IMHO, this article is intentionally misleading. The incubation period is currently estimated to be 2-14 days (mean is 5.6 days per CDC, similar per WHO). The article doesn’t mention any dates or time frames, but does mention:
”Roughly 60 percent of the over 600 sailors who tested positive so far have not shown symptoms of COVID-19” — note how “so far” is ambiguous in that sentence. It also states, “The Navy’s testing of the entire 4,800-member crew of the aircraft carrier - which is about 94% complete...”, which seems to indicate nowhere near enough time has elapsed to draw any sort of conclusion.
This paper [1] found that testing of all pregnancy patients in a hospital yielded 34% asymptomatic cases. That number drops to 8% “shortly after discharge”, and could be lower than 8% (Again, no timeframe is stated).
I don't think it's intentionally misleading, but it is disappointing, how even the 'beat' reporters on this issue of intense international interest don't ask about, or highlight, the open questions, like:
* were these PCR tests (of active viral RNA presence) or antibody tests (of past infection). It's probably the former, meaning 600 cases is a floor, maybe a low floor, on the total number of infected plus recovered.
* the timeframes of testing, & to what extent testing-windows overlap all those who earlier reported symptoms/concern – & any followup to see who was merely pre-symptomatic.
* the total impact on the crew in terms of deaths and serious cases. (Mentioning 1 recent death and 5 current hospitalizations doesn't reveal how many total hospitalizations, or serious ICU/ventilator cases.)
Maybe some of this is because the Navy is holding back details (possibly for legitimate operational reasons). Maybe these wire reporters are stuck rewriting limited primary material released as someone else's press-release or transcript. But it's frustrating when the obvious next questions haven't even been asked or acknowledged.
The article isn't clear what kind of tests these were.
If, as is most likely, they're PCR tests for viral RNA, then they'll only detect active (or recently-active) infections. So anyone who's gotten-over an infection, symptomatic or not, will test negative. The number of infections reported here is a floor on the actual number who have been infected – which could be 2x, 4x, or more.
If instead these are antibody tests, then they're only indicating 600 total infections. But that kind of test is less likely here: such tests are not very useful for diagnosis of active infections, as they only turn positive late in a case. They could be useful for tallying past infected status – but there's a lot of rumbling that early antibody tests haven't been as reliable as hoped.
That's actually in the range of possibilities, I guess.
The best current data on the IFR for 20-40 year olds is low enough that you might not get any deaths out of a ship-wide infection[0], so you don't have the same "Where were all the dead bodies if this ran through the population earlier?" question you do for cities and countries.
The current estimate of the recovery time is around 25 days, and the date of exposure is believed to be March 5th. Assuming we're looking at an exact snapshot of infections today, that gives you March 23rd as the day everyone recovered on the ship was infected by, about 18 days after the first exposure. Assuming some small number (~10) were initially infected, that would only require a doubling period of ~2 days, which is shorter than seen elsewhere, but you're also in an ideal environment (close quarters, communal living) for spread.
I don't know if I believe that to be what happened here, but we should hopefully be able to determine it from the data after the fact with further monitoring and testing.
[0] There's been one, and you could have up to around 6 or 10 while being consistent with the current data; more than a couple dozen would raise a lot of questions.
It is possible there is large fraction of people who had the infection, but are not infected anymore. A serological would tell us the share of people with antibodies for this virus.
Yes, the logistic curves are lazy S curves and approach a limit asymptotically from below.
Here's the calculus: At FedEx, the BoD wanted some revenue projections. We knew (1) the current revenue and (2) the revenue for serving all the target customers. So, for time t in days, let y(t) be the revenue per day at time t, t = 0 corresponds to the present, y(0) is the current revenue. Let b be the revenue when serving all the target customers. Assume that the rate of growth in revenue, in dollars per day, that is, the calculus
y'(t) = d/dt y(t)
is directly proportional to (a) the current number of customers talking about the service and (b) the number of target customers not yet customers hearing about the service, that is proportional to y(t) and (b - y(t)).
Then for some constant of proportionality k we have the first order ordinary differential equation initial value problem
which is the famous logistic curve. So, this curve starts as an exponential and convex, rises, becomes concave, and approaches b asymptotically from below.
[On a Friday, I did the calculus, and a Senior VP of Planning and I picked a reasonable value of k, and I submitted the graph.
The next day at 8 AM was a BoD meeting. The graph was presented at the start, and two guys from BoD Member General Dynamics asked how the graph was constructed. At noon in my office I got a call from another SVP asking if I knew about the graph and could come to the meeting. When I arrived, everyone was unhappy; the two General Dynamics were standing in the hall with their bags packed and plane tickets back to Texas. FedEx was about to die. I calculated a few points on the graph; the General Dynamics guys stayed; and the rest is history.
The problem was, from the beginning of the meeting at 8 AM until noon, no one at the meeting could explain how the graph was calculated. The General Dynamics guys lost patience with FedEx, went to their rooms, packed their bags, and as a last effort returned to the meeting.]
Well the little calculus exercise is, say, an axiomatic derivation of viral growth, say, as for TV sets in US homes a few years around 1950. Well, a glance at the derivation shows that the solution should also be good for viral growth of viruses.
Can get the same thing from a continuous time, discrete state space Markov process subordinated to a Poisson process as in the book on stochastic processes by E. Çinlar, long at Princeton in operations research, etc.
> You can't have half person infected. At some point, everyone is infected and no new person will be infected.
Yes, of course. We all know that.
Can say the same thing for a lot of mathematical physics and other applied math. E.g., when a ball bounces, with the usual freshman physics view, there is a discontinuity in velocity so can't differentiate to get acceleration. General relativity considers mass-energy as a continuum and does differential geometry and uses differential equations, but a simple view of atoms is that they are points and not part of something continuous or we consider atoms as fuzz balls of uncertainty -- all that gets ignored in general relativity. We just saw a general relativity application: A star orbits a black hole at the center of our galaxy, and each orbit is more than 360 degrees around, like Einstein and not like Newton. That the star is made of lots of discrete atoms we ignore.
Such use of continuous and even differentiable several times functions to approximate discrete situations is standard. I saw that issue as a sophomore physics student. But there are no or not many famous research papers showing how using smooth functions to approximate does or does not work. Instead, people understand and accept that, when the discrete case has numbers large enough, we can use continuous approximations.
Heck, linear programming gets used in economic, production, and logistic situations where the real world items are discrete. Often works fine. Was the source of at least one Nobel prize in economics. Yes, when the numbers are small, especially just 0-1, the continuous math can flop badly, and we can encounter the grand question of P versus NP. But if doing resource allocation at General Motors producing 10 million cars a year, can do continuous math, and no one will care about half a water pump.
We can do predator-prey problems -- deer eating the grass, wolves eating the deer, eagles eating the dead deer and wolves, humans shooting the deer, raccoons eating the eagle eggs, the deer eating all the low forage, humans shooting the deer, etc. So, get a system of ordinary differential equations, right, for discrete deer, wolves, eagles, raccoons, and humans. Such equations need differentiable functions, all of which are continuous and differentiable approximations to discrete quantities that are not differentiable or even continuous. People have done that.
Can also attack such predator-prey problems with a continuous time, discrete state space Markov process (stochastic process).
Once in grad school, I mentioned to a prof that for predator-prey problems, the systems of differential equations and the Markov processes, thus, are approximating each other.
Indeed, once the Navy asked for an evaluation of the survivability of the US SSBN (ballistic missile firing) submarines under a special scenario of global nuclear war limited to sea. They wanted their results in two weeks. So it was lots of weapon types -- SSBNs, attack submarines, airplanes patrolling with magnetic anomaly detectors, planes that can drop sonar buoys and homing torpedoes, long range bombers, destroyer ships with good sonar, depth charges, and torpedoes, aircraft carriers, etc. with some numbers of each for each of Red and Blue. So, lots of Red and Blue things shooting at each other.
So for a solution I used a WWII paper by Koopman and saw a continuous time, multi-dimensional, discrete state space Markov stochastic process, wrote the code to generate sample paths, typically 500 for a particular case, using the Oak Ridge random number generator
X(n+1) = X(n) * 5^15 + 1 Mod 2^47
and the Navy got their results on time. Well, the results, the average decline of the SSBNs, looked continuous! Likely the expectation was continuous. So, we have a discrete stochastic situation that yields continuous expectation results.
Lesson: There are lots of continuous situations approximating discrete ones and expectations of stochastic discrete situation being continuous ones.
We are all supposed to know that lesson.
For my derivation for FedEx revenue, packages, and customers, each of those is discrete -- we know that. TV sets are also discrete yet nicely closely followed a logistic curve.
The virus infects people, who are discrete, but we would be foolish to ignore the role of an exponential which is continuous, differentiable, and infinitely differentiable, none of which the people are.
But as I gave at the end, can also get essentially the same result from a continuous time discrete state space Markov process, and there we can handle people one at a time, discretely, right to the end with the last person who gets infected and either gets well or dies at which time the process has an absorbing state and the exact result you mentioned -- no more continuous, asymptotic, limiting stuff.
So, as for the SSBN work, that Markov process addresses your concerns about the discrete nature of the virus and the last person to have the disease.
But for a curve for the virus, if you want to be careful down to the last person and not work with some curve that might have half a case, then there is no curve. Why? The spread of the virus is a stochastic process (random over time; at each time the value is a random variable) and not deterministic (if you will, special case of the general situation that nothing in the universe is deterministic). So, instead of a curve, all we get is a sample path of the process with discrete numbers. So, for analysis and prediction, we face many different sample paths. So, instead of looking at the blizzard of all of those sample paths, we consider expectations and confidence intervals, likely both of which are continuous, that we approximate with empirical averages, say, from running our model 500 times as I did for the SSBN fleet problem.
Lesson: Even if we handle the discreteness explicitly, due to the stochastic aspect, we are driven back to a continuous curve, an average approximating an expectation, that might end with 1/2 a case of the virus.
At roughly 10% infected the epidemic curve is in the steeply exponential portion of the curve, not the flattened end.
And, as a request, perhaps you could glance at the 'principle of charity' and choose some other term than 'vacuous' to describe an argument that your response clearly did not give sufficient thought to.
> And, as a request, perhaps you could glance at the 'principle of charity' and choose some other term than 'vacuous' to describe an argument that your response clearly did not give sufficient thought to.
Vacous is also a technical term[1]. The proposition
The general public may have had little to no access to testing back then, but the military certainly did. They may choose not to release numbers from back then, but the limited testing capacity existed is, IMO, quite justifiably used on people in the military. There’s plenty to criticize about the country’s response but lack of testing in the military isn’t one Of them, at least not relative to the broader (lack of) availability of testing to the wider public .
Even though an early WHO study showed 95% of cases will show symptoms within 7 days, they still don't know the average age of infection, so it is highly presumptuous to say they are asymptomatic.
Stanford’s study should give us more info soon. They recently screened a decent sized group in Santa Clara County to get a sense of how widespread it is, using their newly developed finger-prick test which looks for both antigens and antibodies (whether you have it / had it and recovered). Currently the test is being prioritized for frontline healthcare workers while they work on scaling up:
It's been 12 days since they tested everyone. My understanding is that the results for serological tests are available right away, so I was expecting them to publish results within a few days. Any idea why they haven't yet?
Perhaps they can't get statistical significance. You'd ballpark a 0.5% infection rate in the Bay Area going by deaths and current best guesses for IFR. Your false positive rate might exceed that.
These tests are better done in highly infected areas like NYC.
We have randomized PCR studies and ships where everyone got tested. Yes, there is error there (false negatives), but there's an upper bound to how much there can be.
Probably ended up with the same specificity problem that ruined the German antibody test. It's incredibly hard to test for just a single form of Coronavirus.
still hearing 2-4% infected rate between east coast and the Stanford testing, random tests. I think this article is suggesting it's possible a lot more people have/had it (and are hopefully immune for some unknown time) but we're just not seeing that in the general population yet.
It still feels like the general population is very underexposed to the virus :-/
Random testing in Germany has also revealed higher than expected rates of people with antibodies. Their IFR (infected fatality rate) was 2% overall based on non-random testing. Random testing has yielded an IFR or 0.37%.
This does not increase the risk. These tests only test people who had coronavirus. The larger this portion, the more herd immunity there is in the population. It implies that there were a larger than expected number of people who had the virus, at some point in time. But that's a lagging indicator.
Though that study has been criticized for the use of antibodies with cross-reaction with other Coronaviruses, so the numbers aren‘t necessarily to be trusted.
This is a general problem of antibody tests and precisely the reason why people should not buy those from any retailer (you can in fact do so online or in pharmacies). Unreliable and non-specific.
Let's wait for the development of specific viral antigen tests.
The lower rate was calculated based on only 7 or 8 fatalities.
Also the people in Gangelt, where that test was carried out, are significantly younger than the average German. Their share of people over 75 is 17% below the national average.
That isn't what I saw when I looked up their demographics, it looked roughly in line, skewing older even. [1] They had 12.8% over 75 as compared to for instance, 9% in Frankfurt [2]. Also in a population of 10,000-ish the number of fatalities would have to be by definition closer to 40.
Imagine all 65M people in the UK caught the virus then a 10,000 case fatality number would give a rate of 0.015%.
