This is bad. I've been graphing the exp curve for Italy, UK and USA and the USA curve is fearsomely steep. Italy has more cases now but the USA is growing fastest and looks like it will match Italy's on ~March 28th (looking at the most recent 10 points, see below)
The rate of growth in the USA, extrapolated, is just huge. Looking at the whole curve it does not match an exponential well, I think the early part is skewing it. If we take the last 10 data points, they fall very well onto the curves for all 3 countries, and that curve for the USA is horrific. I'm not an epidemiologist nor statistican so it would be irresponsible to put my predicted figures here, but christ, if I'm right the US is going to be reeling in just a few day.
Edit: @mnl below has pointed out that infection is not an exponential but on the whole a logistics curve (s-shaped curve https://en.wikipedia.org/wiki/Logistic_function). He is correct. However in early stages I believe an exponential MAY be a decent approximation (and I'm reading up on it now). However, the inflection in the 'S' (where new infections would start to slow down) would be expected to be at far higher figures than those I'm looking at - a few tens of thousands of reported infections per country currently - and it's not even close to that (populations of multiple millions in each country).
That's a very good point, and the lack of tests had a secondary effect. Nobody here took it very seriously at first, because the numbers were very low.
This is key. We really can't compare countries confirmed case numbers directly because they are operating very different testing programmes. Just look at Germany. More confirmed cases than the USA, but a quarter of the deaths. Germany also has 80% as many cases as Spain, but about 5% as many deaths. All that, without a severe lockdown.
Clearly something completely different is going on there than in many other countries, and it seems they have an extremely effective and well organised testing system. They're testing about 160,000 people a week. In comparison, the UK to date has only tested around 50,000 people in total so no wonder our case numbers are far lower, even though we have double the number of deaths.
So Germany is an outlier, but it just goes to show even for other countries you can't just compare the curves and draw any definitive conclusions without also looking at the testing regime. This is where the experts with their detailed population models and simulation tools come in.
It is the health care system like number of ICUs, training of doctors and stuff like not being able to get antibiotics simply over the counter like in Italy. If my memory serves me right e.g. in Italy 29% have a resistance to antibiotics, in Germany only 0.4%.
People don't become resistant to antibiotics, bacteria do and resistant bacteria in Italy would just spread to Germany. Anyway Covid-19 is a virus, not a bacterium.
While its true SARS-CoV-2 is a virus, opportunistic bacterial pneumonia is a secondary complication of Covid19 which increases its lethality. So you need decent antibiotics too.
We could possibly clean up the numbers, assuming the death rate is predictable across regions.
Take numbers from a region where testing is frequent, say the death rate is 2%. Then scale the numbers in a region with lack of testing to match the 2% death rate.
Not perfect, as there are external factors like hospital capacity/quality and existing population health.
However, it should give a closer approximation of total cases where politicians fail to provide adequate testing.
Each country has it's own date for when "testing came online", and it seems like starting from then might make things more comparable, despite differences in testing capacity and strategy. Another approach might be to on start looking at the data after the number of cases is > 100.
I think what is going on is a combination of relatively good testing capacity from the beginning and mostly young people infected, which due to the testing were prevented from spreading it to older demographics. See https://experience.arcgis.com/experience/478220a4c454480e823...
Also there is the purely anecdotal hypothesis of a cultural difference between for example Italy, Spain and Germany. In the southern countries it seems like older people have quite an active social life compared to Germany.
TLDR: Any comorbidities present at the time of death are reported as the main culprit. In other news https://www.thelancet.com/action/showPdf?pii=S0140-6736(20)3... Table 2: Treatments and outcomes. Sepsis 100%, Respiratory failure 98%. There you go, nobody dies from the virus alone, problem solved, 20x less deaths than comparable Spain.
Then why are basically all Corona deaths in Germany reported as having other illnesses too? If this claim were true, none of these deaths of sick old people would have been reported as being due to Corona. Do you have any evidence this is more than speculation (at least the english translation also makes it sound like it is worded speculation, not a claim of fact), and that someone who was known to be infected and died was not reported?
I keep asking people about this because I'd for sure would like to know if it were happening, but the only two sources I've seen sounded like speculation by Italian officials that at least as absolute as it is reported in other languages does not match the actual reporting here as far as I can tell.
Related, there's also the distinct possibility that many had Covid-19 well before it was in public consciousness.
Look for ILI (Influenza-like Illness) stats which were appreciably higher in January. The obvious inference is that many had Covid-19 before it was recognised as such.
If that were true, we should see a much higher proportion of tested people showing positive. Also we shouldn't see the proportion of people tested being positive shooting up, but we do. Those ILI stats were probably just Flu.
Yes, and it has shown initially small numbers of active infections, growing rapidly, as a proportion of those tested. If the virus was already widely distributed, we would expect it to be much closer to equilibrium.
I think this is underrated. This thing must have been spreading since November here.
I know a person who back in January acquired something like pneumonia and a bad fever, went to the hospital for awhile and tests were negative for flu, etc. doctors just didn’t know what it was. The person has COPD however.
But anecdotally I’ve noticed quite a few more colleagues over the last few months out sick “with the flu or something”. No idea.
They’re still only testing people with symptoms. We need a randomizes test and a test for antibodies to have any idea how much it has already spread.
If it’s as contagious as they say and spreads in asymptotic people then why wouldn’t there be a significant population that has acquired and recovered from this? Many probably with very mild symptoms.
> If it’s as contagious as they say and spreads in asymptotic people then why wouldn’t there be a significant population that has acquired and recovered from this?
Because all the effects are limited by the time it takes for them to happen. We know the speed of growth, it's much faster than the expected recovery times. From all known COVID-19 cases the number of recovered are still dominated by the recovered in China.
If you haven't heard about the Seattle Flu Study - this is a great read. Coronavirus was in Seattle before officials confirmed it. The federal government also prevented the researchers from doing more testing, delaying valuable time.
If COVID19 was spreading in the US since November then the US hospital system should have been overwhelmed by now with intensive care patients. The first infection in China was traced back to November and they were building hospitals by early February.
The only places I've seen the first US infection being dated that early are conspiracies on Chinese social media that claim the origin of COVID19 to be the US instead of Wuhan. The only way that theory works is to date the first infection in the US and claim that Americans bought it into China during the Wuhan Military games. That theory is easy enough to debunk with common sense because if the US had COVID first the hospitals would be completed overwhelmed before China's was, but it's not the first time wishful thinking's buried common sense in Chinese history.
What is this idea exactly? That the virus rolled through Seattle and other areas with just a bunch of relatively mild cases and without a critical uptick in hospital load? I am not an epidemiologist but that does not seem realistic.
It would be shocking to epidemiologists. All their confidence intervals are well above influenza. They are fully aware of all caveats amateur people talk about here and don't think it is like normal flu.
In italy in hard hit city, they were unable to cremate people fast enough and army had to move bodies. Influenza does not cause that.
Everything I said above was directly taken from non-amateur epidemiologists. I have invented nothing.
The error bars on CFR estimates run from fractions of a percent to a few percent. In countries that have tested large numbers of people who are not severely ill, the case fatality rates have been at the low end of that range.
This isn’t “shocking to epidemiologists”, it’s shocking only to people who dismiss basic facts and try to use irrelevant distractions (like cremation rates) to incite fear.
Epidemiologists say that influenza is easier to control. Irrelevant distraction relevant to topic says that only school here and there has to be closed to contain it. Epidemiologists say on that that one infected person with influenza infects less people then one infected with corona.
Epidemiologists do count with overwhelmed hospitals and services, excess deaths due that that, excess deaths on unrelated heath problems. It not just something they talk about, they have it in their models too. This does not happen with influenza, because it is easier to control. Irrelevant distraction there is Italy or Spain lately.
Epidemiologists do talk also about costs after epidemic ends, in treatment of people who will need care for long.
What amateurs do is to ignore all the above, pick up case fatality ration in well run non-overwhelmed health care system and pretend that is situation same as influenza to feel good.
"spreading in the US since November", and "there's a new, highly infectious respiratory disease since November" are two very different things.
I don't know anyone that credibly believes it was in the US in November. We did, however, that something was amiss that early, and if the US had a pandemic response team who's job was to see something like this coming, we could have been getting testing ready since then.
Yes it was the case for many people in February. They didn't have covid. Your dad is very high risk and should stay home. The doctors in UK don't need a test to diagnose covid in a patient with pneumonia. They see it in a second on an xray because it is so distinct. The Chinese doctors said the same. So do the Italians.
Yeah I’m not sure what people are expecting to happen here. This virus has been circulating in the US for months and testing was limited. There’s surely many multiples of infected people than currently reported, and that’s true for any country that isn’t doing blanket testing of entire population.
Even if that (EDIT: ‘that’ being an idea that virus has been circulating for months) were true (which almost certainly it is not), so what? The only logical explanation for this is that percentage of severe cases relative to totally susceptible and infected is orders of magnitude lower, and now the total number of infected is so large that number of severe cases is starting to get noticeable. But that is not the picture we are getting from South Korea that had much more comprehensive testinG.
> Even if that were true (which almost certainly it is not)
What are you referring to? You don’t think the virus is already much more widespread in the US than currently reported numbers? I’m just making the observation that perhaps the large increases in US cases are more indicative of confirmation of already existing cases rather than necessarily being _new_ cases.
I am not arguing that virus is more widespread than the reported numbers, that much is obvious. I was replying to the idea that virus has been circulating “for months” undetected. With a doubling time of 5 days or so, with “for months” circulation we would be in a totally different territory right now.
> I was replying to the idea that virus has been circulating “for months” undetected.
I don’t think that’s crazy at all. We had our first case sometime in January, and only until very very recently have we had any significant travel restrictions. It’s very contagious and for a significant number of people there are no real symptoms, or if there are, nothing life threatening. I don’t think it’s crazy at all that it’s been working it’s way around the US population for months.
Maybe to put it another way, if we could instantly test al 300+M Americans right this instant, would you be surprised if say 20M or so tested positive or had had it?
Yes, I would be very surprised. Given what we know about severity distribution that means 2M hospitalizations and ~200K-1M ICU cases that we somehow missed.
Yes - absolute criminal negligence in the US and UK. Possibly Australia too.
The problem isn't just that a lot of people will die because the health system is swamped. That's hardly good news, but when you have a high peak you have a lot of people ill at the same time. And that means you run the risk of losing a significant percentage of critical workers in essential services including food, utilities, logistics, and IT.
Some will die, some will "just" be very ill and unable to work for 2-4 weeks. If you're lucky the numbers of seriously ill will be low enough to keep things running. Beyond that you're on a scale from frightening inconvenience and breakdown in some locations to the economic equivalent of critical organ failure.
Pushing any country through this is a huge and utterly irresponsible risk.
Original poster. I'm from the UK. Looking at the curves only and leaving out politics completely, the UK curve is by far the slowest growing of the 3, for whatever reason. It's the US that has the most to fear at this point, of the 3 countries.
UK number of deaths is two weeks behind Italy's. I'm quite sure that that growth will be consistent in the next two weeks in the UK -- namely, up to now, the growth characteristic remained the same across the countries with different policies, and it can be observed, from China and Italy, how long it takes for any policy to decrease the growth. Then check and compare the Italian measures with the UK for your estimate when the UK curve will flatten in the weeks that follow. When the flattening will start will indeed make a huge difference in the direct impact of the virus (the number of ill and dead) between the countries, due to the growth characteristics being what they are. Also see my other posts.
The number of "cases" reflects at the moment the capabilities of the whole medical system in each country (it's dependent on who is selected to be tested at all) and the tests used. The number of deaths hides less. Also, even if the specific numbers can't be compared 1 to 1 across the countries, the characteristics of the curves can.
The growth is fast but it is comparable, and the measures take time to affect it.
