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.
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.
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.
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.
> ... We project roughly 56 present of our population - 25.5 million people -- will be infected with the virus over an eight week period.
There is no qualification to that statement.
It’s reflective of the actual content of the letter.
We have outside knowledge with respect to the letter that changes how we understand that number, but it has been rhetorically used in the letter just as it is quoted in the title.
Often times things are sensationalist, or out of context, this is not one of those situations.
You better lockdown everyone over 60 during those 8 weeks while everyone else gets infected and recovers then, i.e. you need a lockdown
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...
Of the symptomatic cases, 80.9% are mild (https://www.sciencealert.com/large-chinese-study-finds-most-...) 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.
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.
Flu mortality stats for Italy: https://www.sciencedirect.com/science/article/pii/S120197121...
Covid-19 deaths per day in Italy: https://www.worldometers.info/coronavirus/country/italy/
<<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."
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)
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.
This is entirely possible, and is the conclusion of a different, unrelated paper published today. 
> 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?
This is a good idea, and a reasonable metric, but it's not a good way to compare the CFR, because there are too many confounding factors.
For example, it's possible that the early lockdown in Northern Italy actually increased the number of deaths by expanding the window of exposure to elderly populations (whose younger relatives normally would have been out of the house all day). It's possible that, for some reason, Italians are particularly susceptible to SARS-CoV-2. It's possible that the weather pattern or air quality had some strange impact.
I'm not saying any of these things are true; I'm saying that it's not a great way to compare CFRs or speculate about the number of mild or asymptomatic cases.
So in China the lockdowns stopped the Virus from spreading, but in Italy it increased the spread? If the young are all at home giving it to their grandparents, you think it already spread to almost all young people, at pretty much the same point in time, and then lockdowns started and they gave to elderly who somehow mostly didn't get it before that?
> It's possible that, for some reason, Italians are particularly susceptible to SARS-CoV-2. It's possible that the weather pattern or air quality had some strange impact.
If we are considering these as possibilities than we'd better prepare for the U.S. (or any other country) have genetic predispositions or weather patterns that make it even more deadly here than Italy!
I just think my method shows that barring highly unlikely scenarios, this thing is at least 5x as bad as flu, not a lower bound of 0.5 as bad. So we should act accordingly.
I don't think your method allows any conclusion of the comparison between SARS-CoV-2 and A(H1N1) or whichever flu is in Italy this year.
And it depends what "act accordingly" means. I think it's unwise to take extreme measures like school closings or shelter-in-place, which we know will have their own adverse impacts, without first retracting the flawed science that arrived at the 3.4% CFR and then seeking to replicate the study which I linked above.
I mean, do you think that study is equally flawed? Do you think that the researchers who submitted it for review today simply didn't think to compare the number of deaths yesterday with the mean deaths from flu?
People underestimate how many cases Hubei actually managed to treat. They built two purpose built hospitals where every bed was an ICU and converted stadiums and hotels to centralized quarantine facilities so the less acute cases could be near but not in hospitals but could be rapidly shuttled there if the symptoms got worse. They flew in over 40K+ medical workers from all over China to treat less than 80K cases, 80% of which were "mild" which means 2.5 medical workers per non-mild case.
What we really need is the cohort from China who had hospitalizatable symptoms and were denied any sort of treatment, what the range of outcomes in those cases? Even then, it's not a natural experiment because China is practicing triage, same as Italy, and so we need to compare like to like as much as possible.
If the models are correct at assuming that our hospitals are going to get more than 10X overwhelmed, then this is the real number that matters. What's the rate of death for people who have 0 medical intervention.
The reason why is, if the healthcare system isn't overwhelmed, then the CFR is not an important number because the total number of deaths is small enough that variances in that range are trivia. If the healthcare system is overwhelmed, then any data we get from non-overwhelmed systems, which is all people appear to be using, is utterly bollocks.
If people are suggesting that 70% of people in their country could be infected in a year, then we should be using a CFR closer to 10 - 15% as the true number and that means we could be imagining a world where 7 - 10% of all people are dead by this time next year.
But the specific flaw in the 3.4% number is that the denominator was calculated without any real basis for believing that the number of confirmed cases was close to the number of cases (or that it was similarly close in various regions).
That's the part I want to see revisited, and which is of course the topic of a great deal of discourse over the past 48 hours or so.