The rate itself has no time element so it tells you nothing about the number of people in hospital right now and hence isn't very illustrative of how hospitals can be swamped by this disease.
More interestingly (for me at least) is that the mortality rate is dependent on a patient's access to a ventilator. This means if you caught the virus early in the spread of the pandemic your odds of surviving are substantially higher than if you caught it right at the peak of infection.
This is impossible to reflect in a simple global mortality rate and so really paints a different picture of the virus - the death rate in South Korea vs other places really highlights this.
I guess to your point, hospitals are more in this way because the virus is so infectious, rather than it being a universally dangerous disease as may be seen from a higher mortality rate. Remember, a high number of people experience little to no symptoms from catching this.
This variability in symptoms doesn't seem to be as true for other lethal diseases like say malaria or dengue fever
> This means if you caught the virus early in the spread of the pandemic your odds of surviving are substantially higher than if you caught it right at the peak of infection.
I'd say your odds are best if you catch it some time after the peak. The hospital will be better prepared to prevent infections there and have more experience on how to treat patients best. There may even be some treatment that prevents the worst symptoms.
Also, if you (egoistically) try to get Covid-19 early, you may inadvertently infect others against their will.
In most cases, but the 1918 Spanish flu famously got more deadly after a mutation, if you got it early you were better off.
I'm still hoping to get it late assuming better treatment (or better yet vaccine), but I recognize there is no way to know if this is correct in this case.
The best case with mass immunity is that R drops below 0 and the virus burns itself out.
The worst case is that immunity primes the body for a massive and lethal immune system overreaction if the virus returns and/or mutates. This seems to have happened in 1918, which is why the second wave was more deadly.
Generally viruses seem to become less lethal over time, so this is rare and unlikely - and we'd be very unlucky indeed if it happened now.
But it isn't entirely impossible. The smart thing to do would be to have some high-quality monitoring in place to catch it if it starts happening, with high quality contingency planning for an international response.
In addition, this virus tends to prey on the weak. You don't want to have a pre-existing condition around Covid-19. If you look at the top causes of deaths in the USA in recent years then match well with C19's "favorite" targets. This instance, high blood pressure, diabetes, lung disease (e.g., COPD aka smoking), etc.
The last stat I heard was 40% of USA adults have a pre-existing condition. That's a significant amount of potential hospitalizations.
Access to ventilators has only a minor impact on mortality rate. About 80% of COVID-19 patients placed on ventilators die. (This is significantly worse than other forms of ARDS.)
Though my understanding is that the survival rate of a covid19 patient once he requires a ventilator is around 50%. If that's true, at worst, if we ran out of ventilators, the death rate would double. That's bad and we should avoid it but the doubling of a tiny number will still be a small number.
Which is why I am still confused by the ratio of 1:10 that the White House has shown between the death toll under lockdown vs no lockdown.
For the reason above, I would only expect the death rate to double. No lockdown means a lot more people get infected faster. But lockdown still requires to build herd immunity, we are only slowing it down. So the same number of people will get infected ultimately. So either they implied that the lockdown would be permanent until we get a vaccine (at best 2021 Q1), or it completely disregarded what happened after the initial few weeks of lockdown and then the numbers were at best grossly misleading.
Some 15% of people become “seriously” unwell, and require medical intervention such as oxygen. In a situation where the peak is hit unmitigated, these people will not get the medical care they need, and a lot of them will die.
The 15% looks implausible given the fatality rates mentioned here.
But I would expect a lot of the medical care to be scalable so unmitigated doesn't mean no medical care. We have been building field hospitals in the UK and US (though have barely used them so far), using hotels, etc. Providing oxygen should be fairly straightforward. I understood ventilators was the part that caused a serious scalability bottleneck.
Yes - part of the strategy of flattening the curve is to buy time to scale capacity. Dedicated covid19 hospitals also have the advantage of isolating covid19 patients from high risk non-covid19 patients (e.g immunocompromised cancer patients)
As the disease is so easily transmitted hospitals are partly buckling due to contamination within hospitals. A regular 50 year old probably has a good chance of surviving coronavirus. A 50 year old who is midway through chemo, probably less so...
All of this nuance is hard to express through topline death tolls and mortality rates.
The "We shouldn't have killed our economy for this" online comments miss some obvious truths - which is that the economy would be crippled by a high peak regardless.
At best people wouldn't go to work, at worst they'd struggle in and pass out - or maybe die - in front of their coworkers.
So the economy would have ground to a halt anyway as people stayed at home to protect themselves. But it would have done it in an uncontrolled way that didn't inspire confidence in a return to normality.
Which is the economic reason for flattening the peak. Serious damage was always inevitable, but there's a huge difference between a barely controlled but orderly temporary shutdown with mitigation measures, and a shutdown caused by mass panic and paranoia.
In fact even laggard countries have been forced to take some measures, because when their lives are at risk people and their managers act on their own initiative no matter what the official line is.
> But lockdown still requires to build herd immunity, we are only slowing it down. So the same number of people will get infected ultimately.
Yes. I've been saying that, too.
So, in blunt terms, currently we are trying to keep people alive until we can get therapeutics and/or vaccines that confer immunity so that we can get to herd immunity with fewer infections and deaths.
We've been on lockdown because approx 1% of the US population has tested positive. That means 99% are not. How can we come out of lockdown when we are effectively still where we started. We're not even close to herd immunity.
Not sure I agree with your numbers but I agree with your point, we are very likely quite far from herd immunity.
Which means another 18 months in lockdown if we want to stay well within the current ICU capacity until a vaccine is mass produced. Which means an economic downturn not only worse than 2008 (it will be worse already assuming we leave lockdown in a few weeks), but many times worse.
Or we can swallow this thing. It will mean more deaths. Trump says 10 times more. What I am saying is that I don’t understand how he gets there. If it is “only” two times more, then we need to have an adult conversation on how many lives are worth saving vs our society going through something akin to the great depression.
> If it is “only” two times more, then we need to have an adult conversation on how many lives are worth saving vs our society going through something akin to the great depression.
Why is it that only two choices ever exist when this argument is presented? Choose either death by virus or death by status quo economy. It seems like a more pleasant alternative would be reshaping our economic systems to be more resilient against such a crisis which will almost certainly occur again in the future. Maybe the current ownership and distribution models and how they relate to globalism aren't compatible with something that is now simply a fact of life.
The ownership and distribution models aren't the problem. The problem is that while everyone is locked up at home, no one consumes, we don't go to restaurants, to malls, we don't do tourism. And in some case we don't produce either, construction is halted, etc. There is almost no economic activity going on.
No economic model works when everyone is effectively on house arrest.
that we can not "be reshaping our economic systems to be more resilient against such a crisis" seems like arguing from faith. There is no natural law
that dictates that everything has to go to haywire just because things are on a pause, or that the current systems, particularly in the US, constitutes the optimal way to handle this.
We know that New York's hospitals are overrun. We also know that in countries where the hospitals aren't at capacity the mortality rate is much lower. Look at Wuhan vs the rest of China. Or Singapore/HK/Taiwan/South Korea vs Italy, Paris, New York.
So if ventilator access is low and doctors are triaging ventilators to go to the most urgent cases, is the data skewed towards severe cases and late access to ventilation support?
This anecdotal account[1] seems to suggest ventilate as early as possible to maximise the chances of saving a patient. So again, a global stat could be masking a time element and context to the data
These were among the very first cases in Germany where capacity was abundant, hence the low fatality rate.
Also, this is a “up to now” value, more cases might turn out fatal.
“Only” 7 deaths is furthermore not a good data basis for calculating this number.
Moreover, the report is not even public nor peer reviewed. So I can’t even cite it here. However you find criticism of the study by Prof. Streeck online.
The problem is the high number of infections. The virus is having a run in a population that has no immunity, unlike a flu. So it is spreading fast and in large numbers. A tiny hospitalisation rate multiplied by a very large number of people infected may be more than the hospital capacity.
Which is why both of these statement can be true at the same time: this thing is no more dangerous than the flu to an individual if you get it, but it can kill many more people than the flu because the population doesn't have any immunity and many more people will get it.
The majority of people that end up in hospitals actually survive the virus. Their symptoms are treated, not the causes, unfortunately. But you have to take these people in as they have (among other things) respiratory complications, hence the great demand for ventilators incidentally.
Infection Fatality Rate is certainly coupled to the number of people that develop severe symptoms, but it's not this number that you need to look at as to why people end up in hospitals.
Because it's spreading so very fast, and nobody has any pre-existing immunity to this new disease. The flu kills 60,000 Americans every year and so far COVID has killed about 10,000 -- over roughly the same flu season time period. The difference is that the flu is spread out over time and is fighting some pre-existing immunity and flu shots. It also has a lot to do with excess capacity. If there suddenly appeared a new disease exactly as fatal as the flu, that would kill another 60,000 Americans per year and 650,000 people worldwide. There's not really capacity for that.
Thanks, I grabbed the wrong column from my data. Either way that’s half the flu total over the same season. My point is that it isn’t unprecedented load, it’s just all at once — and additive.
That number only includes deaths in hospital of confirmed cases, a lot of people are dying at home particularly of heart attacks induced by oxygen starvation. The data from New York looking at excess deaths compared to the same period last year indicates that the actual number of Covid-19 related deaths is probably around double that.
Well it’s fair to say that neither has the government, if anyone dies in possession of COVID they’re automatically a COVID death, pretty much even if they get hit by a truck. That’s not true of the flu is it?
For a while the US was only counting deaths that happened in hospitals.
This argument -- that we're somehow over-counting covid-19 death -- doesn't hold because we can compare excess mortality this year against the previous 5 years.
Yes, it is. The figures that count covid-19 vs flu are available, and they use the same method. They look at death certifications and then statisticians code those. There's lag in those figures which is why worldometers don 't use that data.
> You're incorrect to say that if anyone dies with Covid-19 that they're counted as a covid-19 death.
I'm not. In some countries they absolutely do count anyone who dies while in the possession of COVID as a COVID death, for instance Italy. " Italy’s death rate might also be higher because of how fatalities are recorded. In Italy, all those who die in hospitals with Coronavirus are included in the death counts."
“On re-evaluation by the National Institute of Health, only 12 per cent of death certificates have shown a direct causality from coronavirus, while 88% patients who have died have at least one pre-morbidity – many had two or three.” [1]
In New York they're not just counting speculative COVID deaths of anyone with respiratory illness even if they've never tested positive [2].
"A subtler issue is what to do when the patient has other serious medical conditions. If the person suffered from chronic lung disease, then became infected with the virus and died of pneumonia, the immediate or primary cause would be pneumonia as a result of COVID-19. The lung disease would be listed as a contributing condition, said Sally S. Aiken, president of the National Association of Medical Examiners." [3]
The CDC has guidance on this but it's fair to say its interpretation will vary from place to place. "COVID-19 should be reported on the death certificate for all decedents where the disease caused or is assumed to have caused or contributed to death" -- that's pretty broad. [4]
My understanding is a few folks who committed suicide and a few who died in car accidents due to head trauma were coded as COVID, but I can't find my source on that and I assume it's pretty limited. I wasn't being literal in my earlier comment, however, and nor should this paragraph be considered as changing or doubling-down on that. I assume such cases, if they do in fact exist would be few and far between.
Hope that helps.
I also don't think it's fair to pin 100% of excess deaths entirely on COVID. We shall see, however.
And indeed they can be counted as COVID deaths if they had respiratory illnesses because the CDC direction is to count any suspicion of COVID or the contribution thereof as a COVID death. [1]
From what I've read the CDC has told med facilities to code any death that is even suspected to be C19 as C19. No test? Doesn't matter. Patient had other serious conditions? Doesn't matter.
With broader testing limited and deaths from being inflated the IFR should be suspect.
There‘s bound to be a high number of Covid-19 deaths that will only be obvious by looking at excess mortalities. At least preliminary data from the Netherlands and Spain indicates that.
The 2% number is 2% of people who have bad symptoms die. 0.37% is 0.37% of all people who get it, including those who have mild/no symptoms die. It simply means a much larger percentage of people get it, not that any less people are dying. I’d say there’s a good chance that many of us have gotten it, and spread it, without knowing it.
> The 2% number is 2% of people who have bad symptoms die.
I don't believe that's true. In countries such as Spain, right now there are about 80k confirmed recoveries and 19k deaths among a universe of 182k confirmed cases.
OP's claim was that "2% of people who have bad symptoms die."
From Spain's numbers, around 10% of those experiencing symptoms that lead them to get tested by Spain's health service, which due to scarcity is reserved for serious cases and people on the front lines, have died since the onset of the epidemic.
A majority of Spanish fatalities were in nursing homes and other restricted facilities. If the virus penetrates these places, average mortality spikes.
One possible explanation is that hospitals were already operating close to capacity. So even adding a small number (percentage-wise) of the population very fast, will cause disasters.
It's still going to be a giant number, but I recommend including the fraction estimated to catch the disease, in this case 0.7 because diseases with an R0 of 2-2.5 typically infect 70% of the population.
I thought there had been cases of people getting reinfected, and that how long the immunity lasts seemed to correlate to how sick you'd been. So the immunity of asymptomatic people wouldn't last very long. Maybe it'll last long enough to make a dent in the infection rate?