UK policy is "testing for coronavirus is not needed if you are staying at home" for symptomatic suspected cases, so it's likely our stats are a bigger underestimate of actual infections than many other countries
>Pushing any country through this is a huge and utterly irresponsible risk.
It's a risk, but the amount of hardship all the people who lose their jobs and business will endure if an indefinite lockdown is implemented is an absolute certainty. Poverty has lasting, lifelong negative health impacts.
This analysis is difficult because it is related to testing capacity. We all know testing capacity was limited early on. It remains limited, but is growing. The faster capacity grows, the steeper the curve will be. Want to have a less steep curve? Lower the amount of testing.
In another comment, you claim looking at the curves leaves out politics completely, but it doesn't. Any politician can make the situation look worse on the curve, but better serve their people, by increasing testing. They can also make their curve look better, but do worse for their people, by claiming their state is unable to purchase tests. This can be a very political game.
Yep. Ventilator usage [if available] and deaths are more reliable indicators, but they're also lagging ones [and even deaths aren't entirely consistently measured since many of the most severely affected patients exhibit comorbities, and many nations don't test the dead]
They are more reliable than the simple number of cases but in the Italian province of Bergamo (and I suppose in neighbouring Brescia, too) lots of people have started dying before the ambulance even arrives at their homes. Those people will not show up on the official statistics of covid victims, at least not now.
A similar thing had started happening in Wuhan once the situation had become really dire, and the closest valid indicator people could find was to look at the number of incinerators and how busy they were (mostly looking at the number, because the incinerators were busy 24/7 anyway).
Often tests are not performed on a random sample of the population but only on people that are symptomatic.
But not all symptomatic people receive tests.
Knowing those two number (number of symptomatic people who would have qualified for a test, were it available; number of test performed) could paint q better picture.
Until recently Ontario had very stringent testing pre-requisites: 2 or more symptoms, history or travel in the last 14 days. Even then, on average, only 2% of tested people tested positively for SARS-Cov-2. In my opinion that makes the notion of much more larger population having it and not noticing due to the lack of testing, at least at this stage, highly unlikely.
Ideally, yes. But given the limited testing capability that is a politically hard thing to do. Even if 50-75% of cases are asymptomatic (and that is a very big if), that would mean that on average you have a number of asymptomatic people that is a factor of 1 to 3 of confirmed cases. While it would be great to isolate those people, at this point that is still not a huge number that means anything for the response.
once people's minds are made up, it's incredibly difficult to walk them back to a different reasoning. Apart from the lack of early tests the problem is therefore exacerbated by the downplaying of the problem during the critical early stages. It wasn't just lost-time that needs to be made up for but also that mitigations will now become harder to swallow!
The death curve is also quite steep. Seven days ago we were at 57 total deaths, now it's 276. Daily deaths has gone from eight people seven days ago to 49.
The death curve is also deceptive - there were likely many patients who were recorded as dying of the flu, or of influenza-like illness, that actually died of COVID-19, due to a lack of testing. The bottom line is that it’s very difficult to make a conclusive statement based on the data collected prior to widespread testing.
As for that Medium article, it’s written by a tech exec with zero education or professional experience in anything related to medicine or the life sciences, so I would treat it with a heavy dose of skepticism. Many of the deluge of preprint articles from academic institutions written by epidemiologists or public health experts would likely be a far better source of info.
We have plenty of flu tests. Covid-19 is also pretty distinctive on chest CT scans, if it's advanced enough to kill you.
The numbers may be wrong in that article but the math itself seems straightforward. It's certainly true that we need more tests to be sure of the numbers.
Here's a pretty interesting simulation from a research group at the University of Basel: https://neherlab.org/covid19/
It's not distinctive from other lower respiratory pneumonia cases - it's only distinctive from the flu, so it could have been confused with other infections.
> Covid-19 is also pretty distinctive on chest CT scans, if it's advanced enough to kill you.
I guess you're suggesting that when people die of Covid-19, we'd know it and count it?
That's not true.
First, CT scans (and other expensive tests) are not generally performed on people who have died of pneumonia, apparently due to the flu (or other causes). Second, the radiologists reading those studies would have to train to make the distinction.
Now, going forward, we have an increasing need to know whether the virus that caused the pneumonia that killed the patient was Covid-19 or not, so maybe such testing will become routine. (I doubt it will be CT scans though, because there will be much cheaper and reliable ways to do it.)
But so far we've been undercounting Covid-19 deaths for the same reason we've been undercounting cases: lack of testing.
I was more thinking that CT scans would happen in advanced cases before the patients die. I did a bit of googling and found CT scans are not a definitive diagnosis but they are distinct from flu at least (just as koheripbal said).
But it's a good point that we might have more deaths than we've counted, and this might just mean we're further along that we realize. The rate of growth is probably not just an artifact of more testing; it's similar to the growth rates in other countries that haven't gotten control of the disease. And we definitely don't have it under control.
I expect that the number of people who die monthly for a certain condition to be relatively stable over time.
We can compare the usual number of people who die of pneumonia with the current one, and any significant difference can be attributed to this novel virus.
Responding on March 16 and 17 to the question, "how many cases will the US report by March 29", their median prediction was 19,000. As of this moment, early on the 21st, that figure has ALREADY been exceeded (per Worldometer). Based on current growth rates, it appears virtually certain that the actual figure on the 29th will exceed the "best-guess" prediction of every single expert surveyed, and the "high-end" prediction of all but one or two. They've completely whiffed a prediction just a few days out.
This is a novel (no pun intended) situation, even for epidemiologists. To understand it, critical thinking skills are at least as important as subject matter expertise. My read is that the Medium article represents some of the best critical thinking on the subject so far.
Here is a report from a team of epidemiologists at Imperial College, led by Neil Ferguson. The title speaks for itself: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID- 19 mortality and healthcare demand. The paper is sobering reading. But of course, all the numbers plugged into the model are saddled with huge uncertainty.
not to downplay any death but there are roughly 100 deaths/day from car accidents and similar number is also from gun-related just to have some perspective. Unfortunate/scary thing is that the virus has the potential to eclipse those numbers by 10x easily
If you want to have better comparable values, you should account that US have had too little testing and it just starts to increase. The US also has such health care system that it doesn't treat most potential patients the same, also potentially missing the cases completely. So the numbers of the "confirmed cases" in the US aren't to be trusted at the moment.
What's more sure, in most of the countries in the world, is that if the tests are available at all, and the patients happen to be admitted to the hospitals with the symptoms, they will be tested, and the percentage of deaths will be comparable in all countries, and we should be able to assume that the hospitals will report the deaths of the patients tested positive.
In short, now that the numbers of deaths increase, these numbers reflect better the issues we are facing than just the reported cases.
We should estimate the number of "comparable" cases across the countries or areas with different capabilities from the numbers of deaths, at least for the countries and areas which have at least enough tests to test those admitted with symptoms and report the dead, and once these numbers aren't too low to be too noisy.
I've demonstrated some of my simple calculations in my other messages, so you can check these too.
It is not an exponential, it's a logistic curve, just approximate with the SIS model, it's easier.
Yeah I knew by Sunday that tomorrow we're hitting 30,000 cases in Spain. My assumptions worked. And it's just the tip, because I don't know anything about whether there's been randomized sampling, so who knows about the normalization.
I just can't believe this. No one listens and this is in-your-face obvious.
OK, looking at this, the curve is upwards without inflection. What would you expect to get if you fitted a D3 poly to it? Why would you even try? Serious Q.
First thing you do is try to make sense of the data, if I can model 15 points with 2, 3, 4 parameters and further ones don't add any improvement I'm onto something. I've always done polynomials first, you can see if there's something much simpler than Lagrange interpolation, which in my experience means you have to go straight to the literature about that kind of problem.
(Of course this works as long as you aren't seeing any peaks)
oefrha, for some reason I can't reply to your comment just yet so I'll post it here: Of course. This is just my own criterion when I start with a bunch of data I know nothing about. Is there a complicated law behind them or maybe not? Am I seeing noise or there's a signal? You can fit anything smooth with a low order polynomial, so maybe there's a differentiable function right in front of you. It's just something I do and if you see no reason for it I might even agree with you on that. It never ends up in the model, though. It's just something I find useful at a preliminary stage.
OK, We're not being responsible doing this and I'm not qualified to do it. I just have been fitting the data and maybe I've been lucky and I'm just an idiot. Having said that, this is also my problem, I have right now a hotspot in the vicinity and I'm worried. I just want to have a quantitative idea of what's going on. Now it's your job as experts to explain what's going on to the politicians and make sure they hear and they can do the right thing. I wouldn't be worried if the messages had matched the numbers when this started, they didn't. At some point we need someone to tell us "we're at this point and tomorrow we'll be at that point". I shouldn't feel compelled to find out by myself what all this is about. I feel awful by posting all this, I'm perfectly aware that non-experts in a field spout nonsense, but this is a very nonsensical situation and I'm tired of hearing we've been doing fine.
I mean, any smooth curve (without singularities) is well approximated by simple polynomials locally, which is simply its power series expansion. Doesn’t mean simple polynomials would necessarily hold much predicative power, however well they fit the current data. Higher order terms, if any, will come to dominate.
Yes, I found out that later, but while we were in the low hundreds fitting to an exponential didn't seem to work very well in comparison to a polynomial (it was overestimating). It wasn't a quadratic either. There it jumped and I remembered I should try population growth models. I started with Gompertz, which is pretty much indistinguishable from logistic at this stage. Then I found out that logistic was more stable and parameters seemed to converge for a few days, so I learned about SIR/SIS. And then I figured I had some idea about what to expect in the following few days.
I stopped trusting any of my rudimentary models by Sunday+incubation, because conditions changed then. Which data, why I trusted them and the set of assumptions taken to consider them representative for the shape of the time series/distribution, that's something I don't think I should share here at this point. In any case I'm used to extract some information from imperfect data, you approximate and estimate. I mean there was by then 12, then 16, then 30 positives in a nursery home next to my door, and no lockdown measures, now there's 100, an improvised hospital there and I'm not allowed go out except for buying groceries. Two weeks ago I needed some picture which I wasn't getting anywhere, the alternative was freaking out after comparing what the authorities were saying with what I knew about the situation. Now they are making sense and the measures in place too, so I expect it getting much better soon.
I don't want to go into epidemiology and I want to respect and trust blindly the epidemiologists, but in any field you expect the professionals having predictive skills working before your eyes, that's their job. Hearing that we should wait for the post-mortem to know where we are now, I mean, come on... And now I'll just shut up.
I mean, it's just frustration. You have to expect this from a novel disease once you realize its R0 has been characterized, it's greater than 2, it's airborne and asymptomatic patients can transmit it. What have been people expecting? I'm a physicist, I've seen this kind of growth. We also have this totalitarian principle which states that "Everything not forbidden is compulsory", I see no fundamental difference, it has to happen. Just don't act like in ordinary politics where problems can be waved away, Nature doesn't care about that.
Oh heck yes. ISWYM and that's the way I treated it - seriously, starting 2 months ago, for exactly those reasons. I just don't get it either, it's like head-meets-wall every time you try to tell anybody. It's so depressing.
(what I thought you might have meant was a criticism of me misusing maths and you were getting pissed off telling people it was a sigmoid not an exponential).
Nobody knows for sure, of course, but my understanding is that it is thought to be between 2.0 and 2.6 in the “do nothing” scenario. Which is scary big: See the Ferguson paper that I referenced in a different comment.
I'm wondering if the claim that we will have two times the number infections after the inflection point is seen will actually be worse. I have a feeling when people see there is an inflection point, they will relax their precautions and make it worse.
As you can imagine, there's more to epidemiology than this. I'm a big fan of letting the qualified people do their work, while we do ours: shut up and do not spread misinformation.
