I'm not professional and my napkin/google calculation shows something closer to 327.2 million * 0.7 * 0.01 = two million two hundred ninety thousand four hundred deaths - is it stupid?
Fauci is not sharing the data he used but 0.01 is probably not the fatality rate he plugged in. That number ignores the many undiagnosed cases. Here are some estimates using alternative methods that don't rely on widespread testing:
In the same boat here, my estimate is around ~250.000, which is 3x as bad as the 2017-18 flu season in the US. But i guess none of us have any real idea at this point.
No, not stupid. It's one scenario, but the time span is absent: do we reach 0.7 in three years or three months? At the current rate probably the latter, which might increase the 0.01 as well, because of a certain overwhelming of the health care system in the US (e.g. a young boy in California has not been treated because he could not pay, so he died).
If you're talking about the case I think you're talking about,
"""
However, Los Angeles’ County Department of Public Health later said the teen’s death was taken off a list of deaths associated with Covid-19 in the area. The department said the CDC would complete an investigation into the teen’s death. It remained unclear what symptoms he may have been experiencing prior to his death.
"""
The 17yo fatality that Gavin Newsom mentioned in a news report was also later reclassified as not CV related.
The late 21yo patient in the UK was never tested for CV.
They have number of deaths displayed, so if you try to match the observed rate and keep total deaths below 200k... well, it's doable, but with pretty strong assumptions.
This is conservative, but also, this is happening in a very short time frame, AND is taking into account all of the social distancing AND is happening at the same time as flu.
Without the distancing measures we have in place we would be looking at millions of deaths.
Once this is over, it will be very tempting to say, "Look it was only as bad as flu, we shouldn't have trashed the economy just for that..." but that of course is not fair reasoning. We only will have 200k deaths because of the distancing.
But social distancing can make at most order of magnitude difference (generous, semi-arbitrary) - which is still way too small change, it just spreads a lot of deaths in time, doesn't stop all of them, right?
Spreading out cases over time means what might have been a death in a crowded, overworked hospital is a recovery in a moderately challenged hospital where the concerns are fresh face masks rather than available hands.
Wrong. Flattening the curve merely delays infections and does not prevent them.
It doesn't seem to work well either. It has been good for a 0.5 R-0 drop which points to other primary vectors instead of aerosols. Also it turns out if you need a ventilator you have a 95% death rate, so if the hospitals get overwhelmed the overall death toll won't be too different. If the death toll is anywhere near 100k total we trashed the economy over a bad flu. It would take 6+ months of isolation to beat the virus with quarantine measures, more than long enough to cause a wave of economic related deaths way higher than the virus. People have to get back to work.
No, you are wrong by confusing number of cases with deaths. Flattening the curve reduces the max number of cases, which reduces hospital overload, which in tun saves lives. Without any intervention we were/are looking at 1M+ deaths:
1M+ deaths is impossible based on .gov's own numbers. Estmated 100-200k dead. The only way a hospital can help is with ventilators. Everyone else gets the exact same treatment at home or not. If we have a 90% death rate on ventilators than in an absolute worse case 'system overwhelmed' scenario there are 10% more deaths. The idea of millions is laughable, but to be expected from political opinion pieces.
CDC estimates that 24k - 62k die every year from the flu.
Fauci estimated 100k - 200k will die from covid-19.
So that would be 2-8x on the extremes. But 2x would be the low end estimate assuming a bad flu season and a low end number for the death rate on covid-19.
Hospitals are optimized for typical illness, not for pandemics. And the death rate has been calculated based upon cases that get adequate health care -- an assumption that goes away when the hospitals have to choose who lives and who dies.
> an assumption that goes away when the hospitals have to choose who lives and who dies.
I feel this sort of statement misrepresents the true problem and portrays deaths from lack of medical care as just a capricious choice made by cruel doctors and nurses. This portrsial is neither fair or truthful.
If you have 10 patients requiring a respirator and only a single respirator to spare, figuring out who is a priority or has a better chance of making it alive is not the same as deciding someone should die.