> I thought there had been cases of people getting reinfected, and that how long the immunity lasts seemed to correlate to how sick you'd been.
What they found so far is that some people had lower levels of antibodies than others, but that it did not correlate to how sick they were. It's also not clear at this point that anyone's been re-infected (although it is possible) because it's much more likely they hadn't recovered but had received a false negative test followed by a positive test.
And if some people can be reinfected after one exposure, it's not necessarily a death knell for a potential vaccine -- you get multiple boosters for some viruses for a reason, and the vaccine just has to take in a large enough fraction of the population to protect everyone.
Do you know any studies of the outcome of the 32 Diamond Princess patients that were the ICU at the time the boat was emptied? I have been looking and I can’t find any data on what was the final clinical outcome of all patients on the Diamond Princess?
It seems they are only tracking the Japanese deaths. It doesn’t seem like anyone is tracking the seriously ill who were transported home, or those that became ill once they got home. Even on these incomplete number the true death rate is 2%.
Adding to that, Netherlands' study of antibodies in blood donors' samples shows about 10x difference between the number of reported / tested cases and actual cases in the general population (i.e. a lot more people got it and were not sick):
The Netherlands has 3.3k deaths vs 29k confirmed cases, which would give a CFR of ~10%
I.e. the Netherlands aren't testing much.
A 10x reduction there brings it back to the CFR range we see in countries with bigger testing programs.
I'm not a specialist but have been following this for a while, and have yet to see evidence the IFR for this isnt around 0.5-1% (assuming decent healthcare).
That's what we saw in the Diamond Princess data, and a bunch of other places.
Pneumonia patients in hospital have their blood oxygen continuously monitored, with alarms if it goes too low because the symptoms of oxygen starvation are very hard to spot even by a trained nurse, but can be rapidly fatal. The most common cause of death is heart attack because the heart isn't getting enough oxygen. So these people dying at home probably think they're not at serious risk and don't want to take up a hospital bed from someone in a worse condition, so they try to tough it out but then they suddenly die.
These are also (usually older) patients who decide they don't want to go on a ventilator because they feel their quality of life, if they were to survive, is so low as to not matter.
These are decisions made in concert with the 'huisarts' (General Practitioner).
The middle part is an interesting point. A study of the first 50 hospital patients in Heinsberg (worst affected region in Germany) found that of 8 who had died, 4 had rejected ICU treatment.
In Sandinavia we see a lot of covid-19 related deaths at elderly care homes. These are older people, often with a lot of underlying deceases in addition to their old age. Very seldom these patients are moved to a hospital, so they die at the home with only palliative care. I guess in many cases they are not in any position to decline or accept ICU at all due to dementia.
Diamond princess skewed heavily towards an older age population, as did some of the hardest hit cities in Italy like Lombardi etc. To counter your point, there isn't any evidence to infer an IFR or 0.5-1% either. We simply don't know given the lack of antibodies testing in a randomized population set that's adequately representative of the right demographics in a given location (say NYC).
My current bet is younger healthy people are more likely to be asymptomatic. And older people much less so. Theodore Roosevelt with likely a young population, most are asymptomatic. Diamond Princess much older population most are symptomatic.
This is a thing I've been thinking about a lot. We're quick to say "We're not testing enough", but also quick to throw statistics around "disproving" the amount of asymptomatic cases. I am on the side of "It's probably orders of magnitude widespread than most countries think", and the number of totally asymptomatic cases is actually far far higher. You can't test only the old and the already sick and then accurately assess likelihood to develop symptoms. Your sample is totally wrong.
Humanity's understanding of this disease is much more sophisticated than the two comments above this would imply.
Researchers are not stupidly looking at Diamond Princess and getting confused because the population is old.
Rather it's a powerful dataset because it enables us to quantify the asymptomatic people of all ages, because people were tested fairly exhaustively before being allowed leave, regardless of symptoms, and because we've had enough time for many of the cases to play out.
The diamond princess data revealed a large number of asymptomatic cases in China, the absence of which were skewing the detected cases in China much older.
Anyway, you don't need to think anything complicated about correcting for ages, etc
You can just look at the data from the Netherlands where they conclude they have 3% population infection, by looking at the random serological testing, and then look at the number of confirmed deaths they have, and do the very simple math.
It's very hard to do that and then say we're missing say 10x higher numbers of asymptomatic cases all over the place.
Anyone who actually knows this stuff would never say that it’s a matter of “simple math”, that’s absurd. Those people have not been saying that they’re sure about anything at this point, because they’re not.
There’s nothing to prove you wrong yet either, of course, but let’s see how your prediction does over the next few months: between 14,400 and 80,000 deaths in Ireland.
The simple math comment was about estimating IFR, given the sampling in the Netherlands, not about the whole domain.
Maybe you are saying the implied model is too crude. Perhaps, but there's a value in it's simplicity - folks can get a convincing estimate of the rough scale of the IFR, that this disease is serious, not the flu etc.
> let’s see how your prediction does over the next few months: between 14,400 and 80,000 deaths in Ireland.
That prediction, was based on the measures in place over a month ago (very few, which was the point).
We're since in lockdown almost 3 weeks.
However, I think it remains a reasonable prediction for an unmitigated epidemic.
To go back to the simple math: If you believe that 3% of a random sample of the Netherlands have had covid, and that the Netherlands has had 3k deaths, then if 100% were infected they might have 100k deaths (without modeling clustering, and healthcare saturation effects). Their population is 3x Ireland's.
>There’s nothing to prove you wrong yet either, of course,
If the serological sampling had shown instead that their 3k deaths had come from 30% of their population being infected, that would have proved the prediction wrong.
There's loads of subtlety which could improve that estimate (people take time to die, clusters, etc) but there is an increasing body of evidence that the early IFR estimates were not wrong by an order of magnitude.
You really think that if your numbers don't pan out, it will be because Ireland somehow suppressed this thing (put that "genie" back in the bottle as it were), and not simply because its IFR is (or became) lower than you assumed it would be?
It's just splendid how a lot of people will criticize an estimate of deaths assuming no mitigating measures, and then say "see? no problem!" when the outcome is much better after stopping most economic activity for a month.
When you look at countries where front was, it looks different. It is quite cherry picking to pick the best off countties. One of then had no war on its soil (and earned finacially overall).
I would caution about taking dutch death numbers as truth. We have an acknowledged deflated death number. Because it states only confirmed cases, whereas we have a large number of home deaths (elderly deciding not to go through ICU traima) that are not tested and hence do not count.
People always seem to forget half of the Diamond Princess population was young, healthy, and under 35. Let’s not forget the crew were on board and infected, too.
It might also not only be age. Sailors on the Roosevelt are likely to be less obese than average, more fit, maybe lower rates of smokers (not sure) and certainly lower rates of other pre-existing conditions. That all puts them in lower risk groups. Just the higher share of men increases risk somewhat. But overall they certainly don't represent the average US population.
This is because they're testing the entire population as opposed to simply those who end up hospitalized and those around them.
We need population testing to get an actual idea of how many people in an area have it. There's likely way more cases nationwide than being reported. In NYC, most asymptomatic/low symptom cases of coronavirus aren't going to be tested until antibody testing later on.
if the US has 33K deaths and the death rate is 0.6% then the US must have at least 5 million cases. If the death rate is lower (most likely around 0.3%) then it means 10 million infections.
Those death rates in US are optimistic in my opinion. What if the actual rate is higher because of worse health in impoverished demographics, or the simple fact people might avoid healthcare because of its prohibitive costs?
They are now including many of the suspected (but untested) cases in their reported numbers now. It increased the total from New York by a significant amount, see [1].
The increase is roughly in line with similar estimates from excess mortality [2], so I would guess they are catching most of the deaths with the new reporting scheme.
these death rates come from published research if anything the death rates over across all age groups are even lower - this is a very common observation as initially most non-symptomatic are missed.
there is a very strong age dependence with this disease, and probably many other risk factors - predisposition to pneumonia etc.
If I understand correctly, research about the death rate is based on people who were tested positive (any source that's based on the general population?). This, depending on the region, could mean people with severe symptoms or non-randomly-selected test takers only. This adds much uncertainty to the estimated overall infection numbers.
It's not just cost. I'm starting to think that if I get sick (covid or otherwise) until the hospital overload subsides, I might have better chances to recover in my own bed even in a relatively severe case.
For each disease we estimate a number called R0, which is how many people the average person will transmit it to if no precautions are taken.
Herd immunity sets in when only 1/R0 people have not managed to get it.
With the flu, R0 is about 1.3. Meaning that herd immunity to a particular strain starts slowing the spread after about 1/4 of us are immune. (It can continue spreading for some time after that point.) I calculated that from the fact that 1 - 1/1.3 = 0.23076923076923076...
Herd immunity is derived from R0 and "susceptibility" percentage. The value for the latter also varies with disease and strain.
If you look at the Italian data, their % positive level never crossed ~30%, and overall averaged <20%. That might indicate that susceptibility for this agent is well below 50%.
If you look at the Italian data, their % positive level never crossed ~30%, and overall averaged <20%. That might indicate that susceptibility for this agent is well below 50%.
The more likely explanation is that social distancing was implemented early enough, and tests were given to people who might or might not have had it.
There is no reason to believe that we burned through most of the vulnerable people in the population.
This is also why people refusing the MMR vaccine is really, really hurtful to vulnerable populations. Measles R0 is like 15 or something - it's crazy infectious. So one kid in a daycare or class of 20 with parents who don't believe in vaccines is enough to push you under herd immunity. Bake in the fact that MMR vaccine is only ~97% good against measles, and you end up with a bunch of dead kids.
We got lucky last time around in Seattle area, in that it only cost us $1m and 0 deaths to get it under control.
Could you post a working version of that link? Most R0 estimates I have seen are between 2.5 and 3.5. 5.6 seems really high to me.
It is worth considering that even if the % immune is lower than the herd immunity level, it still slows the outbreak and reduces Re. That gives us a much slower ramp up and gives other measures like less restrictive social distancing, contact tracing, etc. a chance to work. Even if all those together only get Re down to between 1 and 2, we still benefit since it means we might only need another 1 or 2 lockdown periods before we get an effective vaccine.
> This is because they're testing the entire population
Not really, they are testing a population of only young, healthy and fit individuals with an obesity rate and other conditions absolutely not in line with the general population.
This figure does not surprise me. It is in line with Iceland finding that 50% of people they tested were asymptomatic.
However as https://www.propublica.org/article/what-we-need-to-understan... notes, in other samples about 75% of people who were asymptomatic at the time of the test went on to develop symptoms. So the fact that these sailors are currently asymptomatic does not mean that they will remain so.
Yeah, I think we should be more careful with using the word "asymptomatic" as that is quite different from "presymptomatic".
AFAIK COVID seems to have some case where people are purely "asymptomatic", but with this current hot topic of symptoms or not, lots of articles are writing about presymptomatic people they assume will be asymptomatic. Confusing.
Another big problem in this type of reporting is that majority of countries no longer test people who have mild symptoms or no symptoms. This means that there is bound to be many "unreported" cases as health authorities will not issue test you as they are overloaded.
It's not a big suprise. If you are following news from most countries, once it spread out health authorities stopped testing if you do not have significant symptoms and instead told people to stay home and isolate.
I'm very cautious with these type of studies. Lot of them are not clear in regards to how precise the test is, does it catch other coronaviruses as well, whether they did a follow up study to see if people developed symptoms or even how and when they picked their sample. All of these factors could radically impact the results.
It is, but I don't think the tests are able to tell how long a given person was infected. That two weeks incubation makes a lot of things harder. For example after implementing shelter at home or didn't look like it has much impact, but suddenly after two weeks it became very visible.
It makes things scary when we lift stay home, it will take again two weeks, and things can get bad quickly over that time.
To be fair, shelter at home not appearing impactful earlier on had as much to do with testing capacity ramping up + delayed results. If you’re massively undertesting, even if new infections are decreasing, you’ll likely see growing rate of confirmed positives as you scale daily tests.
Similarly, if the results are taking 5-7 days to return, it is entirely possible for new confirmed positives to skyrocket just as actual new infections are tumbling.
We also don't know yet (or at least I don't) how easily asymptomatic people are able to transmit the infection, which is why I'm perplexed by this quote from the article.
> “With regard to COVID-19, we’re learning that stealth in the form of asymptomatic transmission is this adversary’s secret power,” said Rear Admiral Bruce Gillingham, surgeon general of the Navy.
He says that they are contagious, but he doesn't say highly contagious (I know you're not the one who made that claim, I just wanted to clarify). I'm not sure if we know yet how contagious people without symptoms are, but it's most likely going to be less than a person with symptoms simply because they're no longer coughing.
Do you mind linking to the WHO source? Last I checked they said presymptomatic people are contagious.
It's why track and trace is so important and difficult. People are contagious after 3 days but first show symptoms clustered around 5 days. So we need to contact trace their last week or so. A lot of western governments have been unable to do this so they have decided to hope presymptomatic people are not contagious and just ask symptomatic people to self isolate.
Another factor is what is symptomatic. I had a weird tightness in my chest 2 days before my fever and a tickle in my throat 1 day before. Breathing issues started 4 days after fever. I had no clue the tightness was covid...