In fact, at the risk of being rude ill even go so far and say that it's quite arrogant to pretend to pontificate about this when your knowledge about this issue is 0, and also when one major problem in combating this pandemic is the "epidemic of misinformation".
Many doctors lack training in epidemiology. Many epidemiologists aren't actual doctors.
Healthcare in general is horrible with generating accurate raw data (JHU data comes often from scraping websites and the CDC itself has stopped publishing number of daily tests weeks ago). <-- this in fact is a technical problem not a medical one!
You don't have to be a Dr. med in order to see gaps and problems with statistics and a large part of the conjecturing actually comes from gaps and flaws in the sources and the way data is presented. A background in an isolated discipline (only med, only statistics, only Math, etc) is not enough to harness and make sense of complexity.
Finally research papers themselves are all pre-print and not peer-reviewed which is a trade-off in accuracy for speed.
We're all finding solutions as we go and the more eye-balls from different discipline this gets, the better the outcome!
I would suggest epidemiologists provide some set of problems all this useless but willing pile of software engineers could apply themselves to. For example, scraping data from mismatched data sources or implementing specific hypothetical models. Even if it's only marginally useful, it would give them something to do other then misinformation.
And I am having serious misgivings about posting it, nonetheless, many people have expressed deep concerned, and I'm doing the same, only with actual data.
I made it clear the limits of my knowledge - which may still not excuse me, however I have to ask if you are an epidemiologist and if so, please tell me how to model the data better. And I don't mean randomly google up some papers to dump here and pretend you are an expert (unless you are).
How far can I extrapolate e^x before it becomes useless? What are the confidence limits I can use in the extrapolation? How much can I approximate the logistic function with an exponential, when as now, the cases are currently a small fraction of the population? Why is this site http://nrg.cs.ucl.ac.uk/mjh/covid19/ done by experts using log axis any different from mine using curve fitting with exponentials? Why does http://nrg.cs.ucl.ac.uk/mjh/covid19/#w say the USA is 11.5 days behind Italy whereas my amateur attemp suggest ~9 days? (and yes, I wish I'd seen these graphs before I posted)
What else have I missed? Criticise freely, with reason, don't just accuse me of misinformation because I posted my fears, which others have done too, only I did the maths.
Now please excuse me while I look at the logistics curve and compare its early stages with exponentiation.
>> And I am having serious misgivings about posting it, nonetheless, many people have expressed deep concerned, and I'm doing the same, only with actual data.
There is no "actual data" in your comment above. There is a claim that you make that you have graphed some data, but no graphs and no data.
Also, it doesn't take an epidemiologist to know that a non-epidemiologist should not play at epidemiology. The other poster doesn't have any responsibility to tell you "how to model the data better".
> but if I understand you correctly you did not have it when you made your first post
correct
> It is therefore inadmissible evidence as to whether your first post was a reasonable thing to write.
Completely wrong. I approximated the lowest part of a logistic function with e^x, which is reasonable for small values. Given it matched well with professional epidemiologists' graphs, it suggests I'm getting it approximately right.
> whose responsibility is it to fulfill that desire?
Mine and yours. Don't stick 'reasonable' on your replies and suppose it insures you in any way cos it doesn't.
Mate I can start to pontificate randomly about aeronautics design, and you can very well tell me to shut up with no requirement that you are an expert yourself.
There's a quote that states that all models are wrong, some happen to be useful.
With this in mind I think we should stop nitpicking on non-specialists who try to raise awareness of this pandemic.
Yes there might be some differences from what a specialist would have done.
Due to the speed at which the situation evolves and the inability to test everyone daily there are lots of unknowns so even a specialist may not be able to give a more much precise figure, everything is going to be a rough estimate.
This is a very serious situation and it's better to err on the caution side, people's lives depend on everyone doing their part.
Non-constructive criticism of people who raise awareness will erode people's buy-in and people will die because of this.
People spend years studying epidemiology. No one can write a comment here that will teach you how to do it properly.
But I'll try to help. You're looking at a graph of confirmed cases, in other words, positive test results.
That may be due to an increase in the number of infected people; or because the number of tests being performed is increasing, and therefore the percentage of infected people reported as confirmed cases is increasing; or because some positive test results (even with confirmation) are false positives. And there may be other causes that I don't know, because I'm not an epidemiologist either, just a statistics grad student.
Figuring out the the contribution of each cause is a job for the professionals.
The "behind Italy" number must refer to the number of days after Italy the area reached 100 confirmed cases. Because those numbers obviously don't reflect an extrapolation of the exponential function even 10 days into the future, even corrected for a reduction in the coefficient when numbers grow above 10.000.
You are absolutely right that the early phase of logistic growth is practically indistinguishable from exponential growth. As to what extent this observation is useful when applied to the current situation, I don't know – I am a mathematician, not an epidemiologist. But as a rough guide to aid understanding, I think it probably has some merit.
Thanks, it's nice to have an expert around! I was going to plot the divergence between the two but got seriously despondent and hit the bottle. Trying to sober up now.
May I ask, what area do you work in, numerical, discrete, logic, other?
Indeed, you have a point. But in the US at least we have a serious trust issue with what we hear. I believe Fauci, but he still has to play by somebody else's rules.
I too am tracking the numbers. I seriously and honestly expect them to become unavailable- or at least very hard to get to, if things go very very bad.
I expect to see a bump in the "infection rate" in the next few days as testing becomes more widespread. In fact, I expected to see the start of that already, but if it's happened it's not obvious. The number of cases continues to double every two days and change.
I get that your comment is coming from a good place, because the threat of misinformation is real. But this is an “Appeal to Authority” argument. I’d rather have an informed discussion among smart people, even if they’re not experts in the specific field. I’d rather be able to weigh the input of many people. Especially in a case where the experts haven’t done a great job at communicating or understanding the severity of this.
Rather than admonish people to shut up, it would be more constructive to point out the flaws in their methods, so we could all learn and make better judgements.
Thank you. To me, that's what it's about. I'd rather try and fail and learn from that, but people just telling me to put a sock in it isn't something I can learn from.
> and fitting ke^x to data doesn't make us informed
Well, yours is an interesting post but let me ask if curve fitting doesn't make us more informed then what does? There's an update to the data for the US in the past few hours and it doesn't improve things.
I very carefully stated out my limitations, and then pointed them out again when someone critiqued my approach (see edit on https://news.ycombinator.com/item?id=22645793). I have done my best to accept my limitations, but still I get people like you hammering me.
So the question is why are we even posting anything on HN? Bottom line is what is HN for - non-factual debate, or factual debate?
I strongly get the impression that much criticism isn't based on my admittedly trite analysis but because a lot of people just don't know how to handle really bad news and are trying to blank a nasty reality. Doubly so when I'm accused of of "hold on! I'll save the day!" which is purely your invention.
> I strongly get the impression that much criticism isn't based on my admittedly trite analysis but because a lot of people just don't know how to handle really bad news and are trying to blank a nasty reality.
No, you just made a large number of flaws in your initial analysis, and it made people despair of going to the effort to point out where you went wrong.
You're producing a future estimate, assuming that all properties of your dataset are consistent (they aren't) and will continue to hold (they won't).
As a few examples: (1) varying ratio of confirmed cases to actual total, (2) % increase in testing per day, day-over-day, (3) varying time offset according to disease progression and symptoms presentation (aka testing).
You seem to be of the opinion that any information is better than no information. In scenarios like this, I'm of the counter opinion that bad information is actively harmful and inferior to no information.
> No, you just made a large number of flaws in your initial analysis
Seeing as you don't have access to my analysis, you can't say that.
> You're producing a future estimate, assuming that all properties of your dataset are consistent (they aren't) and will continue to hold (they won't).
This is just vague stuff to put me down. I worked by confirmed cases in publicly available data.
> varying ratio of confirmed cases to actual total
I'm not sure what this mean but I went by the total confirmed cases, day by day. As for your 'increased testing', I'm fully aware the US is finally getting going.
> varying time offset according to disease progression and symptoms presentation (aka testing).
Why would the progress at different rates at different times in different individuals make any difference? I'm going by confirmed cases anyways so unless you know of a new strain with different characteristics that's starting to distort the figures (and there are possibly 2) then it makes no difference.
No, save your slapdowns for the people who push garlic as treatment. You are objecting to me for psychological reasons, not logical ones. You can go to the wiki page and see the growth day by day but you don't want to because it's bad news and you don't like that. Well, get used to it. Your life is going to change, nothing will stop that and the sooner you face it the safer you and your country will be. Hard times ahead. Good luck.
This conversation can serve no useful purpose anymore. It's clear that you will never admit that there's anything wrong with your "analysis" (too big a word for pasting data in a spreadsheet), as far as you are concerned, you are a bloody genius (and helping people!) by plotting a bunch of points in a log scale. And of course any criticism of your methods can only be persecution and for "psychological reasons"... I wonder why anybody would post in a discussion forum if they are going to completely ignore any feedback or criticism (and in a very Trump manner say they're victims of personal persecution). Maybe just validation? I don't know, I'm not a psychologist.
Like other people have said through this thread, it's rather simple: you don't know what you are doing, and at this time bad information is worse than no information, and it will hurt people. And reiterating my remarks on my first post: stop being so arrogant, this is really the only word to describe your attitude as far as I'm concerned.
It does seem to serve no good purpose when we are talking across each other. For example I clearly and immediately modified my original post to state there was a risk of error because I was using the wrong curve (https://news.ycombinator.com/item?id=22645793).
And "I am a bloody genius [...] by plotting a bunch of points in a log scale" - I actually used the words 'admittedly trite' about what I did.
Whatever. This gets us nowhere. Your profile says you have a background in physics and logic/automated reasoning. I'm just a general purpose back-end dev.
We're facing something that may kill more people than WW2, let's concentrate on that. Can we work together to do something useful? Thoughts?
Epidemiologist are working, and they are saying the same as throwaway_pdp09 - that this is bad. If throwaway_pdp09 were claiming otherwise then it would be a different story. No country is going to change their country's healthcare response plan based on some random conjecturing on HN, and regardless of any numbers that pop out here, the instructions are the same - self-isolate until mid-April, at the soonest.
throwaway_pdp09 isn't spreading unnecessary panic and their attitude has been anything but arrogant, pompous, or dogmatic. They are very open in admitting that they are not an epidemiologist. Saying f(x) = 9 and asking why their 'f' is wrong, and wanting to understanding its shortcomings and how to improve it, seems entirely fine to me. You are going to have to be far more specific on the harm caused by a lay-person projecting that we are fucked in 9 days, vs an expert's opinion that we are going to be fucked in 11.
If it helps, pretend this question is being presented and asked at TA office hours during Epidemiology 101 at university by someone who is considering going into epidemiology.
We are all here to learn.
Meanwhile, there's actual, harmful nonsense out there to rail against. Half-remembered gossip misinformation that spreads like an infectious disease with an R0 of 5. Complete crap, like holding your breath for 10 seconds will test for Covid-19, or that essential oils cure Covid-19 or that its eventual vaccine will cause autism. Fight that misinformation, not people who's latent interest in epidemiology has been awakened. Who knows, a reader here could be deciding to get a degree in epidemiology because of an interest sparked because an exp curve is too simple.
I'm just trying to make sense of things, same as anybody else. I don't think anybody's fucked either in 9 or 11 days, I actually have a great deal of faith in the United States and yes, I mean it, but bad decisions from high will cause a terrible amount of pain too soon. I just want to wish the US the best because they'll need it now more than any other time, probably in all it's history. I don't think WW2 stressed you as much as you are about to be now. Buckle up yanks and pull together, I believe in you! You will get through this.