Someone had mentioned recently that one of HN's biggest problems was overly pedantic responses get better upvotes rather than actual content. This has a caused HN to devolve into a fact correctness engine rather than a content engine. To be fair, this is something I've done in that past too.
Yes, I did use a rhetorical phrase to make a point, but one that's pretty prevalent in modern culture and especially when it comes to triage. Perhaps google phrases like "Doctors forced to play God", etc. Ironically, the first hit that comes up is this: https://www.dailymail.co.uk/news/article-8163641/NHS-doctor-...
I really recommend that you go watch episodes of MASH from the 1980's. Particularly the episodes where the doctors have to triage cases that might be savable if they weren't in a field hospital. If the US president says we're in a war, we should all refresh ourselves up on what meatball surgery is during an actual war.
The objection is that the phrasing of a doctor playing God is extremely culturally potent in America, and far less on whether you are technically correct on the intersection of God and medicine.
And in public speech it's the public that determines meaning and not the speaker with their intentions. What the speaker gets to do is make predictions about how it will be received.
> in public speech it's the public that determines meaning and not the speaker
False dichotomy. It's a shared responsibility. Nothing gives the reader or responder the right to project their own biases or guesses of intention onto someone else's words and argue as though they'd been in the original. Please stop doing that.
As a public speaker engaged in public speech, you are responsible for getting the results you want. It would be silly for JK Rowling to blame people for not correctly interpreting her novels.
You are absolutely reaping your own fruits, but you are blaming others for your displeasing harvest.
Sure, it's language used to discuss doctors in the context of abortion, euthanasia, and medical research relating to genetics. I wonder why people might focus on doctor playing God. Could some people actually be religious?
I think no sufficiently intelligent person thinks that hospitals deciding who lives/dies will be done capriciously or by cruel doctors. But on the other hand there were large numbers of fools in the U.S. who thought the ACA would create death panels. So maybe for the U.S. your point is valid.
To me the statement "have to choose who lives and who dies" doesn't carry the meaning that the decision will be taken in a capricious way. In the end it's a horrible responsibility to decide somebody doesn't get a chance to live so that somebody else gets that chance. But that's the situation.
I suppose that is true, if the crisis is impeccably managed from this point onward, we might only see 100k to 200k deaths. On the other hand, if it is not, it wouldn't surprise me to see this level of deaths just in NY state.
True, but flu is spread out over the whole year, and 100k deaths is only 10 million cases, possibly a severe underestimate. We'll be at a million reported cases in a week, or 10 million not long after that.
I'm not sure I understand you statement re: "100,000 deaths is only 1,000,000 cases". That seems an awfully high percentage compared to the recorded numbers so far.
We need a country wide lockdown for 8 to 10 weeks to get ahead of the virus. Give the scientists and doctors sometime to figure out potential mitigations.
I’m almost certain that his estimates are too low unless we can get ahead of it.
I haven't been shouting from the rooftops because I'm not an epidemiologist and don't really want to get into an argument, but none of the low/medium/high death estimates that I've seen have seemed plausible to me. The back-of-the-envelope math that I've been doing would put most of them about half an order of magnitude too low.
From what I can tell, the best-case death estimate in the US should be around 1-2 million, and the worst case should be around 5-10 million. Does this seem wildly off?
This is based on the varying death rates in other countries that have had controlled/mild/manageable outbreaks (e.g. South Korea, Singapore) vs. severe outbreaks (e.g. Italy, Iran). The overall death numbers also seem to change depending on how overrun the hospitals are (going from, e.g. 0.9% to ~3%+), national demographics, etc. I'm also assuming an eventual population infection rate of 40% - 70%.
I'd obviously be thrilled to be proven wrong, but I honestly don't understand how people are coming up with numbers that are so much more optimistic.
Nobody knows the asymptomatic infection rate. Without that, differences in mortality numbers between countries are meaningless, because testing rates are all over the place. Explaining the differences by overrun hospitals is jumping the gun I think.
I can't stress enough how important this factor is... without widespread randomized testing of the population, we have no idea what the true infection rate is or how widespread the virus really is. Our current stats have a huge selection bias problem.
This is why it is so important that we take social distancing, self hygiene, and shelter-in-place measures really seriously in order to protect those among us who may be more susceptible to severe infection.