It's already been linked elsewhere in the thread, but here's one of the widely-circulated commentaries calling the 3.4% CFR into question (in fact making the case that it's meaningless):
However flu does not overwhelm ICU and there are tangential deaths from lack of available healthcare which might double these numbers. Who knows, but it not going to be insignificant at all.
edit: In fact I see Italy counts flu season from October to February inclusive, so I think my estimate is correct.
Fly deaths aren’t evenly spread out like that. There is a definite flu “peak” which then tails off.
It would be safer to assume that your peak is at a minimum of 2-3x the average.
It is absolutely not ridiculous as a lower bound!
One reason for that is that you cannot examine just one locality. Some will be high, some will be low -- fluctuations are just the nature of statistics. It is necessary to average the hot spots and the cold spots to estimate accurately.
Basically, this is a really hard problem and the error bars are far larger than most people realize, especially in the media.
As I said above, I agree that this argument is plausible. I think your argument is at least as likely to be correct as any other, and probably not too far off the mark for the "true" CFR.
> Italy has a population around ~60 million, law of large numbers makes it impossible to have error bars THAT big
However this is not true. The law of large numbers helps with statistical errors. It does zero, absolutely zero, to control for systematic errors. There are so many factors in play that it is extremely hard to declare anything "impossible" with this pandemic.
I think it goes without saying that the numbers we have (whichever ones you choose) are wrong, even to an order of magnitude or more. But the responsible, constructive way during an emergency to express a contrarian opinion is by identifying facts and crafting reasoned conclusions. That includes doing enough due diligence to have some reasonable confidence that you understand the premises behind the public authorities' responses. For example, the clean data he wants to see might not even exist. Telling a blind man that he's blind isn't helpful; he knows that and is presumably (hopefully) making decisions accordingly, such as keeping a wide berth to any potential hazards.
Here's a small handful of what we do know, independent of the cold, hard, vanilla statistics on SARS-CoV-2 that we'd all like to have: Italy is experiencing a public health crisis, whether justified by the number of deaths or not; two national lawmakers in Iran have died (how many die annually of seasonal flu?); Wuhan was no joke; initial outbreak in the U.S. so far seems to align with its evolution elsewhere. All these things are also evidence that can and should be part of drafting early responses. These aren't population mortality rates, r0, infection fatality rates, or the like, but evidence nonetheless; evidence that should be heeded in the absence of more concrete quantitative evidence.
Disease is not the only risk here. People will die from a severe recession. It's important to realize that there are tradeoffs, and to be sure we're making the right ones.
No. He estimated the case fatality rate is that low. The mortality rate is much, much lower.
Or the virus mutates with deletions, the fatility rate goes down.
Or when testing capacity finally reaches demand and lets us find infected folks sooner, the fatility rate goes down.
I'm not trying to be mean to you, just pointing out that there are potential positive outcomes ahead. We honestly don't know what's going to happen next, but there are plenty of reasons to have hope.
Actually you sort of do. Look at Italy, China, South Korea all of whom have had the virus for a longer period than the US.
And given that US has done too little, too late it's looking a lot more like Italy than China which can't give anybody much reason to hope.
I really hope that the worst case scenario can be avoided.
State numbers and national numbers for anything can freak anyone out if they dont deal with large numbers day in day out. Big numbers hide small numbers distributed all over the map.
Plug in numbers for India or China and it's not complicated to produce helplessness and heatattacks.
That’s a big number in any scale. That’s over half of your family and friends.
Not arguing these numbers are accurate. Just saying that they’ll still freak you out if you believe they’re accurate.
Normal deaths are 2.8M/year.
There's 330M people in the US. At 70% infection, that's 230M people. At 1% mortality, that's 2.3M excess deaths.
That's 80% of the normal deaths for a year; and since other causes of death haven't stopped... we get 180% for the year, or "twice as many".
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.
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.
That would be great actually. The problem is armed citizens refusing to stay at home.
I was under the impression that the wealth disparity in CHina was even more extreme than in the US. How brainwashed am I?
You could. Just pay everyone $1000/month until it ends.
Also $1000/month is not even close to enough in most areas to live off. Rent + food + health insurance is a lot more than $1000 for most people.
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.
We still lack the capacity for even testing all the people showing significant symptoms. That is why we can't contain it.