You have to bear in mind when doing any analysis of this that you shouldn’t treat the US as one country when comparing to Italy. The number of distinct outbreaks happening at once makes a big difference in the steepness of the curve in the beginning. Italy might have been 5-20 distinct outbreaks while what’s happening in the US looks much more like 50-100 separate outbreaks developing at once
"Beginning" might be the wrong term, as it's a bit into the beginning that it starts to make a difference.
Local saturation happens fairly quickly. Having 100 infected in one place is very much different to having 1 infection happening 100 different places when you look at it after a week
When you're looking at the "country" view, the "older state" gets lost in the transmissions happening from people crossing borders. So what I mean is, people have been flying back to the states with infections spread out over the entire country while cross-border spread has been much more localized in italy
Oh my. Thanks for that explanation. Given the indifference of the US administration it suggests things may be spreading even faster over there than I realised. We'll know in a week or so.
> people have been flying back to the states with infections spread out over the entire country while cross-border spread has been much more localized in italy
I still don't see the difference? Why do you think that the cross-border movement of the disease should be different in Europe compared to the US? Why do you think that the US should be worse off, if that is your point? Do you think people more fly back to the US compared to the people moving from country to country recently in Europe in the last period (including Italy)? Are you aware of how Europe functioned up to now? Many people worked in other countries, and they typically don't even have to fly to achieve that, especially not across the ocean.
You're basing your curve off faulty data. We haven't been doing testing so we don't really know. Until a week ago no one was doing anything about it and staying home like they are now. Again that will vastly throw off your curve. It's still too early. Give it a week and re-run your model.
Yesterday's evening jump was unexpected. We jumped yesterday, instead of 1.5x the day before, all of the way to 2x.n If 10k is the new baseline and we return back to 1.5x we're going to exceed Italy in cases by Monday and exceed China by Wednesday.
Then, I fear, St Patrick's day partiers will only be measured by next Wednesday; 5 days incubation + 5 days to have test results.
One hopefully positive indicator is that yesterday new daily deaths in the US were lower than the day before (49 vs 57) [0].
Obviously it's only one day so time will tell if that means anything or a pattern occurs. As others have said, the stats for number of people affected is so closely linked to testing rates which have been increasing that this could be a more indicative metric to follow.
I'm sorry to say it, but that's just noise in the data. The death numbers in the United States will follow an exponential curve for a long time yet. Two weeks would be the absolute minimum before the shutdowns have an effect, but I think a month or two is a more realistic hope.
The numbers mean nothing. All your seeing is the availability of testing kits, which has nothing to do with the number of infections. Don’t bother graphing a thing.
For the numbers to have meaning, a stochastic sample of the population should be tested at random, not people coming forward because they think they’re sick.
Most people (and most people who advice the public in the US) doesn't take this serious enough.
One of the foremost experts in epidemiology in the US Michael T. Osterholm said on Joe Rogan (AFAIKR) 6-12 months for the virus to go away, up to 5 years for a vaccine and that it would return in China when people start behaving normally again. This isn't something that will go away in a few weeks or months.
In "Deadliest Enemy: Our War Against Killer Germs" he also predicted a Corona virus coming from China.
In a months time the US will take the place of Italy and see the healthsystem crash.
From what I read in this article and other sources, performing more tests seems to be a very promising approach to get this pandemic under control.
The number of positive tests and death rates are published every day on all channels. I wish the number of performed tests would be also published daily. What gets measured gets managed.
I wonder what limits the number of tests that can be performed. How much would it cost to ramp up testing capabilities so that every person with symptoms can be tested? How much to increase it to a level that everyone can be tested?
Which is scary because Japan seems to have had the virus for a long time and is hardly testing at all. Really makes me wonder how the Olympics will or won't look.
"We're virus free! Our strategy of extensively not testing has eliminated cases of the disease! Come to the 2020 Olympics, stay long, and please spend money here."
Not cancelling or postponing the Olympics is massively irresponsible. That said, those who would still choose to attend are beyond help and a risk to their communities.
It's not a question of cost at this point. It's a question of availability of reagents and consumables, materials to make those, and time it takes to ramp up. The supply chain is like a supertanker.
At first we didn't have enough test, but that ramped up quickly, then we didn't have enough RNA extraction reagent, now we don't have enough swabs, and soon is the collection media that will be missing.
There has been a call for more protective equipement. But as the situation gets worst, beds space, ventilator, and then staff are going to be the bottleneck.
If you google you'll find stories of people helping their local hospital by 3D printing parts for for respirators, and swabs. There's nothing cost effective about that, it's not fast, but it gets the job done. If you were to scale that, you would be competing for the same materials than manufacturers using injection molding or plastic dipping are.
> At first we didn't have enough test, but that ramped up quickly, then we didn't have enough RNA extraction reagent, now we don't have enough swabs, and soon is the collection media that will be missing.
No one is out trying to actively hide this information, but its spread does seem a little uneven.
I also don't want this to be fearmongering. Capacity and supply will grow (hopefully fast enough). Alternative solutions will be validated. We will keep bumping into problems, and we'll keep solving them (cause we'll need to).
The FDA just approved an antibody test. One blood sample, results in fifteen minutes. The manufacturer thinks they can produce enough for 200K tests/day.
Yeah but about HALF of those tests were done in the last TWO days! Capacity is coming online very rapidly now and while we are starting from behind, we will not be so short on tests for long. Roche alone is shipping 400,000 tests per week and Abbot Labs is on track to perform one million tests per week in the next couple of weeks. https://arstechnica.com/tech-policy/2020/03/america-is-final...
The important number is the ratio of tests:true case count. You need ~1000 - 10,000X tests/case to do true contact tracing because you want to a) blanket the country with tests and test every single suspected case even if 99% of them end up not being COVID 19 and b) proactively quarantine every person that a positive person has come into contact with and then test each of those people every single day for 14 days until they come up negative. If a single of those people come up positive, then you want to proactively quarantine all the people THAT person came into contact with, rinse and repeat.
It's great that tests are finally ramping up but the growth in testing can never exceed the growth in cases if cases are doubling every finite number of days. The choices are a severe lockdown where R < 0.5 until the true case count drops to near 0, a non-severe lockdown where R ~1.2 - 1.8 (Hubei's lockdown had an R of 1.3 in the early days until they figured out centralized quarantine could bring it down to 0.4) and you just continue the lockdown indefinitely, or "herd immunity" where R stays at 2.4 until pretty much everyone in the country gets sick.
Once you get your true case load down below your test load, then you can think about using non-pharmaceutical interventions (universal masking, universal temperature screening, mandatory hand washing when entering into a gathering space etc.) along with rigorous contact tracing to ensure that any future outbreaks remain small and contained.
I agree with wanted to blanket the country in tests, but you don't need 1000 tests to do contact tracing for one person, even normally, let alone during social distancing.
You don't need to test people every day for 14 days.
You do because as soon as that person is confirmed positive, then you need to contact trace and quarantine that person's contacts. Every day that goes between a confirmed positive and a contact trace, the more that person's contacts are walking around, spreading it asymptomatically and making the cluster even more out of control.
At the moment of this comment that data says that ~2500 tests have been performed and ~2700 people have been tested. Perhaps those numbers were transposed. Maybe there is a simple, explainable mistake. But all the numbers everywhere are so full of errors, it makes casual statistical analysis just a fancy form of home entertainment at the moment.
I think testing mostly matters to prove to people this is real, but tests don't actually stop the disease. They aren't a cure.
I don't know how to get there from here, but I would like to see a great deal more focus on best practices and cultural change. That's how this pandemic will be stopped and prevented from recurring. Tests will only elucidate how bad it is, but aren't actual treatment.
Stop touching your face.
Stop touching everything.
Stop shaking hands. Maybe adopt bowing instead as a respectful greeting.
Wash your hands.
Be more supportive of remote work.
Design more services that help make flexible remote work a good thing for workers. (I like the Textbroker model. I've tried to promote that previously. No one cared or thought it mattered. Now, maybe people will pay attention.)
Light one small candle rather than curse the dark. Focus on promoting solutions. We don't do enough of that.
Testing helps a lot more than that, because it helps you catch infected people before they spread it further. This was a key factor in China and South Korea getting the disease under control.
It helps you know that infected people exist, but in a "free" state, that's all. Unless you both require verifiable ID and have the power to quarantine someone against her will, you haven't "caught" anybody.
I agree with you on almost all points, but testing does help to stop the disease. They are not a cure but an ability to test infected and recovered people en masse would help immensely to (a) isolate contagious people as soon as possible (b) confirm that the virus is cleared and the person can go back to the productive work with at least some assurance of immunity.
Tests are information. I think we have enough information to try to err on the side of "Let's just assume everyone is a danger. Let's just globally reduce our cavalier, casual exposure to germs as a matter of course."
To me, it's crazy to insist we need to keep testing and we need to know who has it to protect people.
Social distancing and good hygiene are effective whether the person has been identified or not. I wish we would just go with that and stop acting like "a return to normal" is the goal and just around the corner for most people, if only we can identify the parties guilty of being infected and Target them.
It kind of doesn't matter. Just stop touching your face, among other things.
Good idea in theory, not so much in practice, especially over longer periods of time. First, people are fallible and many of them who don’t know if they have it or not, may not take it seriously. Having a positive test (even if asymptomatic right now) would put them in a different mindset. The ability of quickly confirm recovery would put the people in critical roles back to their occupation. Medical professionals, police, truck drivers, water treatment plant workers, utility workers are all going to get sick in droves and it is not going to be pretty.
Ontario publishes this statistic and updates it twice daily [1]. It was just under 2% but started to creep up. To understand the numbers better it helps to know that currently there is about a 6 day wait on the test results. Until very recently criteria for testing were very stringent (2+ symptoms, recent travel), and even then only 2% were found to have it, which - in my understanding - disqualifies the idea that virus was already around for a while.
Corona is killing a negligible % of the population, mostly very old and very sick people (checkout the official data from the Italian health ministary - average age of dead patiences is 79.5 years, all of them with severe background illness, in a part of the country where 29% of the population is at least 60 yeard old. Those are the facts.). If anyting, what we are experiencing is not a corona pandemic but a massive, global hysteria pandemic - much more dangerous.
That’s true only when hospitals are functioning. Corona spread saturates hospitals and then mortality goes up to near 10%, from the virus itself as well as other unrelated causes which get no ICU treatment.
Italy: 47000 cases, 4000 deaths.
This does not include the collapse of the ICU system, meaning people with stroke, heart attacks and other life threatening conditions do not get optimal (or any) treatment.
Maybe, maybe not. Until we get the hard data regarding what is happening in London, we can't say anything definite.
Look at Italy - it was a horrible pandemic - until we got the data, which made it much more reasonable.
So now Italy's pandemic has gone from "horrible" to "reasonable?" It's CFR is increasing, not decreasing. The number of cases is increasing exponentially, not flattening, and the death rate in human terms is approaching 1K per day. I don't know what world you live in, but here in reality, this is horrible.
Just as a side note, Italy had almost 50k death in 2015 - from respiratory diseases alonr. No one was crying 'Pandemic!!' when that happened. Adjusted to population size, this is 4 times mord then here in Israel. Italy has 21% smokers rate, many many of them are old. These data (and more) is unique to Italy, and the reason why corona is so deadly THERE. And in any case - what would be the death rate and for how long if the entire world implements alengthy lockdown?
In the US, 1 person dies of cardiovascular disease every 37 seconds. Since no body cries in the media 'Pandemic!!' (although it is a very real one), I guess that its not the total number of deaths per day that is shocking, its the exponential growth.
The growth is indeed exponential, there is no doubt about that, but what is its potential?
Judging from the data we now have from Italy and the rest of the world, it has a very small overall potential - the very old and very sick (obviously we have to take care of them, but a global hysteria??).