The silver lining: the more widespread the virus, and hence the number of asymptomatic cases... lower the actual the severity statistics are.
i.e. we know "number of deaths", "number of hospitalizations", and "number of positive cases". Right now, when we calculate our various severity rates, we are putting "number of positive cases" in the denominator because we don't know the number of actual infections. There is an unknown multiplier (>= 1) relating positive cases to infections. All our severity statistics need to be divided by this unknown multiplier. But right now, since we don't know what it is... the responsible thing to do for reporting and policy decisions is assume it is 1 (worst case). It is not 1... it is greater than 1... we all know that. But how much is a tough question to answer properly without proper statistical sampling of the population.
There are modelling studies and estimates that suggest value ranges for the multiplier, but I don't want to spread potentially false information on a public forum.
It is, because assuming that having the virus gives some immunity, then if we find out that 90% of people are asymptomatic, that implies that the number of cases we have right now won't go up much more (since many people have already had and recovered from Coronavirus).
Exactly. Fatality rates are mostly just a function of a country's testing (how much testing they're doing, and how biased the sample is).
If you're only testing a small # of people with severe symptoms, obviously the fatality rate will look really high. If you're testing a much wider section of the population, and testing people who aren't severely sick, the number will look lower.
Some examples:
- Iceland randomly tested people in the general population (no symptoms), they found ~1% of people tested positive, and half of those had no symptoms (and so probably wouldn't be tested). [1]
- Italy tested an entire village (the village had a cluster of cases), 3% tested positive, of which half had no symptoms.
- One professor used the Diamond Princess cruise ship as a baseline, and estimated anywhere from 0.025%-0.625% [2]
- China had a fatality rate of 17% initially, which went down to 0.7% if you only consider symptom onset _after_ Feb 1st. [3]
Of course, there are a lot of other factors, and it's possible that the rates end up in fact being really high, but there's an argument that we just don't know how many people are infected and fatality ends up being a lot lower then just dividing # of deaths by # of confirmed cases would have you believe.
Just to be clear: even the lower case scenarios are really serious and worrying, and I'm definitely not in the "this is just another flu" camp. But there's a huge range of uncertainty here.
Nobody knows what is coming, but I'm in the 1M+ camp as well. US is so ill-equipped plus administration is very aware, how devastating the economic consequences are even now (2T stimulus and infinite FED liquidity are already in effect today). Let this spread for two more weeks and the administration might loose their countenance and will declare: "we cannot save both the infected and our country, so we will save our country".
Agreed, I so wish one of the networks or YouTube would give someone like Fauci an hour or two to walk through their methodology in detail instead of just answering topical questions on projections from pundits. We’re not getting a whole lot of context right now that would be useful and engaging.
That's what our media has to offer? An interview by a comedian? I agree we need Fauci to walk us through it. I'd like a panel interview conducted by a reputable interviewer.
Your worst case is correct but % population infected drops dramatically with lock down. The countries with better infrastructure (richer, Western) will likely see ~1-2% of their population infected and a death rate under 1%
The question to me, aside from assumptions about infection rate, is: are the people that are getting hospitalized and/or dying today just unlucky, or are they more susceptible to the virus or its effects?
If they are just unlucky, the death rate may hold. If, however, its just the highest risk population having the worst outcomes, the death rate will plummet as they die off. In order for the US to hit 1M+ deaths, you have to assume that people getting infected in 3 or 6 or 12 months from now are just as likely to die as those dying today.
Can you share your math for the various situations for those of us not as clear on the differing rates in those countries? Has anyone built a calculator that shows how it could play out in different countries based on the experience we have seen in countries so far?
If mass testing is adopted, it would surface the asymptomatic carriers.
In addition, it would allow the creation of "clean" zones (.e.g on flights/buses) where you would need to prove that you are clean.
So, once the virus cannot "hide", and R0 is bought down to below 1, you would actually see the rate of infection crash to zero (I.e. the exponential rate works both ways).
To sum up, as long as there is no vaccine, it all depend on mass testing.