The rejection of the WHO tests in order to belatedly come up with our own tests is a massive scandal.
Rapid testing and containment and tracing only works if the people actually comply.
My mother on the other hand is looking at possibly months of near total isolation. At her age it’s a much larger threat.
For 30-somethings I believe this goes up to 3%. Then higher from there.
Neither of those are huge but nor are they zero. Neither is a .2% death rate at millions of infections. Those are real people, a lot of them will be young like you and in the hospital. We haven't even gotten into how you will put grandpa or your avuncular older neighbors or the old guy riding the bus at risk. Or how if you fall in that 1-3% that you will be competing for hospital resources with all the other pneumonia cases.
Was looking for more info and found this: https://www.washingtonpost.com/health/2020/03/19/younger-adu...
Edit: is it me or did you edit and tone down your comment? In that case I apologize for putting it so harshly and personally. I will leave it as it is because people need to know this is serious for young people too.
Underlying heath simply seems to play a huge role. In China 10-19 year olds represented 1.2% of the total known cases and 0.9% were 9 or younger. That might have been related to transmission with elderly social circles more widely spreading the disease, or exposure to related diseases etc. However, it’s more likely an indication of untested largely asymptotic cases.
PS: half of the 300 to 400 coronavirus patients treated in intensive care units in Paris were younger than 65
16.8% of the French population is over 65. 50% of their ICU cases are over 65. https://countrymeters.info/en/France That works out to about a 5:1 ratio even including 50-64 year olds at significant risk in the younger population. The avoidance of an age specific breakdown suggests they where aiming to convey a specific message rather than clearly conveying information.
You could get sick and require hospitalization.
You could get sick and have permanent lung damage.
You could get sick from something else, or even break your collarbone in a car accident, and be unable to get adequate medical attention because of an outbreak in your region that you helped spread because you had "little reason to fear an infection."
You could infect and kill your mother.
A virus doesn't care how confident you are. It is just a little autonomous machine that uses your body to replicate itself. Don't behave in a way that helps it do that.
That's a lot of people, and how many of those can we expect to have health insurance?
I don't think it's that much, I think that it'd be more in the order of 15% of the people who require hospitalization that actually perish.
Well, until you run out of ventilators, that is...
Have a couple of issues with your points.
1. China did not close its borders soon enough, even though the government was aware of the possibility of a large scale incident. This led to the virus's spread to every other continent other than Antarctica.
2. China has the "benefit" of a central government with a citizen database where privacy has no consideration. Combine that with mostly vertical housing, it's easy to make sure no one is able to go outside except for those selected to be a resource liaison. This is impossible in a place like California.
>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.
It's in all 50 states at this point. Likely in every major urban area. Too late.
Not a single paper to come out in the past 72 hours has a CFR that high. We have been inundated with these very high numbers, but they are based on an almost certainly underestimated infection rate.
Several experts have no opined that the CFR is likely less than 1%, perhaps much less.
A paper today projected it at .04% .
We are not near an inflection point yet.
- Temporary measures, once cancelled, will steepen the curve and recreate rapid community spread conditions. This will lead to a number of cycles of pandemic curves and responses as modeled in a number of papers.
- There is insufficient testing in the US to know what's actually happening, or even if serious or critical ILI patients have it.
- The JHU data shows March 20 suddenly leveled off, but this seems like a single, erroneous aberration since that day hasn't finished yet as of writing. 
- Until there is a safe and effective vaccine proven to work, there's no realistic alternative except to isolate and not venture out more than absolutely necessary, in small numbers.
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.
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?
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.
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.
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.
That’s true of deaths but not hospitalizations: https://www.nytimes.com/2020/03/18/health/coronavirus-young-...
The hospitalization rate is believed to be 10-20% and much less specific to people over 65 or even 50.
This seems to be what Sweden is doing, and so far it's working okay. Nice to see a country that's trying to minimise violation of its citizens' right to free movement by only imposing restrictions that have the most "bang for their buck".
Also Korea. From https://www.sciencemag.org/news/2020/03/mass-testing-school-...: "“South Korea is a democratic republic; we feel a lockdown is not a reasonable choice,” says Kim Woo-Joo, an infectious disease specialist at Korea University. Instead, the key to success has been a large, well-organized testing program, combined with extensive efforts to isolate infected people and trace and quarantine their contacts. "
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.
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.
“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.”