What is the equivalent? Say you started a new web service, that is wonderful and very attractive and cost effective and what-have-you - but only for people who's name start with the letter K.
The media is exploding with compliments, subscriptions are going through the roof, all the celebs who's name start with the letter K subscribe and praise etc etc, and you indeed get an exponential growth - for just a few days.
Then the source dries up. No new subscribers. All the potential market is exhausted. You end up with a few million subscribers - and no more growth what-so-ever, exponential or linear.
In 2015, 1 italian died of repiratory diseases every 11 minutes or so. Covid-19 is a respiratory disease, and given the fact that Italy has a vast population with severe respiratory issues (unlike many many other countries), covid-19 just made the already bad situation worse. This is definitely NOT the situation in the rest of the world.
Not the op and I don't know where the age data is but for the regional data on confirmed cases, tests and deaths, iterate the "24" in this URL up by 2 each day at 6pm Italy time to see them. Alternatively go to the main domain and go to the 'news and media' section
In America at least, the functioning, advanced health care system is a barely accessible to people who are unemployed, and the government doesn't look like it's going to do anything to change that soon.
"Studies have found people are most likely to accumulate large medical debts when they do not have health insurance to cover the costs of necessary medications, treatments, or procedures"
You think there would not be widespread panic if we just let the health system melt down?
What do you think a world without a health system would look like? Unemployment is going to be very hard to deal with, but it really feels like the best option out of the very difficult choices we have in front of us.
Fact is, shit is seriously bad whichever way you look at it.
If we look at the Spanish flu, which was worse than this, there wasn't much panic and the economy recovered fairly quickly. Here's a random article I found online arguing that we'd get better results (both for public health and the economy) by testing more and isolating the at-risk populations than by quaranting everyone: https://www.nytimes.com/2020/03/20/opinion/coronavirus-pande...
Also, disease and death from disease was more a cultural norm at the time. From scarlet fever, diptheria, rubella, smallpox, dysentary, cholera, mumps, measles, chickenpox, on and on. Disease hadn't been conquered to the extent that the 21st Century world assumes. We've lived for almost eighty years with penicillin etc. This shapes how we will handle the pandemic.
A prolonged lockdown will cause - as a certainty - such a huge economical crisis, that all those people at risk we are trying to save today - will die tomorrow from non-existant care (along with many many others who will die and suffer).
The sad truth is that a lockdown and huge economic crisis that will definitely follow can't really save them (other options might help - but not this one).
Merkel publicly estimated 40-70% of the population of Germany would catch Corona this year. Let's assume that holds true for the US. The most reliable public numbers so far suggest 1-3% death rate. Let's assume that holds true in the US also.
US population is 330 million. The lower bound of the estimates above (40% catch, 1% of those die) is 1.32 million people die. The upper bound (70% catch, 3% of those die) is 6.9 million people die.
Just to put the above numbers into perspective. A fairly normal number of deaths in the US without Corona is 2.6 Million from all causes. We're looking at potentially more than tripling the number of people who die this year.
I don't care to get into the debate any deeper than that, just want to make sure we all understand the stakes.
But how many of those people would have died anyway? Somebody over 80 has around a 10% chance of dying every year. Somebody over 80 with Corona has a 20% chance of dying, so the risk of dying is doubled.
This is an excellent point.
I'm from Israel, and yesterday it was announced that the first corona victim has died.
The poor guy was 88 years old, suffered from multiple background illnesses - and suffered a heart attack a few days before he died - it so happens that in addition to all of the above he had corona.
Now, honestly - is this REALLY a corona victim?
Now check the data from Italy - most deaths were like that, and most of them could have equally died from the flu/common cold/brain stroke/just being old.
How far and deep will this madness go?
i don't understand why you got downvoted. We don't consider someone dying from a cold if he's 80yo with heart attack.
We're introducing a novel way of counting casualities, and this is problematic whenever we want to account for the severity of the virus.
Now on the other side, hospitals usually aren't flooded the way they are at the moment, or at least that's my impression. So there is definitely something special about the epidemic (although we don't know why : maybe it's just extremely contagious, and makes everybody become sick about the same time, instead of a natural spread for the flu ?)
Cardiac arrest has been noted as one of the results of COVID-19; it's not just the ARDS that gets you, but at some point, most terminal patients arrest.
Let's for the sake of the argument ignore all the deaths that would happen with proper care, young and old alike. A low double-digit percentage of all identified cases require hospitalization to survive. A double-digit percentage of those will die if they don't get intensive care. 40-70% of the population is expected to contract the disease this year.
It's not madness to take very strong measures to prevent that wave of hospitalizations from overwhelming the healthcare system. Most healthcare systems operate close to capacity, and people won't stop getting sick for other reasons while the epidemic is ongoing. This is the situation facing all countries with an advanced Covid19 epidemic.
But hey, it's a free market. Maybe one or two free-world countries will go on with business as usual, and we will get to see in practice whether the rest of the world was excessively careful. I wouldn't want to stake my parents' health on that when all indications say otherwise, but maybe someone else is OK with the gamble.
The percentage is from confirmed cases. For many many people, corona infection has none or very mild symptoms, and they aren't even tested. Since we don't know the actual number of sick people (which can only be estimated, with some estimations talking about several times more patiences then confirmed cases), the actual percentage is unknown.
> Predictions from any model are only as good as the data that parametrised it. There are two major unknowns at this stage. (1) We don't know to what extent covid-19 transmission will be seasonal. (2) We don’t know if covid-19 infection induces long-lasting immunity.
>How long immunity lasts for following covid-19 infection is the biggest unknown. Comparison with other Coronaviridae suggests it may be relatively short-lived (i.e. months). If this were to be confirmed, it would add to the challenge of managing the pandemic.
>Short-lived immunisation would defeat both ‘flattening the curve’ and ‘herd immunity’ approaches. Devising an effective strategy would be even more challenging under low seasonal forcing. It would also considerably complicate effective vaccination campaigns.
Why don't we know the extent of seasonal transmission? At the very least, we have data from areas that are in opposite seasons, even if we've yet to collect data on the transition from one season to another. Can't we get some insight from comparing the rate of transmission in Australia, where it's summer, to the UK, where it's winter?
This virus has spread just like you would expect it to if airplanes did not exist (probably because most flights are short range). And it started at the North Hemisphere.
The southern countries are all on the initial stages, and I doubt any one has any reliable number for transmission speed, due to both test limits and low numbers overall.
Yes: as usual with disease the poorest countries are going to be hit the hardest. If you think that Lombardy's medical facilities are bad, this will be quite the next level.
That, IMHO is the point that was only implicitely made by the original article : massive testing lets you keep the economy at least partially work, because you know who can go to work safely and who can't.
I really hope someone makes a deep study of the decisions that were taken regarding testing facilities in the various european countries, because i have the feeling, at least here in france, that doctors gave up a little too fast on that option (and i still don't understand why)
The wider this disease spreads, the more likely mutations and new strains will appear. This could very quickly spiral out of control. If you are insinuating that an economic shutdown will cause more deaths, you are probably incorrect. Although, we will never know the answer for certain.
I'm in india and may be I do not understand gravity of the situation, but I'm more worried about USA, here people are already scared as shit and most things are in lockdown, which helps the situation.
Something I talk about a fair amount: It's incredibly hard to measure what didn't happen but should have. Humans are really bad at that, and understandably so.
If we had adopted a lot of the practices being advocated currently and avoided the epidemic, no one would know or believe we had accomplished anything. Having a pandemic and defeating it is the only way humanity can know and understand with confidence that we need to make a lot of changes to make life work with so many billions of people on the planet.
I have a serious medical condition. I've gotten off all drugs. I know what my life is supposed to look like because I know what my condition is supposed to do. Other people have what I have. I know the typical prognosis.
Yet I have no credibility. I've been mocked and attacked and dismissed online for years because other people cannot see that I've done anything and don't believe I have. Other people can't see what I see and it makes me look to them like a loon suffering hallucinations, not a visionary that people ought to listen to.
I once had someone email me and tell me "I give my child the sea salt and coconut oil you've recommended, and he's in the ER less, but he's not on fewer drugs."
She meant he still was on the same amount of maintenance drugs as before. She wasn't really recognizing that fewer ER visits meant fewer rounds of antibiotics, steroids and similar.
The child was taking less medication, but the mother couldn't quite manage to count the drugs that weren't happening. In her mind, it would only count if her child could reduce his maintenance drugs.
There are a lot of things I hope we change. But the reality is that without a pandemic, no one would believe those changes actually provide germ control and actually matter to the functioning of the world. People would just find the restrictions annoying and pointless and would rebel against it.
You are only going to get compliance when enough people have been burned that change seems less onerous than not changing. That's basically how humans always handle things.
It's frustrating. I wish it weren't so.
But people don't change everything at great cost to avoid disaster based on predictions and models. We make those changes because we got burned in actual fact, not in theory, and we don't want to go back.
And then it's no longer hypothetical. Then it's actually real and we aren't running from Boogeymen. We're problem solving and dealing with actual reality.
We already have remote work. It may have already reduced our vulnerability and lessened the impact of this pandemic.
I'm not seeing that talked about. We have no means to measure how much worse this pandemic would have been without remote work, without the internet, without credit cards and PayPal and a zillion other things that already exist.
In most cases, we don't even try to measure the disasters that didn't happen. That gets viewed as talking out your ass, basically.
I have a form of cystic fibrosis. It isn't relevant treatment for anything for most people and coconut oil is medically recommended for the condition or, alternately, MCT oil. Coconut oil is high in medium chain triglycerides and has a long history of being medically recommended by doctors for serious gut issues, including stomach cancer.
I've seen citations for such. I don't happen to have them at my fingertips. But you (or anyone) can go looking for such if they are curious.
Illiterate politicians can still survive if they keep competent people in their surrounding. Our president pushed out the relevant people from national security council, kept his own folks, and did not listen to anyone in January.
Four years of presidency tenure has it’s downsides.
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[ 3.5 ms ] story [ 330 ms ] threadhttps://news.ycombinator.com/item?id=22635225
The rate of growth in the USA, extrapolated, is just huge. Looking at the whole curve it does not match an exponential well, I think the early part is skewing it. If we take the last 10 data points, they fall very well onto the curves for all 3 countries, and that curve for the USA is horrific. I'm not an epidemiologist nor statistican so it would be irresponsible to put my predicted figures here, but christ, if I'm right the US is going to be reeling in just a few day.
Edit: @mnl below has pointed out that infection is not an exponential but on the whole a logistics curve (s-shaped curve https://en.wikipedia.org/wiki/Logistic_function). He is correct. However in early stages I believe an exponential MAY be a decent approximation (and I'm reading up on it now). However, the inflection in the 'S' (where new infections would start to slow down) would be expected to be at far higher figures than those I'm looking at - a few tens of thousands of reported infections per country currently - and it's not even close to that (populations of multiple millions in each country).
See table at bottom.
Clearly something completely different is going on there than in many other countries, and it seems they have an extremely effective and well organised testing system. They're testing about 160,000 people a week. In comparison, the UK to date has only tested around 50,000 people in total so no wonder our case numbers are far lower, even though we have double the number of deaths.
So Germany is an outlier, but it just goes to show even for other countries you can't just compare the curves and draw any definitive conclusions without also looking at the testing regime. This is where the experts with their detailed population models and simulation tools come in.
Take numbers from a region where testing is frequent, say the death rate is 2%. Then scale the numbers in a region with lack of testing to match the 2% death rate.
Not perfect, as there are external factors like hospital capacity/quality and existing population health.
However, it should give a closer approximation of total cases where politicians fail to provide adequate testing.
Do you have any statistics pointing to obesity as an increased risk factor for a respritory disease?