It seems like most everyone keep glossing over the fact that if you have a disease that doubles its infection count every x days, and it takes around x days to show symptoms you would always expect about 50% of infected to be asymptomatic at the time of testing
I feel that the asymptomatic thing is more wishful thinking in places where infection control has failed. Other countries have shown that you can contain the spread of Covid19, even if there are asymptomatic (or more realistic, low symptom severity) cases.
No country except Iceland or South Korea knows how many are infected, everyone else's numbers are horribly wrong.
But death numbers and hospitalization numbers don't lie. Sure, different countries are counting deaths differently, making it hard to compare them to each other, but the trajectories don't lie. And if you look at growth trajectories, no country is experiencing uncontrolled exponential growth at this point: https://ourworldindata.org/grapher/covid-daily-deaths-trajec...
If deaths are on a downward trajectory, it means that infections have been on a downward trajectory for weeks. And that's how we can know that it's controlled, without knowing how many have it or have had it, while being asymptomatic.
Except for when they do. Easter just passed and the the trajectories are plotted up to and including today, when Sweden for example is adding deaths to dates two weeks back every day, and the last 5-7 days _ALWAYS_ looks like a downward trajectory. The last little spike there from before easter has grown by 35% since after easter and is still growing daily.
You can't draw conclusions based on the trajectory of the last few days when an absolute majority of cases are added days, and up to weeks after.
Sure, but in that chart Italy for example has had a declining graph for over two weeks, which means you can be reasonably sure it's not growing exponentially there.
And in Sweden's case, if you also look at the number of ICU admissions, they've been flat for weeks, and those numbers have very little lag.
I'm not saying everything is fine, I'm not saying we're over the peak, but I am saying that it's not the case that any country is experiencing uncontrolled exponential growth and is going to turn into a zombie wasteland in a couple of days.
Sweden's ICU admissions number for a particular day usually takes a week or two to settle down.
For instance, here's how the numbers were updated each following day for the number of ICU admissions on the second of April: 42, 42, 43, 46, 47, 49, 48, 49, 49, 49, 49, 52. So it took until the 14. of April for the reporting of the second of April to settle down---and we still don't know if it's going to change again or not.
As far as I can tell, the official site doesn't record a history of what they reported, so the history is just what I manually copied to a file once a day when I happened to look.
Do I think the lag is crucial? No. But it's unexpected to me.
You have to ask what phenomenon causes an exponential increase in deaths/day and does not increase ICU utilization. The answer I’ve seen seems to be “yes, the disease is killing a steadily growing number of people but they’re older and aren’t going to the ICU before they die.” This is where Italy was at one point; they just got there much later.
As someone pointed out to me, the euromomo website is useful for this, it tracks the total mortality rate across Europe and compares it with the historical data.
By ignoring the hospitalized/homestuck difference one can have a clearer idea of what is happening. Sadly I don't know of a way to get the data for the whole world.
Another note on mortality tracking is that everyone is staring themselves blind on corona-related deaths, and comparing between countries, and exclaiming that the higher the death rate per capita is, the more of a failure the country's policies are.
But this isn't necessarily true. You have to look at the total mortality, and the excess mortality. If a country has high corona mortality, but no excess mortality, it means that most people dying from coronavirus are people who normally would have died from something else anyway. And whatever policies that country has have to be good enough.
If a country has high corona mortality and excess mortality, then it's fair to say that that country's policies aren't enough, and it's fair to have the discussion whether you could do more or should do more.
Euromomo data is really interesting to me because of these two points:
1) the spike in death rate caused by Covid-19 this year is of the same magnitude as the normal flu season spike in 2016
2) this year's flue season spike was low compared to recent years. Maybe due to a warmer summer?
One interpretation could be that a large number of vulnerable people escaped death from regular ILIs this European season, only to sadly succome to this pandemic.
When looking at a single region like Bergamo, the death toll is four times higher than normal... Absolutely nothing like a normal flu season spike. See graph in http://archive.is/AaJ76
If you look at the euromomo information for a country it is averaged across all regions, that includes those regions that started lockdown before severe outbreak, so the spike averages down to be small. I.e. you can’t look at the country info and make conclusions about the severity of the disease.
> Agree with your points although the link was blocked for me.
Euromomo [1] has per country breakdown. While some countries are relatively unaffected (yet?), bringing the average down, some, like Italy, Uk, Spain are way beyond the 2017 peak.
As pointed elsethread, possibly because of lockdown, at least in Italy, the worst has been confined to the northen regions (about one fourth of the population but more than half the confirmed cases). If allowed to spread equally everywhere, the numbers would presumably be higher.
That will be because you are using 1.1.1.1 for your DNS: archive.org has decided to give a bung IP to CloudFlare just because... (personally I think CloudFlare are doing the right thing here - protecting your privacy - unfortunately archive disagree. I think archive are wrong since DNS is often cached which is much the same).
> 1) the spike in death rate caused by Covid-19 this year is of the same magnitude as the normal flu season spike in 2016
the current number depends on lockdown measures. We didn't have lockdowns in 2016, and it is likely if we didn't have them now we'd be much worse. You can look at the graph for Sweden which decided to only apply mild measures for a comparison which shows this is much worse than the 16/17 flu.
The rest of the reasoning is still correct, and I have heard it pointed out before, though I believe you meant warmer _winter_ :)
Yes, which is wonderful. I am wondering what caused the large 2016 spike. Another interesting thing is the effect any behaviour changes are going to have on regular flu numbers. It's already looking to have a big effect in then southern hemisphere.
> But death numbers and hospitalization numbers don't lie.
They most certainly do lie. I know people who work in a particular police department, and they have been exercising a policy of not testing people they find dead. Situations like somebody found dead at home in bed, perhaps some blood that looks like it’s been coughed onto a pillow. Whoever’s in charge of policy wants the numbers lower, so they don’t do a test, and the death is recorded as something non-Covid related. Conversely you have NY who recently decided to declare all cases of death where Covid could have been a plausible cause as Covid-19 deaths. Not only are death statistics reliant on methodology and testing policies, but they are equally as open to manipulation by political actors as the infection statistics are.
This isn’t unique to this situation either. These kinds of statistics are manipulated all the time in lots of different situations. For example you could never smoke a cigarette in your life, but if you manage to die of lung cancer, there’s a reasonably good chance you’ll be recorded in smoking statistics. Then you have things that are even more nebulous, like trying to figure out how many people died as a result of the Chernobyl accident. Lots of different people will try to answer that one for you, and the gap between the lower estimates and the higher estimates is enormous.
you'll see a spike in the overall mortality for a region.
If you look at the mortality figures from the UK (published by the ONS) you can clearly see a peak, compared to the average range for that week over the last (10?) years.
That peak matches the shape of the numbers of victims of covid (the number is higher because nursing homes are horribly affected)
> death numbers and hospitalization numbers don't lie.
Death numbers are close but still have some uncertainty. New York for example is reporting much higher than usual numbers of people found dead at home. Not clear if they have been tested, if they are victims, or if maybe they had unrelated medical problems but couldn't/wouldn't go to a hospital under these circumstances.
Key thing in New York is that the protocol is about fever. You won’t be allowed in a doctors office unless confirmed negative, and you usually need a fever to get tested.
There are many scenarios where people in need of care won’t get it. It’s a vicious cycle and it’s fueling the ignorant rhetoric downplaying the broader issues.
More people are found dead at home because during a lockdown-at-home you're simply more likely to be at home at any given point in time overall, obviously.
The study, conducted from 1-6 April, tested 1,554 people. It did not involve antibody tests, which can tell whether a person was previously infected and is therefore probably immune. Future studies should involve antibody tests, the government has said, to inform policy as the country starts to reopen shops from 14 April.
> No country except Iceland or South Korea knows how many are infected, everyone else's numbers are horribly wrong.
Is South Korea still consideered an outlier WRT testing regimes? Not to throw shade on their great efforts in leading the way, but many other countries now have extensive testing.
Australia has highest per-capita testing in the world. New Zealand is doing well. A number of other developed nations have been testing people since the start, but Australia and NZ have some added benefits of distance and relatively small populations that are helping them counter the pandemic better than most.
In Australia we are testing people with symptoms (recently expanded in most places to hae no additional criteria). Some counties with a bigger outbreak/ lesser lockdowns are going to have more people with symptoms to test. 1.7% positive rate is one of the lowest in the world and combined with high testing suggests we are detecting most symptomatic cases.
NZ is mostly just testing people with symptoms too. That's pretty worrying to me given data like this article's. I think we should also be testing big random samples from the population. We've started testing hundreds of apparently-healthy volunteers, which is a good start: https://www.stuff.co.nz/national/health/coronavirus/12107495...
Also for anyone looking at NZ/Australia graphs, a large number of the cases are people returning from overseas that are detected (it is estimated there are 1 million NZers overseas, 5 million left). This has the effect of making the exponential growth look slow (unless the community transmission goes out of control, but both countries appear to be preventing uncontrolled CT).
> But death numbers and hospitalization numbers don't lie.
Well... there is some indication hospital staff are being directed to assume all cases are COVID19 until proven different. Patients that die with presumptive COVID19 are reported as COVID19 deaths.
So agree, numbers don’t lie. But... handling emergencies effectively can lead to problematic numbers.
So agree, numbers don’t lie. But... handling emergencies effectively can lead to problematic numbers.
My brother and I discussed this at length.
He claims (and I have no reason to doubt) that New York has 5x the usual death rate right now. About 2x the usual death rate is clearly COVID-19, another 1x is probably COVID-19 but not tested, another 1x is unclear and the rest are people who likely would have died anyways.
An example of that unclear bucket are people dying from heart attacks. COVID-19 stresses the heart which can cause that. However thanks to COVID-19, EMTs have moved to "Do not do CPR and if we cannot revive, do not take to the hospital." This procedure makes sense because CPR on a COVID-19 patient sprays the whole room with COVID-19. And taking someone with it to a hospital likely will cause them to get it, and it is particularly bad in people with heart problems.
However it also means that heart attacks have a higher likelihood of killing you than usually.
So..people die of heart attacks. Is that heart attack attributable to COVID-19? Is it fatal just because COVID-19 has overwhelmed the health system? We don't know and aren't trying to find out because knowing isn't the priority in a world where our health care system is stretched to the breaking point. All we really know is that people are dying.
This is so tiresome. Someone has cancer for six months, gets COVID and dies 17 days later and now Tucker Carlson is here telling me not to count that death. How often do you really think it happens that someone is hospitalized with COVID (otherwise, they'd not even be getting tested most places in the world) and dies of something else a week later? I'm sure it has happened a few times, but what has also been happening hundreds of times every day is people die untested and are not included in the official numbers. Its ridiculous to even have this discussion, and the motivations for it are absolutely disgusting.
Especially because the same people always compare the numbers with influenza, which are almost entirely based on statistics and comparison to previous years. For example in Germany in 2017 25000 people died of influenza (the bad flu year), but people which had a confirmed death due to influenza (i.e. Being tested positive and died of it) were something like 300 IIRC.
Don't get me wrong I think it's perfectly valid to use statistics for estimating the impact/IFR but you can't like many people with an agenda pick and choose your counting methods.
For influenza, the CDC includes deaths by pneumonia during flu season as part of the official death count because the certificates don't reliably list the true cause of death.
We see this happening now in the US with unofficial deaths getting lumped into the C19 deaths, some of which may very well have been flu.
Actually at least in Germany the numbers for influenza are entirely based on statistics. In particular the 25000 people died of influenza in 2017 number that is thrown around is based on looking at the usual statistics over the same period and everything above that is attributed to influenza. I think we will only have only have accurate statistics about the death rates etc in maybe a year
The OECD definition for a cause of death is the “disease or injury that initiated the train of morbid events leading directly to death...”
They also recognize a a contributory cause of death, defined as “a significant condition that unfavourably influences the course of the morbid process and thus contributes to the fatal outcome, but which is not related to the disease or condition directly causing death.”
The cause of death would be the cold, yes. That's how tallying these statistics work and yes, people can die from the cold.
If someone ends up catching pneumonia because their immune system was compromised as a result of immunotherapy, pneumonia was the direct cause of death and the cancer lead up to pneumonia.
The fact that we have to have this argument about basic death statistics is depressing. If you really wanted to play around with the numbers like what you're suggesting, you could easily make it so covid-19 causes zero deaths just by looking far back enough to find a contributing factor. Like age, immune system issues, other injuries, obesity etc.
> If you really wanted to play around with the numbers like what you're suggesting, you could easily make it so covid-19 causes zero deaths just by looking far back enough to find a contributing factor. Like age, immune system issues, other injuries, obesity etc.
So, if there was an epidemic of pneumonia going around, would you count that as a death due to pneumonia, and then use that statistic to help justify lock downs and enforced social distancing?
Because that is what is happening when you take an extremely sick person who finally died and slap a "death by covid-19" label on them.
There wouldn’t be an epidemic of pneumocystis pneumonia without an epidemic of immunodeficiency so I’m not sure that applies. But I see what you’re getting at. And, yes, e.g. if a COPD sufferer died of pneumonia of the pandemic strain I would call that a death attributable to the pandemic, noting that the COPD probably made them more susceptible.
