~
mNovak
Which I think is roughly what the numbers have been showing so far--debatably
an upper bound, given the under-availability of testing.

------
tunesmith
Easiest way to get this number: estimate actual/confirmed case ratio is 10x,
and estimate a 5-day infection doubling time. That hits the projection almost
exactly.

------
grej
There are 1030 known positive CA cases right now according to the JHU map.

The governor's letter is using a doubling time of 4 days, but there's good
reason to believe this 4-day time is due to recently increased testing.

If the governor instead takes the best-guess mean doubling time from several
epidemiological studies[1] of 6.4 days, then, you would have to assume there
are are 38.5 actual cases for any one tested positive case right now in order
to get to 25.5M.

(25.5 * (10 ^ 6)) / (1030 * (2 ^ ((7 days/wk * 8 wk) / 6.4 days_to_double))) =
38.46742327016

So to get there, the governor has to be assuming that the current measures
being put in place will do absolutely nothing, and also assuming almost actual
40 cases per real case, which is quite possible.

If you assume the 4-day doubling time they quoted will continue for 8 straight
weeks, and the number of current cases is accurate (again, probably not -
probably an underestimate), you still just get to 16.9M cases.

Seems to me the more likely situation is that: (1) there are more cases than
we think right now (Maybe not 40x, but maybe 10-20x?). (2) the doubling time
will be affected quite A LOT by the measures being put in place. It might drop
the R0 to close to 1.

In that case, I would expect the enacted measures to at least half the R0
starting from this week, beginning of a flattening of active case count
starting at this point.

That new R0 would hugely affect doubling time. But even conservatively
estimating that R0 only goes down by 25% vs 50%, in 8 weeks time the
projection of cases in CA would still be reduced by almost 60x.

TLDR - Best guess 8 weeks from now, CA has between 400k-1M cases. But not
anything close to 25.5M. You can downvote me in 8 weeks if I'm wrong.
Hopefully, the real number is closer to mine than to Gov. Newsom's.

[1]
[https://www.thelancet.com/journals/lancet/article/PIIS0140-6...](https://www.thelancet.com/journals/lancet/article/PIIS0140-6736\(20\)30260-9/fulltext)

~~~
mid
“Any statistics can be extrapolated to the point where they show disaster” —
Thomas Sowell, 1996

~~~
grej
Also - “If you torture the data long enough, it will confess.”

― Ronald H. Coase

~~~
TMWNN
Also "If something cannot go on forever, it will stop." —Herbert Stein

------
blackrock
At what point will they capitulate and give up?

This sounds like they have completely given up on containing it. We are now
left to our own fate.

------
creato
Is this the projection _with_ the lockdown measures that are in place?

~~~
k1t
No, the projection assumes no measures at all are taken - not even the ones
that already have been.

"Newsom’s request said 56 percent of California’s population, a whopping 25.5
million people, would be infected over an eight-week period. A governor
spokesperson later clarified the projection included zero mitigation efforts
such as the Bay Area’s shutdown of non-essential businesses to decrease
contact between residents."

[https://www.ocregister.com/2020/03/19/gov-
newsom-56-percent-...](https://www.ocregister.com/2020/03/19/gov-
newsom-56-percent-of-californians-projected-to-be-infected-with-coronavirus-
in-8-week-period-2/)

------
throw03172019
Politician math != math

------
xbhdhdhd
I hope no one projects COVID19 onto anyone. What a rude man. Hope he
reconsiders.

------
zaroth
I’m not saying there isn’t a report on Gavin’s desk with a bunch of lines on
it, one of which extends to 25.5M in 8 weeks.

Yes, if you double 1,000 14 or 15 times you get to 25.5M.

The problem is that the population of California is 40 million. Even with
basically unmitigated spread, your clusters will slow growth simply due to
lack of new available uninflected contacts.

Going from 1,000 people to 63% of your population in 8 weeks is frankly not a
serious projection. Keep in mind this is a political document, not a
scientific paper.

~~~
btilly
We have 1000 confirmed cases when most people who have symptoms can't get
tests to confirm whether they have it.

That is a long way from having only 1000 cases at present. We are at a
significant multiple of that. Estimates of Wuhan at a similar point suggest
that they had 7x official figures. We are likely about 5000-10000 in reality.

Now what is the growth? Here is a trivial sanity check. From
[https://www.worldometers.info/coronavirus/coronavirus-
cases/...](https://www.worldometers.info/coronavirus/coronavirus-cases/#case-
tot-outchina) on a log scale it is clear that reported cases worldwide have
been growing by a factor of 10 every 2 weeks. Projecting that out for 8 weeks
starting with 1000 gives you 10 million. Starting with our likely 5000-10000
we hit all of California. At which point the limit is not that exponential
growth doesn't get us there, but rather that the exponential curve hits
saturation and breaks down. At which point you fit to other models based on
past epidemics to get an estimate of where it tops out.

Now 63% is in line with projections we've seen for weeks. That's 25 million
people. if we believe the recent Lancet estimate that the fatality rate is
0.5-1.5% of people who get it, that is 1.25-3.75 million dead Californians. If
we believe more conservative estimates, that's still a lot of dead people no
matter how you slice it.

~~~
zaroth
A good basic sanity check is to look at the log-graph of total cases in any
given country, not the whole world.

Take Italy for example. You’ll see immediately the growth is not a constant
exponent. Nor would even simple theoretical models expect it to be. It’s a
logistics curve, or “S” curve, which means the exponent starts out at the
highest value (once it takes off) and then is constantly decreasing over time.

What that looks like in the logarithmic charts is a line which starts at a
high slope and flattens over time.

See, for example:
[https://www.worldometers.info/coronavirus/country/italy/](https://www.worldometers.info/coronavirus/country/italy/)