Also there is the purely anecdotal hypothesis of a cultural difference between for example Italy, Spain and Germany. In the southern countries it seems like older people have quite an active social life compared to Germany.
https://www.youtube.com/watch?v=0M4kbPDHGR0&feature=youtu.be... turn on google auto translate
TLDR: Any comorbidities present at the time of death are reported as the main culprit. In other news https://www.thelancet.com/action/showPdf?pii=S0140-6736(20)3... Table 2: Treatments and outcomes. Sepsis 100%, Respiratory failure 98%. There you go, nobody dies from the virus alone, problem solved, 20x less deaths than comparable Spain.
I keep asking people about this because I'd for sure would like to know if it were happening, but the only two sources I've seen sounded like speculation by Italian officials that at least as absolute as it is reported in other languages does not match the actual reporting here as far as I can tell.
Look for ILI (Influenza-like Illness) stats which were appreciably higher in January. The obvious inference is that many had Covid-19 before it was recognised as such.
This might be a good thing.
I know a person who back in January acquired something like pneumonia and a bad fever, went to the hospital for awhile and tests were negative for flu, etc. doctors just didn’t know what it was. The person has COPD however.
But anecdotally I’ve noticed quite a few more colleagues over the last few months out sick “with the flu or something”. No idea.
They’re still only testing people with symptoms. We need a randomizes test and a test for antibodies to have any idea how much it has already spread.
If it’s as contagious as they say and spreads in asymptotic people then why wouldn’t there be a significant population that has acquired and recovered from this? Many probably with very mild symptoms.
I could just be in denial right now as well.
Because all the effects are limited by the time it takes for them to happen. We know the speed of growth, it's much faster than the expected recovery times. From all known COVID-19 cases the number of recovered are still dominated by the recovered in China.
Virus causing COVID-19 is "novel" meaning not existing among humans at all until a few months ago.https://www.nytimes.com/2020/03/10/us/coronavirus-testing-de...
The only places I've seen the first US infection being dated that early are conspiracies on Chinese social media that claim the origin of COVID19 to be the US instead of Wuhan. The only way that theory works is to date the first infection in the US and claim that Americans bought it into China during the Wuhan Military games. That theory is easy enough to debunk with common sense because if the US had COVID first the hospitals would be completed overwhelmed before China's was, but it's not the first time wishful thinking's buried common sense in Chinese history.
Especially asymtomatic. You’d not be coughing or sneezing more than usual which must have some effect.
Just a thought. No one seems to have mentioned this idea.
Or the fatality and hospitalization rates have been overestimated due to severity bias.
We know this to be true, actually. We just don’t have good estimates of what the true rates are.
It wouldn’t be shocking at all to find out the virus is already widespread, and only slightly more dangerous than influenza.
Even in Italy, if there is widespread infection, the ~4k dead would reflect a low mortality rate.
In italy in hard hit city, they were unable to cremate people fast enough and army had to move bodies. Influenza does not cause that.
The error bars on CFR estimates run from fractions of a percent to a few percent. In countries that have tested large numbers of people who are not severely ill, the case fatality rates have been at the low end of that range.
This isn’t “shocking to epidemiologists”, it’s shocking only to people who dismiss basic facts and try to use irrelevant distractions (like cremation rates) to incite fear.
Epidemiologists do count with overwhelmed hospitals and services, excess deaths due that that, excess deaths on unrelated heath problems. It not just something they talk about, they have it in their models too. This does not happen with influenza, because it is easier to control. Irrelevant distraction there is Italy or Spain lately.
Epidemiologists do talk also about costs after epidemic ends, in treatment of people who will need care for long.
What amateurs do is to ignore all the above, pick up case fatality ration in well run non-overwhelmed health care system and pretend that is situation same as influenza to feel good.
Not that I have heard of. You’re going to have to cite some evidence here.
(They’re both respiratory viruses with similar R0, so your evidence needs to be pretty extraordinary to be convincing.)
I don't know anyone that credibly believes it was in the US in November. We did, however, that something was amiss that early, and if the US had a pandemic response team who's job was to see something like this coming, we could have been getting testing ready since then.
That’s exactly what happened to my dad in February.
What are you referring to? You don’t think the virus is already much more widespread in the US than currently reported numbers? I’m just making the observation that perhaps the large increases in US cases are more indicative of confirmation of already existing cases rather than necessarily being _new_ cases.
I don’t think that’s crazy at all. We had our first case sometime in January, and only until very very recently have we had any significant travel restrictions. It’s very contagious and for a significant number of people there are no real symptoms, or if there are, nothing life threatening. I don’t think it’s crazy at all that it’s been working it’s way around the US population for months.
Maybe to put it another way, if we could instantly test al 300+M Americans right this instant, would you be surprised if say 20M or so tested positive or had had it?
Yes, I would be very surprised. Given what we know about severity distribution that means 2M hospitalizations and ~200K-1M ICU cases that we somehow missed.
The problem isn't just that a lot of people will die because the health system is swamped. That's hardly good news, but when you have a high peak you have a lot of people ill at the same time. And that means you run the risk of losing a significant percentage of critical workers in essential services including food, utilities, logistics, and IT.
Some will die, some will "just" be very ill and unable to work for 2-4 weeks. If you're lucky the numbers of seriously ill will be low enough to keep things running. Beyond that you're on a scale from frightening inconvenience and breakdown in some locations to the economic equivalent of critical organ failure.
Pushing any country through this is a huge and utterly irresponsible risk.
The number of "cases" reflects at the moment the capabilities of the whole medical system in each country (it's dependent on who is selected to be tested at all) and the tests used. The number of deaths hides less. Also, even if the specific numbers can't be compared 1 to 1 across the countries, the characteristics of the curves can.
The growth is fast but it is comparable, and the measures take time to affect it.
Of course that’s assuming the labs doing the testing are doing it first in first out.
It's a risk, but the amount of hardship all the people who lose their jobs and business will endure if an indefinite lockdown is implemented is an absolute certainty. Poverty has lasting, lifelong negative health impacts.
Scary that the US (especially some areas) and Switzerland are starting to track above Italy:
http://nrg.cs.ucl.ac.uk/mjh/covid19/20mar2020/covid-us-norm....
This analysis is difficult because it is related to testing capacity. We all know testing capacity was limited early on. It remains limited, but is growing. The faster capacity grows, the steeper the curve will be. Want to have a less steep curve? Lower the amount of testing.
In another comment, you claim looking at the curves leaves out politics completely, but it doesn't. Any politician can make the situation look worse on the curve, but better serve their people, by increasing testing. They can also make their curve look better, but do worse for their people, by claiming their state is unable to purchase tests. This can be a very political game.
They are more reliable than the simple number of cases but in the Italian province of Bergamo (and I suppose in neighbouring Brescia, too) lots of people have started dying before the ambulance even arrives at their homes. Those people will not show up on the official statistics of covid victims, at least not now.
A similar thing had started happening in Wuhan once the situation had become really dire, and the closest valid indicator people could find was to look at the number of incinerators and how busy they were (mostly looking at the number, because the incinerators were busy 24/7 anyway).
That works only at the beginning.
But not all symptomatic people receive tests.
Knowing those two number (number of symptomatic people who would have qualified for a test, were it available; number of test performed) could paint q better picture.
https://www.worldometers.info/coronavirus/country/us/
Here's a good article on estimating current number of cases from number of deaths:
https://medium.com/@tomaspueyo/coronavirus-act-today-or-peop...
As for that Medium article, it’s written by a tech exec with zero education or professional experience in anything related to medicine or the life sciences, so I would treat it with a heavy dose of skepticism. Many of the deluge of preprint articles from academic institutions written by epidemiologists or public health experts would likely be a far better source of info.
The numbers may be wrong in that article but the math itself seems straightforward. It's certainly true that we need more tests to be sure of the numbers.
Here's a pretty interesting simulation from a research group at the University of Basel: https://neherlab.org/covid19/
I guess you're suggesting that when people die of Covid-19, we'd know it and count it?
That's not true.
First, CT scans (and other expensive tests) are not generally performed on people who have died of pneumonia, apparently due to the flu (or other causes). Second, the radiologists reading those studies would have to train to make the distinction.
Now, going forward, we have an increasing need to know whether the virus that caused the pneumonia that killed the patient was Covid-19 or not, so maybe such testing will become routine. (I doubt it will be CT scans though, because there will be much cheaper and reliable ways to do it.)
But so far we've been undercounting Covid-19 deaths for the same reason we've been undercounting cases: lack of testing.
But it's a good point that we might have more deaths than we've counted, and this might just mean we're further along that we realize. The rate of growth is probably not just an artifact of more testing; it's similar to the growth rates in other countries that haven't gotten control of the disease. And we definitely don't have it under control.
We can compare the usual number of people who die of pneumonia with the current one, and any significant difference can be attributed to this novel virus.
https://fivethirtyeight.com/features/infectious-disease-expe...
Responding on March 16 and 17 to the question, "how many cases will the US report by March 29", their median prediction was 19,000. As of this moment, early on the 21st, that figure has ALREADY been exceeded (per Worldometer). Based on current growth rates, it appears virtually certain that the actual figure on the 29th will exceed the "best-guess" prediction of every single expert surveyed, and the "high-end" prediction of all but one or two. They've completely whiffed a prediction just a few days out.
This is a novel (no pun intended) situation, even for epidemiologists. To understand it, critical thinking skills are at least as important as subject matter expertise. My read is that the Medium article represents some of the best critical thinking on the subject so far.
https://www.imperial.ac.uk/media/imperial-college/medicine/s...
What's more sure, in most of the countries in the world, is that if the tests are available at all, and the patients happen to be admitted to the hospitals with the symptoms, they will be tested, and the percentage of deaths will be comparable in all countries, and we should be able to assume that the hospitals will report the deaths of the patients tested positive.
In short, now that the numbers of deaths increase, these numbers reflect better the issues we are facing than just the reported cases.
We should estimate the number of "comparable" cases across the countries or areas with different capabilities from the numbers of deaths, at least for the countries and areas which have at least enough tests to test those admitted with symptoms and report the dead, and once these numbers aren't too low to be too noisy.
I've demonstrated some of my simple calculations in my other messages, so you can check these too.
considering how the UK handles the crisis it won't be far behind the US either.
Yeah I knew by Sunday that tomorrow we're hitting 30,000 cases in Spain. My assumptions worked. And it's just the tip, because I don't know anything about whether there's been randomized sampling, so who knows about the normalization.
I just can't believe this. No one listens and this is in-your-face obvious.
(edit: good catch though)
(Of course this works as long as you aren't seeing any peaks)
oefrha, for some reason I can't reply to your comment just yet so I'll post it here: Of course. This is just my own criterion when I start with a bunch of data I know nothing about. Is there a complicated law behind them or maybe not? Am I seeing noise or there's a signal? You can fit anything smooth with a low order polynomial, so maybe there's a differentiable function right in front of you. It's just something I do and if you see no reason for it I might even agree with you on that. It never ends up in the model, though. It's just something I find useful at a preliminary stage.
OK, We're not being responsible doing this and I'm not qualified to do it. I just have been fitting the data and maybe I've been lucky and I'm just an idiot. Having said that, this is also my problem, I have right now a hotspot in the vicinity and I'm worried. I just want to have a quantitative idea of what's going on. Now it's your job as experts to explain what's going on to the politicians and make sure they hear and they can do the right thing. I wouldn't be worried if the messages had matched the numbers when this started, they didn't. At some point we need someone to tell us "we're at this point and tomorrow we'll be at that point". I shouldn't feel compelled to find out by myself what all this is about. I feel awful by posting all this, I'm perfectly aware that non-experts in a field spout nonsense, but this is a very nonsensical situation and I'm tired of hearing we've been doing fine.