Worth pointing out that the available life-saving equipment is being given to young people there, which complicates the simple statistic.
If this is true, it would artificially inflate the percentage of older folks who die, and do the opposite for the stats on younger people.
I learned this from someone who has been heavily researching the COVID situation for months, and whose opinion I trust.
N(t) = N0*2exp(t/Td)
- 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)
Solving for Td:
Td = t/(ln(N(t)/N0)
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 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) There are 10x (or 40x if you think) more cases out there and this is less dangerous than the flu or
2) There are 1x the cases out there and the transmission rate is what it is.
Bayesian stats is leaning towards 1) right now, and has been for a while given the evidence from SK and the cruise ship. However, when lives are at stake, it's incredibly important to err on the safe side until you're sure. In other words, be willing to lose $1 million dollars rather than lose 1 life (just throwing numbers out there).
But at some point, the greatest western economy crashing will lead to more loss of life than the flu. Let's just be sure 1st that it is just a bad flu and not potentially something worse.
Another critical reason for death rates to vary so much per country: Death rate is very dependent on quality and access to care.
― Ronald H. Coase
I find this dubious given the widely publicized shortage in tests. Also I question why you are using research from a month and a half ago when there is lots of more recent data to refine those models.
For a back of the envelope, see https://www.worldometers.info/coronavirus/coronavirus-cases/... on a log scale. You'll find a doubling time worldwide very close to what the governor's letter says.
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.
(1) is definitely true given that doctors still can't order a test simply because someone has symptoms of COVID, or even symptoms of COVID and a known exposure route from someone who is positive. (Source, my ex who is a doctor who couldn't get a test for someone today in Orange County.)
(2) is to be strongly hoped for. That is the reason why we are implementing the kinds of lockdowns that we are seeing.
We know there are more cases than confirmed cases. Order of magnitude at least
Assuming that South Korea catches most of their cases and Diamond Princess caught all of them, and assuming also that those two populations are of the same basic age-and-health distribution as rest-of-world, and assuming that the virus is roughly equally deadly everywhere.
Further assuming that all deaths caused by COVID are deaths involving pneumonia, and that all deaths of elderly, I'll people whose proximate cause of death was pneumonia or pneumonia as a complication of their other illness, and yet further assuming that none of those deaths would be recorded as death by cardiovascular disease or chronic respiratory disease (as those two causes of death are in the top 5, and could hide the entire population having COVID)
All of those assumptions led me to an upper bound for undetected COVID cases as of March 1st of 350,000-400,000 cases. (That is how many cases would have produced a death rate that could have hidden in the moderate spike of influenza and pneumonia deaths from Jan 15th to Feb 15th)
My assumptions are massive, and have wide error bars in both directions, but each assumption either seems entirely defensible or else was mandatory to get an upper bound other than "everyone, plus or minus everyone"
Thinking about the cohort of infections eventually leading to those deaths, though, means we're really getting a snapshot of the number of infections some 19 days ago (5 days incubation, 14 days from symptom to death ). With a conservative 6 day doubling period, and assuming still in growth phase, cumulative infections today is roughly 900x cumulative deaths today.
So ballpark for the US (217 deaths) is about 195k current infections.
Spain (831 deaths): 748k infections
Italy (3405 deaths): 3M infections
My flu and pneumonia data came from https://gis.cdc.gov/grasp/fluview/mortality.html
Check out the disclaimer on that page, too (even routine things like flu and pneumonia, that happen every year, the statistics are really bad until a few years later when all the adjustments are made)
One interview I saw from a CDC modeller last week was using 5-day doubling, 15-day median time to death, and 1% CFR to estimate, and was saying thus that current cases ~= 800x current deaths.
So, yeah, it's clearly more widespread than reported, and clearly all numbers everywhere are totally wrong (including yours and mine)
But even if it's 100x, you can't get near 25.5M cases in 8 weeks.
Also though, NYC is likely to need that hospital ship more than CA.
This sounds like they have completely given up on containing it. We are now left to our own fate.
"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."
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.
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/... 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.
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/
You are in error there. California has about 40 million people, 0.5 to 1.5% of 40 million is 200K to 600K.
Mind you, that is still a lot of dead people, and that is just California, and assuming the health care system isn't going to be overrun in which case the 1.5% might be conservative.
"If something cannot go on forever, it will stop." —Herbert Stein