When influenza deaths are estimated each year, the models assume that a lot of people will die due to the virus but the cause will be recorded as heart failure or pneumonia without etiology. From the perspective of the epidemiologist, they are influenza deaths, even if they were old and frail with bad hearts.
Yes, just like when someone suffers life-long health complications because of pneumonia, and then dies of something which otherwise may not have killed them, the cause of death is counted as the most recent event, not pneumonia. I think it suffices to say it goes both ways.
I'd like some evidence for this -- can you provide some?
When it comes to wearing surgical masks, yes, hospital staff are to assume that everyone's got it because it's pretty annoying to get it from a guy who came in for toenail fungus or a lady who came in for a prenatal screen and then be out of work for 2+ weeks. This is literally what has happened across Italy, China, New York, and other places. It's not like you write down in some electronic medical record "Man comes in with complaint of unattractive toenails. Presumed to be infected with COVID-19 without evidence." That's too damn much work.
On the other hand, when people die, some are being listed as presumed to have COVID-19 even in the absence of a positive test. Here's what the doctor sitting across from me says about how he's directed to fill out death certificates (yes, we're drinking Scotch, but this ought to still be accurate): On death certificates you are supposed to write a primary cause of death and then the interval between death and preceding underlying causes. For instance, if someone dies of ARDS preceded by dry cough, fever, difficulty breathing, you can say that they died of ARDS with presumed COVID-19 infection as an underlying cause. (You're apparently not really supposed to write "cardiac arrest" as a primary cause of death, because by definition, when you die your heart stops... so it's tautological in some sense and thus useless.) Another example: you could write "pneumonia" as primary cause of death, preceded by lung cancer preceded by asthma, and you could check a box for smoking but you couldn't write smoking down as a cause of death.
If you were hit by a bus and died of injuries, but you'd had COVID-19 symptoms beforehand, the certifying physician would need to write down "injuries from being hit by a bus", or rather in medicalese, "motor vehicle accident, pedestrian (ICD-10-CM subfamily V04)" [1]. COVID-19 in that case is not a cause of death, and that rando legislator from Minnesota who claims it is has a reading comprehension problem. My mom who works in the death certificate department will definitely be checking anything he signed.....
Why not only write down confirmed COVID-19 cases? Because, for instance, at the hospital at which the physician across from me works (in the COVID clinic, in fact), they serve about 100,000 patients but are allotted 25 rapid COVID tests a day. Since each patient needs two tests because of the high false-negative rate, that's 12 rapid-tested patients a day. Wowza. Yeah, let's use that on the guy who walked into the ER and got intubated within 20 minutes. Why bother?
Anyhow, interested to hear about your experiences.
South Korea hasn't done much antibody testing, and they are largely testing people with symptoms. They are doing a lot of it, but they still have a potentially large proportion of infected going under the radar.
I don't agree with that. If you look at how many negative results are returned, that is a good indicator of whether you're sufficiently testing. For example, the average here in Australia is that 1.7% of tests yield positive cases. That suggests that you're probably testing enough, especially considering if people are self-selecting to be tested when they think they have symptoms. In that case, you'd expect there to be minimal additional asymptomatic cases, or you'd be catching them in the negatives.
Compare that to some states in the US, where it's a full 30% positive rate, and it's obvious the testing there isn't sufficient.
> people are self-selecting to be tested when they think they have symptoms. In that case, you'd expect there to be minimal additional asymptomatic cases, or you'd be catching them in the negatives.
How does that follow? The asymptomatic people won't self-select to be tested.
I think that the reported numbers of deaths place some bounds on the kinds of hypotheses that are tenable, including those suggesting that there is already a protective level of herd immunity, or a vanishingly small death rate. For instance, one early hypothesis was that the virus was endemic in our population for a long time, but that doesn't explain why the death rate shot up suddenly over the past month. And 15000 people dying per week could not have escaped notice, even a month ago.
Many of those hypotheses coincided with claims that the lockdown was unnecessary or excessive.
> Many of those hypotheses coincided with claims that the lockdown was unnecessary or excessive.
This is it. The (short-term) financial incentives to opening up the economy are _massive_. Anyone trying to support that will jump all over some weakly supported hypothesis like this.
As are the social incentives for those of us who are lonely and bored.
A hypothetical young healthy man might be quite happy to accept 0.37% of people dying (the vast majority of whom are old and/or near death any way) if it means he doesn't have to put his life on hold for a year and can start dating again. Young males routinely take much higher risks for mating opportunities. I'm honestly surprised at the level of compliance so far, but I doubt it will last.
True, and that 0.37% number is probably the number with adequate hospital resources. If everyone caught this at once, there will be triaging of patients and the overall mortality rate would be higher.
Only 25% of the positive-cases on the Diamond princess turned out to be asymptomatic after 4 weeks.
The much-higher, 50% numbers that were being thrown around were obviously overestimated - precisely because it takes a week or two or three for some people to start showing symptoms.
As such, it's incredibly unlikely that the # of real cases is some large multiplier of the number of confirmed cases in any areas that are regularly testing people with flu-like symptoms.
> As such, it's incredibly unlikely that the # of real cases is some large multiplier of the number of confirmed cases in any areas that are regularly testing people with flu-like symptoms.
Please note that the reporting on Sweden from outside Sweden is completely bananas. The idea of how Sweden is handling the pandemic, alongside cherry-picked data, is being used to argue for whatever lockdown theory people seem to have.
The facts though are that Sweden is not an outlier in any way shape or form. Compared to other European countries, Sweden is boringly in the middle of the pack, and showing the same trajectories as every other country. Swedes are working from home, isolating themselves, going out less, traveling less, staying home from school, closing non-essential businesses, and washing their hands just like everyone else.
In some sense, you're right -- Swedes are doing lots of things differently these days, and the reporting I've seen is broadly terrible and used to support various contentions. I'm most interested in the numbers. Sweden has twice the population and ~20 times the fatalities of Finland, its next-door neighbor. I'll be watching carefully to see how things play out.
Belgium and Sweden have had a similar timeline yet Belgium has a much higher number of deaths/capita. Same could be said for a lot of countries that have had much more fatalities. Look at the higher fatality rates in Quebec too, even though the province set in place really strict lockdowns and has had it's first deaths much later than Sweden. My point here is that Sweden is well in the middle of the pack.
So what gives? Shouldn't Sweden be a complete outlier with a much higher number of fatal cases? It compares negatively to Norway, sure but it has much better results than a lot more similar countries too. How is that possible? We are absolutely starting to move the goalposts if we went from predicting spanish flu mortality rates without a lockdown to a slightly higher death count per capita compared to a few neighbors but a much better one compared to a lot more.
Also, I don't know why people assume Sweden simply has had the virus later than everyone else and that's why they haven't been hit as hard yet. There's no basis for that, it's not like travel routes are slow and it still takes weeks to spread a disease. There's no reason to assume that when Belgium or Germany got the virus, Sweden was just magically spared for a few more weeks. We should've been seeing an impossible to miss outlier numbers from Sweden by now and the complete opposite is happening .
Actually compared to many other countries Sweden did have community spread significantly later (10 days or so if I remember correctly). Also Sweden has large variations within the country, Stockholm was really a week or so ahead of everyone else
There are so many confounding factors that it is very hard to say. Sweden does look like an outlier compared to the other Scandinavian countries.
Testing criteria between countries are so different that it is very hard to make any comparison. About the only number I trust is all cause deaths and even that is laggy.
Universities and high schools have been closed for almost a month now, that's pretty much the same timeline as most other countries. Elementary schools are not closed, but they're very empty, most kids are staying home.
The reasoning behind this is that elementary schools function as babysitters, and this frees up adults in essential occupations so that they can go to work normally, instead of having to stay at home with their kids. There's also starting to appear evidence that kids might not be a serious disease vector, contrary to pretty much everyone's gut feeling.
And this is what I mean by the reporting being bananas. It's very easy to look at the fact that "schools are open" and assume it's business as usual in Sweden. It absolutely isn't.
It's also pretty funny that you linked an article from The Guardian, which breathlessly exclaims that Sweden has a death rate that's twice that of Denmark. Yeah, ok, but the death rate in the UK is twice that of Sweden. Pot meet kettle. If Sweden is doing twice as good as the UK, who the fuck are people in the UK to criticize Sweden's actions? It's as if a Swedish newspaper would criticize Denmark for having twice the death rate of Finland. It's absurd.
The reporting is bananas. It's agenda-driven, not fact-driven.
"Professor Russell Viner (UCL Great Ormond Street Institute of Child Health and President of the Royal College of Paediatrics and Child Health) said, "We know from previous studies that school closures are likely to have the greatest effect if the virus has low transmissibility and attack rates are higher in children. This is the opposite of COVID-19.""
Thanks a lot. The article had also a link to the paper, which I read. It's for sure interesting that with SARS the results were inconsistent, as opposed to flu pandemics.
Hmm, New York Blood Center says, "Please be aware that we do NOT test for COVID-19. You should contact your health care provider if you want to be tested." [0] Where else should I be looking?
Germany and Finland are doing this. Here are some results already completed in a German town showing that 14% of people tested positive for antibodies...
That study did their research in a town that was already infected, meaning that our understanding of the infection rate for Covid-19 is probably lower than reality.
Precisely - as an early outbreak centre that town is referred to as "Germany's Wuhan", and is expected to have among the highest proportion of infected inhabitants. So actually the 15% figure came as a disappointment and something of a surprise.
A disappointment? NYC has among the highest testing rates in the world and has only found about 1.5% of people infected. If there's another 14% in NYC that have been infected without needing medical attention, that is fantastic news.
The German town of Gangelt is the study case that the OP was referring to, which thanks to a small population and a well-attended carnival party with many infected attendees and a legion of subsequent linked cases had acquired the reputation that everyone must have been exposed, i.e. a place that would have established something like herd immunity. So to discover that only one in seven inhabitants had detectable antibodies was indeed dismaying: either the infection pattern or the immune response wasn't as expected. Or both.
Doesn't even have to be widespread, a randomized set of say 1,000 New Yorkers tested for antibodies across age and demographics could give us invaluable insights into the infection rate of this virus. It's infuriating seeing politicians pass the buck by pointing to a world of widespread testing, which we know will not happen anytime soon.
This is an artefact of the current antibody tests, which mostly only sample a response to a single antigen. Which viral proteins you mount a response against will vary from individual to individual. To really know if you have no antibody response you need to test for a response to multiple antigens.
Let's be realistic though. Given the way that this virus promiscuously spreads, if a relatively large portion of individuals weren't generally asymptomatic, by now we would have approximately zero healthcare workers.
I think you underestimate how effective proper sterile technique is. If all the equipment is available, and the staff appropiately trained, there should be a very small chance of becoming infected. In some countries this is not the case, but some places have demonstrated that they can keep their frontline workers from getting infected.
> 75% of people who were asymptomatic at the time of the test went on to develop symptoms. So the fact that these sailors are currently asymptomatic does not mean that they will remain so.
There's also a wide range of symptoms from 102F fever all the way to sp02 dropping below 80, with varying impacts on the health-care infrastructure.
At this point, conserving health infrastructure for normal incidence is as much of a problem (i.e even in the best case outcomes, there will be some cases of "stay at home, never catch the disease, but die from delayed response to a stroke").
If the asymptomatic people get immune, then this might drop the other multiplier of the R0.
It is in line with Iceland finding that 50% of people they tested were asymptomatic.
That's imprecisely stated. 50% of the people that tested positive were asymptomatic. Most of the people tested, both in Iceland and on the Theodore Roosevelt, have tested negative.
Esper's comments are ridiculous. It's been clear for months that there is some significant degree of asymptomatic spread, it's not new information.
Yes. Extensive testing was done in Korea and Taiwan in February and the same results came out. With extensive contact tracing, it became clear that asymptomatic cases played a big role in spreading the virus.
This data is not different or new, not even better.
Agree on the asymptomatic/presymptomatic thing. Also, I'd imagine the doubling time on an aircraft carrier is a lot shorter than in normal society. There are a lot of people packed into very small spaces.
Suppose the doubling time on an aircraft carrier is 5 days. That means half your infections are in the 5 day presymptomatic window.
Are there any data on the severity of the symptoms?
From what I've gathered, but without any hard data, in non-severe cases (i.e. not needing hospitalization) they can vary from a slight sore throat, dry cough and mild fever, to the same with a high fever and general sense of exhaustion.
Don’t you think that anyone who got the “slight sore throat, dry cough and mild fever” or milder symptom variation would be unlikely to get tested or talk about it?
The disconnect between the definitions of “mild” as in “passing without hospitalization” and “mild” as in “easy to bear for most people” is part of what grants weight to the message that the new virus is extremely bad even in the mild version.
It could be worth applying the falsifiability check here. What are the chances you could hear a message contradicting this observation?
I’m going to imagine a possible counter-message and its optics. “I was exposed and got sick, symptoms seemed to match up but they were really weak and not enough to get tested”—this would be unlikely to gain any positive attention. On facts it’d be very unspecific by the nature of it, on emotional level it might seem unfair to the suffering of other patients, from social/mass media point of view it’d just not be news- (or share-) worthy at all. Even if this case was much more common, the message has virtually no chances of ever being expressed and heard under current circumstances.