A best case scenario might be to look at the number of confirmed CV-19 deaths in China as a percent of total China population. This of course assumes competent public health policy, but we’re assuming what the best case could be.
I think that number might be coming from the idea that at that level of infection you'd get herd immunity - i.e. this thing is going to keep going around until we hit herd immunity.
With the current tools we have, it seems inevitable to me. Look at china or hong kong... lockdown led to getting local infections under control, which leads to an easing of restrictions, which lead to new infections from outside of the region. So by that logic, life doesn't get to go back to "normal" until either herd immunity is reached, or new tools come online.
True, but that seem to be a reasonable assumption according to at least some virologists looking at it.
There are so many unknowns right now that any modeling is going to have issues, best you can do is state your assumptions clearly, and explore the ones that seem most likely in some depth. Otherwise you just end up with an ensemble of models that could result if nearly anything.
Totally true. Obviously nobody knows right now if that will happen or not, but that question was posed on a recent episode of This Week in Virology (great podcast, btw) and they seemed to be saying that the mutated seasonal variant is a fairly unique characteristic of the flu virus, and it would not be _likely_ to happen with COVID-19.
The thinking behind that is that short of having a vaccine (18 mo off at best, probably) we are simply not capable of containing it, just slowing it down. Once you you somewhere in that 40-70% range, it self contains due to lack of available hosts.
Talking to people who study this stuff for a living, it's not an unreasonable assumption at this point.
Plateauing during stringent isolation (if that is the case) isn't' evidence against this, I think.
The big problem is that there still are not anything like good population estimates in the US, and unlikely to be since serious testing isn't done. Death and hospitalization statistics are better (but can get inaccurate if systems are overwhelmed) so the best the modelers can do is try and project from countries with better data ... inherently this is not as good as having good local data.
How about they start treating these people with Hydroxychloroquine and azithromycin? It seems to work. Has to be better than letting people die or suffer permanent lung damage.
> All "VIP"s are immediately put on Hydroxychloroquine when they show the first symptom. Even before a test. (waiting for the test results takes way too long and gives the virus time to ruin your lungs!).
From what I've read, results are mixed so far. I believe it's being tested out in MANY places right now to gather more data, but it seems clear at this point that it's definitely not a miracle cure.
Ummm, it's more like, saying, I had one wife 8 weeks ago, and 4 7 weeks ago, and 16 6 weeks ago, and 64 5 weeks ago, and 256 4 weeks ago, and 1024 4 weeks ago and 4096 3 weeks ago, and 16384 2 weeks ago, and 65536 1 week ago, and I have 262144 today, so in 4 weeks I will have 16777216 wives.
That is, there is more than a single data point supporting the claims of exponential growth. There are lots of them.
It’s not relevant; yes, it is wrong. Firstly, we have a lot more than the one datapoint. Secondly, we can look at what’s happened in other countries (like China). But, most importantly, the models don’t work like this, they’re more like a simulation. Take a look at the “Methods” section of this report, for example. It’s quite easily readable.
US has three months of data from Europe & Asia. Not to mention any other models of contagion. You're comparing it to a comic about extrapolating based on one data point. So no, the comic isn't relevant
The exponential growth curves have a couple dozen data points by now. We know they can't be extrapolated forever, but we also have no reason to expect the curve to top out before it hits nearly the entire population.
The xkcd is not really relevant. The xkcd is about naive extrapolation from an assumed growth model and two datapoints (which is insufficient to even validate that the growth model has the right general shape, much less to have much confidence about the parameters.)
The covid-19 projections are epidemiological projections which incorporate many data points to estimate parameters and validY the shape of the curve, and even more general knowledge from the field about the likely shape of the curve of an outbreak.
"[ The graph is labeled "Things", with "Time" advancing to the right on the x-axis. The level of "Things" has been rising over time to a point labeled "Now". The current level of "Things" is above a level labeled "Good", and about as far below a level labeled "Bad". ]"
"Here's the situation: This line is here. But it's going up toward here."
Published around March 9th. One day later one president was recorded stating:
"It will go away. Just stay calm. It will go away... [B]e calm. It's really working out. And a lot of good things are going to happen."