I stopped trusting any of my rudimentary models by Sunday+incubation, because conditions changed then. Which data, why I trusted them and the set of assumptions taken to consider them representative for the shape of the time series/distribution, that's something I don't think I should share here at this point. In any case I'm used to extract some information from imperfect data, you approximate and estimate. I mean there was by then 12, then 16, then 30 positives in a nursery home next to my door, and no lockdown measures, now there's 100, an improvised hospital there and I'm not allowed go out except for buying groceries. Two weeks ago I needed some picture which I wasn't getting anywhere, the alternative was freaking out after comparing what the authorities were saying with what I knew about the situation. Now they are making sense and the measures in place too, so I expect it getting much better soon.
I don't want to go into epidemiology and I want to respect and trust blindly the epidemiologists, but in any field you expect the professionals having predictive skills working before your eyes, that's their job. Hearing that we should wait for the post-mortem to know where we are now, I mean, come on... And now I'll just shut up.
Can you clarify. I can modify the top post (mine) if you're saying I'm overstating things. Happy to be wrong here.
(what I thought you might have meant was a criticism of me misusing maths and you were getting pissed off telling people it was a sigmoid not an exponential).
My key takeaway was that once you see the inflection point, you know that you’ll have roughly 2x the number infections by the time it’s done.
As you can imagine, there's more to epidemiology than this. I'm a big fan of letting the qualified people do their work, while we do ours: shut up and do not spread misinformation.
In fact, at the risk of being rude ill even go so far and say that it's quite arrogant to pretend to pontificate about this when your knowledge about this issue is 0, and also when one major problem in combating this pandemic is the "epidemic of misinformation".
Many doctors lack training in epidemiology. Many epidemiologists aren't actual doctors.
Healthcare in general is horrible with generating accurate raw data (JHU data comes often from scraping websites and the CDC itself has stopped publishing number of daily tests weeks ago). <-- this in fact is a technical problem not a medical one!
You don't have to be a Dr. med in order to see gaps and problems with statistics and a large part of the conjecturing actually comes from gaps and flaws in the sources and the way data is presented. A background in an isolated discipline (only med, only statistics, only Math, etc) is not enough to harness and make sense of complexity.
Finally research papers themselves are all pre-print and not peer-reviewed which is a trade-off in accuracy for speed.
We're all finding solutions as we go and the more eye-balls from different discipline this gets, the better the outcome!
Yes, and this is why doctors aren't being asked to do epidemiology and epidemiologists aren't being asked to care for patients.
And (likely) sofware engineers are not asked to do either.
I made it clear the limits of my knowledge - which may still not excuse me, however I have to ask if you are an epidemiologist and if so, please tell me how to model the data better. And I don't mean randomly google up some papers to dump here and pretend you are an expert (unless you are).
How far can I extrapolate e^x before it becomes useless? What are the confidence limits I can use in the extrapolation? How much can I approximate the logistic function with an exponential, when as now, the cases are currently a small fraction of the population? Why is this site http://nrg.cs.ucl.ac.uk/mjh/covid19/ done by experts using log axis any different from mine using curve fitting with exponentials? Why does http://nrg.cs.ucl.ac.uk/mjh/covid19/#w say the USA is 11.5 days behind Italy whereas my amateur attemp suggest ~9 days? (and yes, I wish I'd seen these graphs before I posted) What else have I missed? Criticise freely, with reason, don't just accuse me of misinformation because I posted my fears, which others have done too, only I did the maths.
Now please excuse me while I look at the logistics curve and compare its early stages with exponentiation.
There is no "actual data" in your comment above. There is a claim that you make that you have graphed some data, but no graphs and no data.
Also, it doesn't take an epidemiologist to know that a non-epidemiologist should not play at epidemiology. The other poster doesn't have any responsibility to tell you "how to model the data better".
There is in http://nrg.cs.ucl.ac.uk/mjh/covid19/#w which I said matches what I've found rather well.
> The other poster doesn't have any responsibility to tell you "how to model the data better".
Yes he does,
There may be data there, but if I understand you correctly you did not have it when you made your first post.
It is therefore inadmissible evidence as to whether your first post was a reasonable thing to write.
> Yes he does,
If you have decided you want to be an epidemiologist, or at least to learn their skillset, whose responsibility is it to fulfill that desire?
I don't think there is a reasonable answer to that other than "mine."
correct
> It is therefore inadmissible evidence as to whether your first post was a reasonable thing to write.
Completely wrong. I approximated the lowest part of a logistic function with e^x, which is reasonable for small values. Given it matched well with professional epidemiologists' graphs, it suggests I'm getting it approximately right.
> whose responsibility is it to fulfill that desire?
Mine and yours. Don't stick 'reasonable' on your replies and suppose it insures you in any way cos it doesn't.
With this in mind I think we should stop nitpicking on non-specialists who try to raise awareness of this pandemic.
Yes there might be some differences from what a specialist would have done.
Due to the speed at which the situation evolves and the inability to test everyone daily there are lots of unknowns so even a specialist may not be able to give a more much precise figure, everything is going to be a rough estimate.
This is a very serious situation and it's better to err on the caution side, people's lives depend on everyone doing their part.
Non-constructive criticism of people who raise awareness will erode people's buy-in and people will die because of this.
But I'll try to help. You're looking at a graph of confirmed cases, in other words, positive test results.
That may be due to an increase in the number of infected people; or because the number of tests being performed is increasing, and therefore the percentage of infected people reported as confirmed cases is increasing; or because some positive test results (even with confirmation) are false positives. And there may be other causes that I don't know, because I'm not an epidemiologist either, just a statistics grad student.
Figuring out the the contribution of each cause is a job for the professionals.
May I ask, what area do you work in, numerical, discrete, logic, other?
I too am tracking the numbers. I seriously and honestly expect them to become unavailable- or at least very hard to get to, if things go very very bad.
I expect to see a bump in the "infection rate" in the next few days as testing becomes more widespread. In fact, I expected to see the start of that already, but if it's happened it's not obvious. The number of cases continues to double every two days and change.
Rather than admonish people to shut up, it would be more constructive to point out the flaws in their methods, so we could all learn and make better judgements.
Yes, but that's the thing isn't it? We're not informed, and fitting ke^x to data doesn't make us informed.
This reeks of Dunning-Kruger. I get that the intention is good, but we have to have some humility and not go all "hold on! I'll save the day!"
> and fitting ke^x to data doesn't make us informed
Well, yours is an interesting post but let me ask if curve fitting doesn't make us more informed then what does? There's an update to the data for the US in the past few hours and it doesn't improve things.
I very carefully stated out my limitations, and then pointed them out again when someone critiqued my approach (see edit on https://news.ycombinator.com/item?id=22645793). I have done my best to accept my limitations, but still I get people like you hammering me.
So the question is why are we even posting anything on HN? Bottom line is what is HN for - non-factual debate, or factual debate?
I strongly get the impression that much criticism isn't based on my admittedly trite analysis but because a lot of people just don't know how to handle really bad news and are trying to blank a nasty reality. Doubly so when I'm accused of of "hold on! I'll save the day!" which is purely your invention.
No, you just made a large number of flaws in your initial analysis, and it made people despair of going to the effort to point out where you went wrong.
E.g. https://news.ycombinator.com/item?id=22648730
You're producing a future estimate, assuming that all properties of your dataset are consistent (they aren't) and will continue to hold (they won't).
As a few examples: (1) varying ratio of confirmed cases to actual total, (2) % increase in testing per day, day-over-day, (3) varying time offset according to disease progression and symptoms presentation (aka testing).
You seem to be of the opinion that any information is better than no information. In scenarios like this, I'm of the counter opinion that bad information is actively harmful and inferior to no information.
Seeing as you don't have access to my analysis, you can't say that.
> You're producing a future estimate, assuming that all properties of your dataset are consistent (they aren't) and will continue to hold (they won't).
This is just vague stuff to put me down. I worked by confirmed cases in publicly available data.
> varying ratio of confirmed cases to actual total
I'm not sure what this mean but I went by the total confirmed cases, day by day. As for your 'increased testing', I'm fully aware the US is finally getting going.
> varying time offset according to disease progression and symptoms presentation (aka testing).
Why would the progress at different rates at different times in different individuals make any difference? I'm going by confirmed cases anyways so unless you know of a new strain with different characteristics that's starting to distort the figures (and there are possibly 2) then it makes no difference.
No, save your slapdowns for the people who push garlic as treatment. You are objecting to me for psychological reasons, not logical ones. You can go to the wiki page and see the growth day by day but you don't want to because it's bad news and you don't like that. Well, get used to it. Your life is going to change, nothing will stop that and the sooner you face it the safer you and your country will be. Hard times ahead. Good luck.
Like other people have said through this thread, it's rather simple: you don't know what you are doing, and at this time bad information is worse than no information, and it will hurt people. And reiterating my remarks on my first post: stop being so arrogant, this is really the only word to describe your attitude as far as I'm concerned.
And "I am a bloody genius [...] by plotting a bunch of points in a log scale" - I actually used the words 'admittedly trite' about what I did.
Whatever. This gets us nowhere. Your profile says you have a background in physics and logic/automated reasoning. I'm just a general purpose back-end dev. We're facing something that may kill more people than WW2, let's concentrate on that. Can we work together to do something useful? Thoughts?
throwaway_pdp09 isn't spreading unnecessary panic and their attitude has been anything but arrogant, pompous, or dogmatic. They are very open in admitting that they are not an epidemiologist. Saying f(x) = 9 and asking why their 'f' is wrong, and wanting to understanding its shortcomings and how to improve it, seems entirely fine to me. You are going to have to be far more specific on the harm caused by a lay-person projecting that we are fucked in 9 days, vs an expert's opinion that we are going to be fucked in 11.
If it helps, pretend this question is being presented and asked at TA office hours during Epidemiology 101 at university by someone who is considering going into epidemiology.
We are all here to learn.
Meanwhile, there's actual, harmful nonsense out there to rail against. Half-remembered gossip misinformation that spreads like an infectious disease with an R0 of 5. Complete crap, like holding your breath for 10 seconds will test for Covid-19, or that essential oils cure Covid-19 or that its eventual vaccine will cause autism. Fight that misinformation, not people who's latent interest in epidemiology has been awakened. Who knows, a reader here could be deciding to get a degree in epidemiology because of an interest sparked because an exp curve is too simple.
I'm just trying to make sense of things, same as anybody else. I don't think anybody's fucked either in 9 or 11 days, I actually have a great deal of faith in the United States and yes, I mean it, but bad decisions from high will cause a terrible amount of pain too soon. I just want to wish the US the best because they'll need it now more than any other time, probably in all it's history. I don't think WW2 stressed you as much as you are about to be now. Buckle up yanks and pull together, I believe in you! You will get through this.
How come? "Distinct outbreaks" just means the older state was underdiagnosed, not that the characteristics of the pandemics change.
Local saturation happens fairly quickly. Having 100 infected in one place is very much different to having 1 infection happening 100 different places when you look at it after a week
When you're looking at the "country" view, the "older state" gets lost in the transmissions happening from people crossing borders. So what I mean is, people have been flying back to the states with infections spread out over the entire country while cross-border spread has been much more localized in italy
I still don't see the difference? Why do you think that the cross-border movement of the disease should be different in Europe compared to the US? Why do you think that the US should be worse off, if that is your point? Do you think people more fly back to the US compared to the people moving from country to country recently in Europe in the last period (including Italy)? Are you aware of how Europe functioned up to now? Many people worked in other countries, and they typically don't even have to fly to achieve that, especially not across the ocean.
Then, I fear, St Patrick's day partiers will only be measured by next Wednesday; 5 days incubation + 5 days to have test results.
Obviously it's only one day so time will tell if that means anything or a pattern occurs. As others have said, the stats for number of people affected is so closely linked to testing rates which have been increasing that this could be a more indicative metric to follow.