This line of thought, of course, should not lead to a conclusion that the prevailing variation of the virus is really mild. It only points out that the accounts we get the chance to hear may not be enough to judge the general severity of the symptoms.
> Don’t you think that anyone who got the “slight sore throat, dry cough and mild fever” or milder symptom variation would be unlikely to get tested or talk about it?
That's my opinion, as well, there's clearly under-reporting of these cases, and that's why specific serological tests are important.
Anecdata: a partner of an acquaintance of mine had fever (but rather mild) for a couple of days, then developed anosmia. The doctor told him to stay at home and that's it. He was never tested so the doubt lingers (happened well over a month ago, so one can't discount a flu, either).
Non-severe covers bronchitis, pneumonia, etc. My friend (who tested positive but was not hospitalized) described it as "chest pain, difficulty breathing, if I do something silly like walk 10 feet to the kitchen I get lightheaded and hold on to the wall" - for about ten days.
The question I had was whether there’s a connection between delay and severity: if you’re one of those asymptomatic cases for a week or two, how does that change the likelihood of ending up on the worse end of the spectrum?
What has gone wrong with this site? Why is this comment grayed out form downvotes? It's a straightforward testimony of real experience, and it doesn't even vary significantly form the consensus set of symptoms.
I see this all the time, on a site that used to be a really good spot for rational discussion.
I don't know about the US, but usually getting pneumonia here (in normal non epidemic-conditions) gets you at least a visit to the hospital if not straight up hospitalization.
[2] "we inferred that infectiousness started from 2.3 days (95% CI, 0.8–3.0 days) before symptom onset and peaked at 0.7 days (95% CI, −0.2–2.0 days) before symptom onset "
The point was more that the "typical incubation period" you are citing seems to be wrong, and not the presentation of the disease. Obviously yes, we'll know more with more data, but that's not an independent variable you're introducing.
It was the contention to which you were responding, in a conversation which was similarly challenging the WHO (and everyone else's) estimate on the severity. And I was pointing out that you can't do that, logically your argument was a tautology. The same effect you were arguing against would argue against your evidence.
You misunderstood my argument. I made no claim about severity. Merely than in about five days it will be clear which patients were presymptomatic versus asymptomatic.
Not to mention. There's a giant filter called basic training which going to skew the numbers. you have a bunch of kids running around in the best shape of there lives and hey what do you know they handle the virus better than average.
What about pregnant women? They're known to be more vulnerable to certain types of illnesses (especially viral infections), yet 29 out of 33 pregnant women who tested positive of COVID-19 in NY were still asymptomatic:
Women are less effected overall. It is thought it is due to ACE2 receptor distribution in the body being different than men, but they don't know. However there is statistically significant worse outcomes/disease severity for men.
Pregnant women basically puts the cap of the upper age at around 40. This disease the virus causes in the body is very much worse for those that are older.
The study tested pregnant women admitted to the hospital to give birth. There are a lot of doctor appointments and lab work to check things in their last trimester. So they could've contracted it through those high risk places or routine contact with health care workers who I would say are also high risk.
Still, the study showed on admission that they were positive so they probably didn't get it from the hospital, unless on admission actually means some time after. That assumes it might be able to be detected so soon into the infect as well. It is a bit strange in that regard that it is such a high number.
Pregnant women are going to be younger on average, and this affects older people the most. Also, same thing as the comment above says, just because they dont have symptoms now does not mean they will never have symptoms.
The NEJM letter [1] this article is summarizing is only talking about their condition while in the hospital (that is, of the 215 tested, the 33 who tested positive didn’t show symptoms before being discharged (median length of stay is 2 days).
That letter cites an article[2], which found that of the 43 pregnancy patients who tested positive, 14 (32.6%) were asymptomatic when admitted. However, 10 of them developed symptoms during their stay in the hospital or shortly after being discharged. It doesn’t say how long they tracked patients, but at most, 4 of the 33 could have been asymptomatic.
IMHO, the letter is confusing at best, but more likely intentionally misleading. FWIW, I probably would have come to the same conclusion had I not spent ~45 minutes digging through citations...
1) The main cause of infant death due to coronavirus seems to be complications from early labor and the baby being premature. Also related to hypertension in the mother. But it's only the leading cause due to lack of other causes, not necessarily because it's common.
2) Pregnant women also have a non-standard, somewhat suppressed immune system, since they're basically tolerating a (half-)foreign 9-month infection of sorts. It also explains, as you mention, being vulnerable to various types of infections.
But if one of the causes of death for covid is cytokine storm, which is basically an over-responsive immune system failing to regulate itself, then it makes sense that pregnant women, with an over-regulated immune system, might have less risk from that aspect of the disease.
More info on it if you look at theories on placental development and why women are more susceptible to autoimmune diseases. Pretty fascinating stuff.
This was testing people admitted to the hospital while going into labor. How easy would it be for a person to distinguish symptoms of being in labor from symptoms of having the illnesses?
My question is, of these asymptomatic people that do go on to have symptoms...how many are so severe that they would have likely missed work or gone to a doctor? I think that is important too. How do we know if a bunch of people have had it, but had such minor symptoms that they just went on about their day? I had a spout of shortness of breath around late Feb - early March, I just chalked it up as allergies. Maybe it was? I have no idea, but how many people that get COVID19 have similar situations where symptoms are so mild they just think it's nothing. That seems important when we look back in time where people weren't on edge and on the look out for any type of symptom. Of course asymptomatic people are going to show symptoms, but does that mean they would have reported it were they not told by a doctor to report anything out of ordinary?
We need widespread home antibody tests. I had a bad chest cold for a month recently, probably just a cold but I sure wish I knew for sure. If I found that I have antibodies I would try to volunteer to help in the fight and donate plasma. It would completely change my behavior, but I may never know unless I get sick as a dog with usual symptoms.
There's always the chance that the test itself is not particularly good and just has a high false positive rate. Although it is difficult for a PCR test to produce a match if there is no genetic material present, it may amplify trace signals, depending on the cutoffs chosen.
I looked into this a few weeks ago. The PCR test has an incredibly low false positive rate, below 1%. It is low enough that it is feasible to test a 100,000 people and expect basically zero false positives. The false negative rate is somewhere around 30%. So the real danger with PCR is that you will miss cases.
The opposite is true for the antibody tests. The false negative rate is around 10% and the false positive rate is also around 10%. So in 100,000 tests, you would expect to miss about 1,000 true positives. But, and this is critical, you would also mistakenly get 1,000 false positives - even if only 1/100,000 people are actually infected!
Next time you see someone claiming 50% asymptomatics. First thing to ask is whether they used PCR. Or if they used an assay with a terrible false positive rate.
If not done well PCR has an incredibly high false positive rate. If you contaminate your set up area (or equipment) with past PCR amplification material you will get a very high rate of PCR positivity.
Of course if you do things correctly this shouldn’t happen, but if the average pathology lab technician is as skilled as my ex-students and colleagues (and myself) then I would be not be so keen to rule out false positives.
Yes there is a major issue with false negatives, especially when the swab was not performed or stored correctly. RNA is not very stable and it is very easy to destroy all the viral RNA if you are not careful.
I am familiar with these drawbacks, having worked as a research assistant doing RT-PCR and qPCR. My understanding from a brief stint in industry is that there is a lot more quality control to be found in industrial and diagnostic labs than is typically found in a research lab. So I imagine there is still an appreciable amount of false positives even in a diagnostic lab, but they do have a lot more quality control in place to reduce it.
> The PCR test has an incredibly low false positive rate, below 1%.
Do you have a source, offhand? The problem with asserting any sort of false positive rate is that you need to benchmark against a source of truth. What source of truth are we talking about? A second PCR test? Clinical diagnosis?
If we benchmark against the clinical diagnosis, for example, then clearly this is a huge false positive rate -- most of the patients are clinically diagnosed as negative, which is all this article is saying. Benchmarking against a second test doesn't really tell us much if trace signals are being amplified, or if the laboratory is in any way compromised because of the urgency of the testing.
> The false negative rate is around 10% and the false positive rate is also around 10%. So in 100,000 tests, you would expect to miss about 1,000 true positives.
> you would also mistakenly get 1,000 false positives
I think you mean missing 10,000 true positives and getting 10,000 false positives.
This seems to me the most obvious implication. That when you only test symptomatic people, the test might be accurate, but in testing everyone the false positive rate is much higher.
A friend and I were having a tangentially related conversation about net-healthy processes that could theoretically be mandated during a pandemic and their effects on the populace at large.
Putting everyone on a daily fitness regimen would almost certainly save lives, even outside of our current pandemic. Likewise, if things got bad enough that grocery stores had to close and the national guard / army / gov were called in to deliver daily rations to households, I wonder what kind of effect that'd have on the country's obesity problem long-term, also.
Ignoring the completely dystopic dictatorship and near-apocalyptic context that'd be required for such a scenario, of course.
> Still, the case of the Theodore Roosevelt offers a case study for researchers about how the virus spreads asymptomatically in a confined environment among mostly younger adults.
...but they don't mention what the average age is. Presumably someone has the data to produce an interesting scatterplot of age versus symptom severity.
It's the first time I see news about the aircraft carrier. Could someone summarize why the captain got fired for testing his whole crew in an environment where a lot of people have to live very closely together? My first assumption is that it was a really good decision.
He sent an email to his commander and his commander's commander about how the situation was deteriorating... which were then leaked to the press and was promptly relieved of command by Acting Navy Secretary Thomas Modly who later on resigned.
Most people think it was a good call but it also may have compromised the safety of the carrier because now it's known they may be operating under less than perfect condition.
Yes and no. He was relieved because he went around the chain of command, which is a universal career-ending move in the military even if you do it for all the right reasons—which he did.
Also, although he was relieved of command, he wasn’t “fired” or “canned” or discharged from the Navy. He will undoubtedly go into an early retirement with a full pension at his current rank of Captain. That doesn’t change the fundamental unfairness of how he’s been treated, but he’s going to be fine. And I think he knew and accepted the consequences of his actions.
It's better to do the right thing than the correct thing and this man will be able to live with himself throughout his pension instead of having a heavy conscience weigh him down.
From all I could gather from Europe, I believe he acted as a human more than a robot and under the given circumstances it was the right call.
Ok, apparently his commanders didn't want the responsibility. They wanted a "phone call" they can ignore, not a written record that will later bite them in the ass.
And in order to actually act they had to leak it because silently acting on it involves getting a refusal from their commanders and also writing an email. It's monkeys all the way up.
TL;DR is the first guy got canned for "politicizing" (and, really, operating outside the chain of command by widely publicizing his fears and 'leaking' information about) the problem.
Basically, the military chain of command has ALWAYS really cared about how you handle these things. He violated it, and my military friends generally feel he did the "right" thing, but many also feel he knew what was coming and should take his punishment, because you just don't do it. While, at the same time, our government has shown an increasing desire to centralize authority and cover up for political reasons. So, I can see both sides, for sure. "You should never do that" meets "doing that is the right and moral thing in this environment". Fine.
The guy who called him out basically said a bunch of uncool and undisciplined shit about him, VERY publicly, and had to resign under pressure. He could have kept his job if he had toed the "outside of the chain of command" line and kept his cool. But he couldn't resist running his mouth in exactly the "uncool and outside of the military's expected behavior" manner. Again, the MO of the current administration.
This all sounds exactly how i imagine the Chinese regime is attempting to cover up how many Corona related deaths they actually have. Except nobody wants to be that person who leaks the story.
This is mixed news. While this indicates the death rate may be lower and the infection rate higher among the general population, the demographic of individuals in the US military are going to be of significantly higher health than the general population.
So, it doesn't necessarily ease the risk for demographics already identified as 'at-risk'. If anything, their risk might be understated given the higher infection rate.
this is a really good point. AFAIK, 100% of the canonical pre-existing conditions which are highly dangerous with COVID are disqualifiers for joining the military.
this cohort will give us a much better picture of how the virus impacts a totally healthy and young population. as with countless other pieces of evidence, it should also help to put the "it's just a flu bro" falsehood to bed.
> Disqualified from signing up, but you can age surely?
To an extent. The US military caps military service at 30 years (20 for reserve officers), last I checked. So if you enlisted at 35 (right at the cutoff for the usual maximum age to enlist), you'd be forced to retire at 65, whereas if you enlisted at 17, you'd be forced to retire at 47. 65 (IIRC) is right on the edge of when age starts becoming a significant risk factor; for the vast majority of military personnel, it ain't gonna be a factor.
There are of course exceptions to this based on rank or specialization; for example, had my grandpa been promoted to General, he would've been able to serve longer, but he wasn't selected for the promotion so he aged out as a Colonel (or at least that's how he explained it to me).
Majority on the ship are going to be under 40. Most people start their military careers between 18 and 22, and most people leave at it before 20 years of service.
Squadron commanders, senior medical officer, Dept heads and the CO and Admiral would most likely be in their forties or early fifties.
Yes. Current understanding of the mortality rate is that it’s roughly 10x more lethal than the flu across all age demographics. This means you might only have a 0.2% of dying as a 20 year old, but you only had a 0.02% chance of dying of the flu.
The caveat is that mortality rate is intimately tied with the availability of certain types of care; if you need a vent and the hospital is full, you die even if otherwise you would’ve lived. Thus case mortality rate will change dramatically once the hospitals fill up.
I don't think that's true. covid has stronger age dependence. Just look at the ratio of covid vs. influenza deaths on the CDC's website (https://www.cdc.gov/nchs/nvss/vsrr/COVID19/index.htm). 3:1 covid:flu for over 85, but 1:1 for 25-35 and 1:10 for children. (relative ratios as we don't know total covid infections).
This is especially striking with children: if the US had the same number of covid infections as seasonal flu, you'd probably have lower pediatric deaths from covid than flu.
These statistics don’t support that conclusion, because these statistics are for total deaths. You can’t meaningfully compare the total deaths from a disease that’s done for the season (Flu) with one that’s still on going (COVID-19).
What you should be comparing is case fatality rates.
But can you not compare the ratios between age groups? That's all I'm doing here - showing deaths have a higher age correlation with covid than flu. - not making any statement about absolute CFR/IFR.
You see significantly higher multipliers by age group than for flu. As one example, they are guessing teenagers have 1/17th the mortality rate of say a 40 year old. For flu (going by deaths), it's about 1/5th.
It's more likely that cases/infections is skewed by age, because we test severe cases more than mild cases, than infections as a whole is skewed by age. Assuming infections are uniformly distributed, or rather have a similar distribution to the flu, seems entirely reasonable until we have good data suggesting otherwise.
There is no reason to believe that infections aren’t skewed by age. We took a wide range of preventative measures that are completely unique within living memory, such as closing down most schools and colleges. Until we’ve actually done statistical analysis on who got sick, any predictions based on historical trends are largely invalid.
Almost certainly. The US had 27k deaths in the past two weeks. That's more than some entire years of flu related deaths. Give it another few weeks and it will be more than any recent year.
Good point, yes, but I bet that Gulf war soldiers where also extra-healthy when they enlisted. Not so much when they returned home.
Army, is an activity with lots of health risks, chemicals and strange diseases exposure attached. Not the best choice if you expect to live for one hundred years.
That reminded me of an Army recruiter well known for his “tactics”. People close describes him as a “Car salesman “. Apparently, is very good at making sure the candidate doesn’t change his/her mind.
I think we should also consider that some members of the military depending on their duties get exposed to chemicals that the civilian pop don’t get exposed to at the same levels.
There are a lot of people who have pre existing conditions and have no idea, even in the military. There was a marine recruit who died during basic training because of a heart defect, it wasn't an issue his whole life and it didn't come up as a problem during the in depth physical you get before hand.
Sure but that is irrelevant. It is absolutely certain that the rate of most diseases associated with increased Covid19 risks is much lower in the active army than in the general population, even if it is not 0.
The former only holds if you assume that a large majority of asymptomatic carriers never develop symptoms. It’s entirely likely that an asymptomatic positive test is a precursor to developing symptoms.
It would tend to add weight to the growing evidence that public health officials in most countries have been pursuing the wrong strategy all along. We could save more lives in the short term and avoid overwhelming the healthcare system by focusing our limited resources on providing safe voluntary quarantine spaces for the elderly and others at highest risk.
With other viruses, pregnant women are typically considered at elevated risk. For example, they had a significantly higher fatality rate with the Spanish Flu. So it's still unclear who is most likely to be asymptomatic based on the data we have so far.
Immune systems during pregnancy are vastly different than normal. It's quite possible that is a factor in the asymptomatic rate here. Many studies like this are using populations with inherent selection bias: that makes them interesting, for that population, but you cannot generalize from those results.
I don't quite understand why "more infectious but less lethal" is better than "less infectious but more lethal" -- both mean that lots of people are going to die.
Even with the earlier estimates of how infectious it is, it seems quite likely that a large proportion of the population is likely to catch it sooner or later. If that is so, then the less lethal it is, the better.
Let’s assume 100% in NY are or have been infected. 12,000 deaths / 20 million = 0.0006% fatality.
Then scale that up to US population outside N.Y.: 18,0000 deaths / 0,0006 = 3,000,000 infected out of 300,000,000 for an infection rate of... 1%.
Herd immunity takes about 66% to 70%. So: only 65% to 69% to go, or about 200,000 deaths.
Lower the assumed infection rate in NY to anything realistic and it only gets worse. For (still high) 20% you’re looking at a million deaths to achieve herd immunity.
Being asymptomatic is not the same as being immune. It means that more people will feel fine and spread the virus more because they don't know they have it.
Well, for what it's worth, if they get the virus while on a long tour of duty, by the time they get back they should be good to contribute to the herd immunity.
Only if they form antibodies. Studies have been suggesting that people who get it in asymptomatic form are not all forming antibodies - leaving them wide open to be future communicators of the disease.
There are no studies that have suggested anything like this. There simply has not been sufficient time to perform a study of the type needed to prove such a claim: you would need to gather a cohort of people that you know had the virus, wait for them to recover, then test for antibodies.
Moreover, even if the percentage of such people were shockingly high (i.e. over a fraction of a percentage), you would need to conduct a huge survey to distinguish it from error rates on the tests themselves.
To everyone suddenly thinking about antibodies vs T-cells vs whatever else, the podcast "This Week In Virology" discusses some of the difficulties at https://www.microbe.tv/twiv/twiv-602/ (discussion with Stanley Perlman). A number of other episodes also hit on coronavirus. Listen while you're walking the dog.
Another fun seminar is this one by Prof Pamela Bjorkman at Caltech; it's useful to watch the slides with at least one eyeball so not for dog-walking. https://www.youtube.com/watch?v=OBcc_dk9Q9U
Forming antibodies (antibody driven adaptive immunity) seems like the most likely way patients are recovering. This would be typical of recovery from Coronavirus infection.
A known failure mode of vaccines is if the person who is being vaccinated lacks the right B cells for creating antibodies matching the antigens on the surface of a pathogen. If the B cells a person has lack the right B Cell receptors, they can't generate the correct antibody response to an antigen, because they can't bind with/identify an antigen in the first place. Additionally, they may lack a sufficient number of antigen naive T cells, which haven't yet become differentiated as T memory cells and effector T cells.
But that doesn't mean that it is impossible to create a vaccine: this problem exists already for successful vaccines. For example, the Hepatitis B vaccine has a relatively high failure rate, but is still provides immunity 90+% of the time. It just means that some smallish percentage of the people you vaccinate aren't actually contributing to population immunity.
It’s possible and desirable for a vaccine to stimulate antibody production where a “natural” infection would not, which is one of the things that will be tested during their development. An extreme example is infection with the tetanus-causing bacterium clostridium tetani, which doesn’t provide natural immunity at all.
It's not clear to me that asymtomatic doesn't mean immune. If the primary symptoms are due to over-replication of the virus and not fighting it enough resulting in cell death in lungs and other airways, then asymptomatic infection indicates the immune system is fighting it enough to fend it off.
Now, this rests on symptoms being directly caused by higher virus cell counts rather than toxic byproduct cascades of some sort. I'm not sure that's true
This is devolving into semantics. Being a asymptomatic means you are infected, which means you are not immune. You can still develop symptoms later and/or still transmit the disease.
You would be considered immune if your body produced antibodies that prevented infection. This immunity can be gained by successfully fighting the infection or by receiving a vaccination that triggers an immune response.
Now hopefully we can get a better estimate of the range of the latent period. That these cases are asymptomatic does not mean they won't show symptoms at some later date. It also does not mean they are invulnerable to reinfection, and if this virus indeed has Antibody Dependent Enhancement like SARS, this could create an extremely dangerous setup for a second wave with a significantly higher, order of magnitude, death rate.
All of the bits and pieces are floating around in papers, hopefully they won't be confirmed like everything else that started as errant literature.
Is it possible that more people are asymptomatic because the sample population is more athletic? I would imagine there's a certain physique that's maintained and required for the military.
Were they testing for the virus or for antibodies? If it was testing for the virus tests only show positive for a few days then testing everyone on board will miss those who already had it, correct?
According to the Captain's email, sailors were tested, and results known the next day. I don't know what equipment they had onboard the Roosevelt, but the quick turnaround might indicate the type of test. These tests were also performed around Mar29.
Sounds like RT-PCR tests. Serological tests probably aren’t available in that scale yet (unsure).
Regardless, it’s going to be extremely interesting now that countries start doing random serological tests.
I read today about a group of Swedish athletes who visited a competition in Wuhan in October and some developed severe respiratory issues afterwards that couldn’t be diagnosed.
Edit: 5 were tested and 1 was positive which was interpreted as being a later infection. So no October infection.
This was what was coming out when it was blowing through China, this was what the big concern back February. This isn't news. A good deal of people will never notice they have it which is why the spread of this thing is so difficult to contain.
I guess maybe people doubted it really was that hard to stop or were not paying attention before, but its why its is absolutely critical everyone isolate even without symptoms.
"Human coronavirus NL63 (HCoV-NL63) is a species of coronavirus that was identified in late 2004 in a seven-month-old child with bronchiolitis in the Netherlands.[1] The virus is an enveloped, positive-sense, single-stranded RNA virus which enters its host cell by the ACE2 receptor."
To add, I also wonder whether those with contacts to disease super spreaders (aka toddlers in kindergarten) have better immunity against covid-19, just by being previously infected by other coronaviruses. Possibly some currently unknown ones as well.
Let me cite full abstract of the research on CT scans of symptom-free COVID-19 patients [1]
Purpose
To evaluate the chest CT findings in an environmentally homogeneous cohort from the cruise ship “Diamond Princess” with Coronavirus Disease 2019 (COVID-19).
Materials and Methods
This retrospective study comprised 104 cases (mean age, 62 years ± 16, range 25-93) with COVID-19 confirmed with RT-PCR. CT images were reviewed and the CT severity score was calculated for each lobes and the entire lung. CT findings were compared between asymptomatic and symptomatic cases.
Results
Of 104 cases, 76 (73%) were asymptomatic, 41 (54%) of which had lung opacities on CT. Other 28 (27%) cases were symptomatic, 22 (79%) of which had abnormal CT findings. Symptomatic cases showed lung opacities and airway abnormalities on CT more frequently than asymptomatic cases [lung opacity; 22 (79%) vs 41 (54%), airway abnormalities; 14 (50%) vs 15 (20%)]. Asymptomatic cases showed more GGO over consolidation (83%), while symptomatic cases more frequently showed consolidation over GGO (41%). The CT severity score was higher in symptomatic cases than asymptomatic cases, particularly in the lower lobes [symptomatic vs asymptomatic cases; right lower lobe: 2 ± 1 (0-4) vs 1 ± 1 (0-4); left lower lobe: 2 ± 1 (0-4) vs 1 ± 1 (0-3); total score: 7 ± 5 (1-17) vs 4 ± 2 (1-11)].
Conclusion
This study documented a high incidence of subclinical CT changes in cases with COVID-19. Compared to symptomatic cases, asymptomatic cases showed more GGO over consolidation and milder extension of disease on CT.
Thanks for the link! My question was more into the direction whether permanent damage can occur in mild/asymptomatic cases and it looks like it is not the case. Anyways, if I am wrong and anyone has better information on this, please share it.
All the data points to the fact that coronavirus is more widespread and less deadly than most outlets are reporting (after all, increase the denominator, the % goes down).
The countries with the lowest death rates are also the countries that did the most comprehensive testing. Ditto for this aircraft carrier.
Of course governments and outlets are fearmongering lest they be accused of not doing enough, but this thing is way overblown and I fear we'll be living with the consequences for an entire generation.
Are you of the opinion that this is simply just a slightly worse flu?
> All the data points to the fact that coronavirus is more widespread and less deadly than most outlets are reporting
You couldn't be more wrong. There are nurses and doctors working on the front lines dealing with patients, and they're completely and utterly overloaded. Lack of resources. Lack of help from local and federal governments. They're the ones telling us this is way more deadly than it seems.
> Are you of the opinion that this is simply just a slightly worse flu?
I mean I'm about 95% sure I already had it. Had literally every single symptom but the local health authority (Alberta, Canada) wouldn't test me. My SO had it worse but again, they wouldn't test her.
Felt like a worse flu + more coughing and shortness of breath. Worse fever. My symptoms were bad for about 3 days, then felt like a cold for about a week, then a cough stuck around another week or two after. My SO had bad symptoms for about a week, was moderately sick for another week and a bit, but her symptoms disappeared pretty quickly afterwards. In either case, because we didn't require hospitalisation, AHS wouldn't test us.
Anyhow, there's a massive body of evidence that there's many times more people infected than confirmed cases. Are you disputing that? Do you actually think there is no one infected other than confirmed cases?
Our health authority, until a few days ago, wouldn't test anyone that wasn't a severe case or an at-risk group... You could literally have every single symptom and they'd simply tell you to stay home. Now they've only expanded testing because there's way less hospitalisations than their models predicted...
Edit
> There are nurses and doctors working on the front lines dealing with patients, and they're completely and utterly overloaded. Lack of resources. Lack of help from local and federal governments.
Maybe that's a failing of your health care system? In Canada hospitalisation rates are way less than predicted. Our province also gave away a bunch of PPE because it doesn't appear as though they'll get used.
Nah they were predictions assuming the measures we put into place a month ago. But as far as I could tell their assumptions also used data from Italy, whose population is significantly older and whose health care system is less functional.