[0] https://www.worldometers.info/coronavirus/country/us/
For the numbers to have meaning, a stochastic sample of the population should be tested at random, not people coming forward because they think they’re sick.
One of the foremost experts in epidemiology in the US Michael T. Osterholm said on Joe Rogan (AFAIKR) 6-12 months for the virus to go away, up to 5 years for a vaccine and that it would return in China when people start behaving normally again. This isn't something that will go away in a few weeks or months.
In "Deadliest Enemy: Our War Against Killer Germs" he also predicted a Corona virus coming from China.
In a months time the US will take the place of Italy and see the healthsystem crash.
The number of positive tests and death rates are published every day on all channels. I wish the number of performed tests would be also published daily. What gets measured gets managed.
I wonder what limits the number of tests that can be performed. How much would it cost to ramp up testing capabilities so that every person with symptoms can be tested? How much to increase it to a level that everyone can be tested?
At first we didn't have enough test, but that ramped up quickly, then we didn't have enough RNA extraction reagent, now we don't have enough swabs, and soon is the collection media that will be missing.
There has been a call for more protective equipement. But as the situation gets worst, beds space, ventilator, and then staff are going to be the bottleneck.
If you google you'll find stories of people helping their local hospital by 3D printing parts for for respirators, and swabs. There's nothing cost effective about that, it's not fast, but it gets the job done. If you were to scale that, you would be competing for the same materials than manufacturers using injection molding or plastic dipping are.
Where are you getting this information from?
For swabs - here's an example in action up in Ontario Canada: https://www.ctvnews.ca/health/coronavirus/ontario-limits-who...
No one is out trying to actively hide this information, but its spread does seem a little uneven.
I also don't want this to be fearmongering. Capacity and supply will grow (hopefully fast enough). Alternative solutions will be validated. We will keep bumping into problems, and we'll keep solving them (cause we'll need to).
https://covidtracking.com/data/
We have tested 150K people.
We have 327M people in the US, we have tested 0.00046% of the population.
We do not have tests.
You didn’t multiply by 100 to change from per unit to per cent.
Still bad though.
https://www.biospace.com/article/releases/20-20-bioresponse-...
It's great that tests are finally ramping up but the growth in testing can never exceed the growth in cases if cases are doubling every finite number of days. The choices are a severe lockdown where R < 0.5 until the true case count drops to near 0, a non-severe lockdown where R ~1.2 - 1.8 (Hubei's lockdown had an R of 1.3 in the early days until they figured out centralized quarantine could bring it down to 0.4) and you just continue the lockdown indefinitely, or "herd immunity" where R stays at 2.4 until pretty much everyone in the country gets sick.
Once you get your true case load down below your test load, then you can think about using non-pharmaceutical interventions (universal masking, universal temperature screening, mandatory hand washing when entering into a gathering space etc.) along with rigorous contact tracing to ensure that any future outbreaks remain small and contained.
You don't need to test people every day for 14 days.
https://covidtracking.com/data/
At the moment of this comment that data says that ~2500 tests have been performed and ~2700 people have been tested. Perhaps those numbers were transposed. Maybe there is a simple, explainable mistake. But all the numbers everywhere are so full of errors, it makes casual statistical analysis just a fancy form of home entertainment at the moment.
I don't know how to get there from here, but I would like to see a great deal more focus on best practices and cultural change. That's how this pandemic will be stopped and prevented from recurring. Tests will only elucidate how bad it is, but aren't actual treatment.
Stop touching your face.
Stop touching everything.
Stop shaking hands. Maybe adopt bowing instead as a respectful greeting.
Wash your hands.
Be more supportive of remote work.
Design more services that help make flexible remote work a good thing for workers. (I like the Textbroker model. I've tried to promote that previously. No one cared or thought it mattered. Now, maybe people will pay attention.)
Light one small candle rather than curse the dark. Focus on promoting solutions. We don't do enough of that.
Of course, then people will say "we were just lucky" or the threat was never real.
But in terms of actual germ control, I would like to see more focus on shifting the culture to one of higher levels of germ control permanently.
But I don't need convincing. I already know this stuff is serious and makes a difference because of my medical situation.
Tests are information. I think we have enough information to try to err on the side of "Let's just assume everyone is a danger. Let's just globally reduce our cavalier, casual exposure to germs as a matter of course."
To me, it's crazy to insist we need to keep testing and we need to know who has it to protect people.
Social distancing and good hygiene are effective whether the person has been identified or not. I wish we would just go with that and stop acting like "a return to normal" is the goal and just around the corner for most people, if only we can identify the parties guilty of being infected and Target them.
It kind of doesn't matter. Just stop touching your face, among other things.
Everything I've read suggests that older, densely populated cultures pretty universally have adopted bowing over shaking hands, eat spicier foods, etc.
My belief is that over longer periods of time, cultural change is a much more reliable and effective means to combat disease.
"An ounce of prevention is worth a pound of cure."
[1] https://www.ontario.ca/page/2019-novel-coronavirus
Diabetes, high blood pressure, obesity: these aren't what people think of as "severe background illness", but all of these seriously increase risk.
Some evidence of this? Hospitals were completely overrun in Wuhan initially, but the mortality rate didn't get anywhere near 10%.
https://www.worldometers.info/coronavirus/country/italy/
I’ll respectfully disregard Wuhan numbers - no one knows for sure what’s the count other than the Chinese government.
London hospitals have started to become overwhelmed with patients, and this is only going to get worse. https://www.hsj.co.uk/news/hospitals-critical-care-unit-over...
Italy just had 793 deaths in one day. If you really want to "look at Italy" why are you ignoring all the Italian doctors?
https://www.independent.co.uk/news/world/europe/coronavirus-...
https://www.euronews.com/2020/03/12/coronavirus-italy-doctor...
At the moment one Italian dies from covid-19 every two minutes. https://www.bbc.co.uk/news/live/world-51984399
Post link plz
http://www.salute.gov.it/imgs/C_17_pagineAree_5351_24_file.p...
Hospitals fucked = lots of other people are screwed as they depend on unrelated treatments.
Heath system going out has huge cascading problems for society.
Worse than the huge cascading problems caused by making a double digit percentage of the population unemployed indefinitely?
That's deaths. With a functioning, advanced health care system.
Those numbers don't get better without that.
"Studies have found people are most likely to accumulate large medical debts when they do not have health insurance to cover the costs of necessary medications, treatments, or procedures"
In most cases, no job = no health insurance
If you want to talk about insurance and affordability: https://en.m.wikipedia.org/wiki/Patient_Protection_and_Affor...
That's what the entire marketplace concept was about. Admittedly, there are issues, but it's an improvement and something we can go farther with.
What do you think a world without a health system would look like? Unemployment is going to be very hard to deal with, but it really feels like the best option out of the very difficult choices we have in front of us.
Fact is, shit is seriously bad whichever way you look at it.
US population is 330 million. The lower bound of the estimates above (40% catch, 1% of those die) is 1.32 million people die. The upper bound (70% catch, 3% of those die) is 6.9 million people die.
Just to put the above numbers into perspective. A fairly normal number of deaths in the US without Corona is 2.6 Million from all causes. We're looking at potentially more than tripling the number of people who die this year.
I don't care to get into the debate any deeper than that, just want to make sure we all understand the stakes.
edit: corrected doubling to tripling
If 1 billion people get infected, that's 10 or 20 million people (or more). And so on with larger numbers of infected.
That's not 'negligible'.
We're introducing a novel way of counting casualities, and this is problematic whenever we want to account for the severity of the virus.
Now on the other side, hospitals usually aren't flooded the way they are at the moment, or at least that's my impression. So there is definitely something special about the epidemic (although we don't know why : maybe it's just extremely contagious, and makes everybody become sick about the same time, instead of a natural spread for the flu ?)
It's not madness to take very strong measures to prevent that wave of hospitalizations from overwhelming the healthcare system. Most healthcare systems operate close to capacity, and people won't stop getting sick for other reasons while the epidemic is ongoing. This is the situation facing all countries with an advanced Covid19 epidemic.
But hey, it's a free market. Maybe one or two free-world countries will go on with business as usual, and we will get to see in practice whether the rest of the world was excessively careful. I wouldn't want to stake my parents' health on that when all indications say otherwise, but maybe someone else is OK with the gamble.
In South Korea, where testing criteria are relatively broad, the death rate for the positive test group is over 1% (100/8700).
> Predictions from any model are only as good as the data that parametrised it. There are two major unknowns at this stage. (1) We don't know to what extent covid-19 transmission will be seasonal. (2) We don’t know if covid-19 infection induces long-lasting immunity.
>How long immunity lasts for following covid-19 infection is the biggest unknown. Comparison with other Coronaviridae suggests it may be relatively short-lived (i.e. months). If this were to be confirmed, it would add to the challenge of managing the pandemic.
>Short-lived immunisation would defeat both ‘flattening the curve’ and ‘herd immunity’ approaches. Devising an effective strategy would be even more challenging under low seasonal forcing. It would also considerably complicate effective vaccination campaigns.
The southern countries are all on the initial stages, and I doubt any one has any reliable number for transmission speed, due to both test limits and low numbers overall.
I really hope someone makes a deep study of the decisions that were taken regarding testing facilities in the various european countries, because i have the feeling, at least here in france, that doctors gave up a little too fast on that option (and i still don't understand why)
Something I talk about a fair amount: It's incredibly hard to measure what didn't happen but should have. Humans are really bad at that, and understandably so.
If we had adopted a lot of the practices being advocated currently and avoided the epidemic, no one would know or believe we had accomplished anything. Having a pandemic and defeating it is the only way humanity can know and understand with confidence that we need to make a lot of changes to make life work with so many billions of people on the planet.
I have a serious medical condition. I've gotten off all drugs. I know what my life is supposed to look like because I know what my condition is supposed to do. Other people have what I have. I know the typical prognosis.
Yet I have no credibility. I've been mocked and attacked and dismissed online for years because other people cannot see that I've done anything and don't believe I have. Other people can't see what I see and it makes me look to them like a loon suffering hallucinations, not a visionary that people ought to listen to.
I once had someone email me and tell me "I give my child the sea salt and coconut oil you've recommended, and he's in the ER less, but he's not on fewer drugs."
She meant he still was on the same amount of maintenance drugs as before. She wasn't really recognizing that fewer ER visits meant fewer rounds of antibiotics, steroids and similar.
The child was taking less medication, but the mother couldn't quite manage to count the drugs that weren't happening. In her mind, it would only count if her child could reduce his maintenance drugs.
There are a lot of things I hope we change. But the reality is that without a pandemic, no one would believe those changes actually provide germ control and actually matter to the functioning of the world. People would just find the restrictions annoying and pointless and would rebel against it.
You are only going to get compliance when enough people have been burned that change seems less onerous than not changing. That's basically how humans always handle things.
It's frustrating. I wish it weren't so.
But people don't change everything at great cost to avoid disaster based on predictions and models. We make those changes because we got burned in actual fact, not in theory, and we don't want to go back.
And then it's no longer hypothetical. Then it's actually real and we aren't running from Boogeymen. We're problem solving and dealing with actual reality.
Then you see real change.
We already have remote work. It may have already reduced our vulnerability and lessened the impact of this pandemic.
I'm not seeing that talked about. We have no means to measure how much worse this pandemic would have been without remote work, without the internet, without credit cards and PayPal and a zillion other things that already exist.
In most cases, we don't even try to measure the disasters that didn't happen. That gets viewed as talking out your ass, basically.
I’d rather you not talk about your homeopathic alternative medicine in the time of a real medical threat.
I've seen citations for such. I don't happen to have them at my fingertips. But you (or anyone) can go looking for such if they are curious.
Four years of presidency tenure has it’s downsides.