How would more asymptomatic cases make this an overblown situation? Sure, there's evidence that there are lots of unreported cases but there's also quite incontrovertible evidence of death spikes in places that didn't implement swift restrictions.
I get being frustrated at lockdown but your reasoning sounds motivated to me.
More asymptomatic and mild cases would lower the death rate to something more akin to the flu. It would also mean that we'll achieve herd immunity quicker than previously assumed.
Lots of the fear was based on assumptions that this would be as deadly as SARS or MERS but at this rate we're looking at overall deaths that is slightly higher than the flu but lower than things like cancer or heart disease.
This is the terrible take that will be everywhere in the next few weeks; “I think I had it, therefore I am an expert on the spread of this disease”. There is no data or coherent argumentation here. I’m sorry you were sick, but this isn’t an argument based on facts, it’s an anecdote based off of little that might put people in danger.
We need to inoculate ourselves from this argument because we are about to see it everywhere. Confirmation bias par excellence
Come on, all the data is out there. There's been 2 million confirmed cases. Pretty much every expert agrees theres far more undiagnosed cases. We know the testing rates. We know who's being tested. The information is out there.
Our local health authority is literally giving away PPE...
Seems your only argument is that the idea it's not as dangerous as initially assumed "might put people in danger".
Except the fallout definitely will. Shutting down the economy, limiting health care access has real consequences.
I’m not asserting anything other than that this argument is not based on data.
The data aren’t there, you aren’t an expert, and this argument doesn’t help anyone. That’s the most positive read I can give what I consider to be a reckless take, and this take will be EVERYWHERE in the next few weeks. We need to guard ourselves because this take is deceptive; it lets us feel superior to everyone who is freaking out, which will help individuals calm down at the expense of public health.
Probably something more like Sweden but then again, our demographics are pretty good. Either way, I'd expect all the potential deaths in a shorter timeframe.
What I really would have preferred is a response more akin to Taiwan's. A lockdown was required because of how lax we were in allowing travellers to return from China and Europe with virtually no screening. Had we simply taken it seriously in January (our government was shockingly nonchalant back then) we could have avoided a lot.
I too am a 'pretty sure I had it already' person. I have also spoken to others that, like me, think they might have had it already.
In the weeks before the story went crazy I bought a dehumidifier in the belief that this might help me eradicate a dry cough that would not go away. Not for one moment did I think I had coronavirus at the time, however, as time went on, I began to wonder. Placebo or not, the dehumidifier was an extraordinary measure and my symptoms had been remarkably similar to those of the dreaded disease.
Because none of us were tested and because we didn't go to hospital we can be readily dismissed by those that only believe the TV news.
The founding myth is also a bit odd. We have a flying mammal - a bat - passing the disease on to an ant-eating mammal nobody ever sees in zoos - the Malayan pangolin - for this creature to be smuggled into China to then make it to a seafood market to then infect Wuhan. The sources for this are lacking and it is lazy reporting dressed up as science. I am surprised Father Christmas isn't in there somewhere.
The Spanish Flu of a century ago was only called that because neutral Spain wanted to know what was going on with the flu whereas the warmongering nations were blind to the epidemic that was wiping out their troops. There is a theory that the Chinese folk brought in to dig the trenches of WW1 were the source of the so-called Spanish Flu.
I am open to the idea that the Chinese happened to do the research and pick up on covid-19 first, hence the idea that it came from Wuhan. But did it really? There are 7 billion or so humans with many billions of intensively farmed animals yet it was some endangered species that doomed us all? I am increasingly believing the anecdata is stronger than this 'pangolin story'. I am definitely open to the idea this virus was doing the rounds outside China although there is no proof. However, I see this as like the Spanish Flu, now believed to have not started in Spain.
There is a Chinese saying about people too afraid to eat food in case they choke on it. Right now we are on track for everyone to stay indoors for eternity lest a Baby Boomer get it.
Same, I had it starting January 4th in the SF (North) Bay Area, I'm about 90% sure.
I was probably basically a super spreader too, tbh. I went to work every day, 'cause I tend to power through whatever is thrown at me. At least I avoided shaking hands.
People were even talking about it back then... they didn't know it was Corona, but friends I know who are nurses were saying there is a "weird, bad respiratory infection" going around, and a lot of "atypical pneumonia" and a "really bad flu season but it's a weird flu".
We already had it weeks and weeks before the shelter-in-place in the Bay Area, I'm very sure.
There is strong evidence COVID-19 was not circulating in the Bay Area in January. Samples collected by the Seattle Flu Study in Jan/Feb 2020 have been retested and COVID-19 was not found before Feb 21. As Trevor Bedford says, had COVID-19 been circulating in CA it almost certainly would have showed up quickly in WA. There is other evidence based on the genetics of sequenced viruses. Details:
https://twitter.com/trvrb/status/1249414291297464321
There are more hospitals and health workers doing nothing now globally (and no, I am not ignoring the outliers here, like Lombardy, Madrid, London, New York, I’m talking about the rest of the world), waiting for a wave that never came, even though everyone was 2 weeks behind Italy in the last 2 months. Cancer patients, people with other serious issues are being ignored now, if one of your parents had a condition that is not being treated any more, you might see things differently.
People seem addicted to comparing numbers at a point in time and drawing conclusions, not considering whether they are changing at different rates, not to mention the derivative of the rate of change.
Why would the ratio of, say, cases in NY vs Oklahoma vs. Japan stay constant? Just because? Clean living?
I don't have expertise or authoritative predictions, I'm just saying that graphs are all over the place and practically everywhere has historical data with a different shape, and the end state/equilibrium is not know, except apparently, tentatively, for China and South Korea.
We locked most of the nation down for almost a month and still overloaded medical infrastructure and had to build field hospitals. We're burying people in parks and storing bodies in mobile freezers. Most elective surgeries are still on hold because the hospitals are filled with Covid patients. A few nations had to ration health care and didn't treat people over 60. What other disease has done this since the Spanish flu?
Follow the Iceland data. They've tested about 10% of their population, including random testing of seemingly healthy people. They've almost eliminated new cases. Death follows about three weeks after symptoms, so we'll know the infection fatality rate soon. Right now it's quite low there, but I predict it will trend towards 1% - 1.5% like we saw in Germany and South Korea, whose rates also started out low. That's >10x the death rate of the flu and would indicate half a million to a million dead in the US.
Sad to see that everything that tries to bring some positivity to this crisis or a different point of view gets downvoted into oblivion here, including studies and opinions on how we’re doing more harm with certain measures.
I get it. Everyone wants to find some meaning and importance to justify what's going on.
Tons of jobs and wealth are being destroyed, governments are issuing tons of debt and expanding the money supply, people need to believe they're saving millions of lives.
* Sailors are not in any way representative of the general population.
* Sailors in the US Navy are notoriously overworked and there is a strong culture of working when sick. So we're they actually asymptomatic or did they report for work shivering and sweating and semi delerious?
It is quite possible the virus is not nearly as dangerous and lethal as people fear. If the young have nothing to worry about the prospects are pretty good.
The best way to reach herd immunity is to have lots of immune people around you.
Not a single death of anyone between 10-19 and only one death under 10. 7 in their 20s.
Those are statistically minuscule numbers considering Italy has over 22k deaths and over 168k confirmed positives.
This paragraph is also quite interesting:
"As of April 13th, 217 out of the 18,641 (1.2%) positive SARS-CoV-2 patients under the age of 50 died. In
particular, 47 of these were less than 40 years (32 men and 15 women), age range between 5 and 39
years. For 6 patients under the age of 40 years no clinical information is available; the remaining 33 had
serious pre-existing pathologies (cardiovascular, renal, psychiatric pathologies, diabetes, obesity) and 8
had no major pathologies."
The US military is not a representative sample of people; it's a bunch of people with better health and fitness than the general population. And the military is an institution that will reject people from joining based on a lot of the health conditions that make COVID-19 more dangerous to them.
It's useful data, to be sure, but it also highlights that the disease can be really dangerous for people outside certain groups.
> The best way to reach herd immunity is to have lots of immune people around you.
It's not at all clear yet that recovering from COVID-19 confers any lasting immunity.
FWIW I am hoping that there are maximal number of invisibly sick people that never notice it, that is the best outcome you could have (other than nobody being sick of course)
if you knew someone is unaffected getting exposed is not such a bad outcome.
> the virus is not nearly as dangerous and lethal as people fear
Whereas being still deadlier than the combination of all wolves, dogs, crocodiles, hippos, lions, tigers, elephants, sharks, spiders and all known venomous snakes in the planet...
Any serial killer wannabee would kill for having the same results in just three months
Sometimes, David kill Goliath. This does not mean that Goliath was not dangerous. One of the problems with this situation is that human stupidiy hurts us all, and we of course aren't short of that.
Most people that go to corona's infection parties would surely remain quiet at house if there was a Lion sitting at their door.
Since about a week ago data has been coming in from antibody testing in Europe... and the results are that IFR (infection fatality rate) is clearly less than 0.5% (0.37% in one city in germany[1]) and the number of actually infected people at least 15 times to 30 times higher than the confirmed number of cases.
Today there's been a new result from antibody tests in the netherlands done on blood dononrs which showed about 3% infection rate. Extrapolated to the population that would imply 500k infections, 20x higher than the official stats.
The Heinsberg study isn't the only source pointing to this. Almost a month ago the NYT also ran a story on randomly tested Iranian airplane passengers which suggested that as of that time there may already have been 500k-5mil infections in the country.
Netherlands is currently at 30000 cases with 3000 dead, cfr of 10%. 20x infection would put the IFR at 0.5% which is well in line with what is expected
Possibly dumb question, how do we know someone with antibodies was exposed? The whole idea of vaccination is based on multiple things producing the same antibodies, so isn't it plausible there could be related viruses or genetic factors or something that would lead to antibodies for some people that hadn't been exposed?
Yes, there is the chance of false positives with antibody tests, in particular for other strains of Corona, but scientists can do a sample of antibody tests on people they know to have been infected with covid-19 and get a rate for false positives and take that into account.
I'm not so sure that's clear yet. Just going on blunt metrics, the virus has already killed 0.1% of NYC's entire population, probably on pace to hit 0.2% if the down-curve even only roughly matches the up-curve. So it would have had to have spread to 50% of the population for the fatality rate there to be only 0.4%, which seems unlikely (there's only a smattering of antibody data around the world so far but nothing has found spread even close to 50%, especially at the level of a metropolis)
If people on here are so keen on calculating CFR and not R0 to estimate how bad the virus is, they should also take into account logistic and demographic problems of every area. Hence, the CFR of New York might be so bad because of terrible medical infrastructure in the first place, and additionally patients who are not willing to go to the hospital because of fear of bankrupting themselves. Certainly not saying this virus is "just like the flu" because it is not and it is killing a lot of people. But epidemiologically this is much more complex than all of us are able to understand as non-epidemiologists.
Even w/o those non-positives, the death count for NYC is in the neighborhood of 8,000[0] (and still rising at a decent clip) for a population of 8 million. That's 0.1%.
You can also look at individual counties[1] and you get some variation but the same picture. Ex. 2.7k deaths in Queens for a population of 2.3mil, 0.4k deaths in Richmond for a population of 0.4mil
(That's 0.1% for the entire population and not even nearing the maximum yet, so obviously the IFR's and CFR's will be even higher.)
also while this may sound insensitive 0.1% of the population is not the same as X percent of old and sick people
it is not like the virus takes down everyone equally. The overwhelming majority of those affected are both old and fairly sick already.
Again I am not implying anything other than there is clear skew and the measures should target those that are at risk. It makes no sense to create generic, unworkable rules where we lock up all 20 year olds that have no risk whatsoever. It is not realistic.
There’s also the problem that healthy young adults are generally very stupid when it comes to assessing risk. Sure, they’re probably only at mild risk of days of debilitating hospitalization, but they’re also going to be fairly careless about people at greater risk around them.
Locking everyone up gives us a chance to gather data, prepare treatments, and find a way to protect those at risk. Letting spreaders run around carelessly will not make anything but the economy better.
This is massively informative. If anything pregnant women take a lot more precautions than other people. They are most likely under representing the overall infection rate.
As another data point in the Netherlands (officially 30k cases - only serious cases and hospital workers were tested, 30% of the tests are positives), actual seroprevalence is 3% ~500k people have been infected (~2 weeks ago), dividing the excess deaths, you get 1.3% mortality rate.
We can't tell anything from the article.
* We don't know how many people were tested.
* We don't know how many people tested positive.
* We don't know the false positive rate for the test.
~50% of enlisted sailors are 25 or younger, with each successive age bracket getting smaller. For officers it is more like ~13% and it's evenly distributed by age bracket.
Asthma, no. Diabetes, no. There is not a single person on that ship with either, they’re both disqualifying from shipboard service.
There are probably some people who are overweight to a varying degree, but again people who get overweight and don’t get back within standards get removed from the Navy.
>> The majority of the positive cases so far are among sailors who are asymptomatic, officials say.
I don't know much about this kind of thing, but isn't the most important word in that sentence "sailors"? I would think people living on an aircraft carrier are, on average, way different in many major ways than the average American. So it seems like making any kinds of assumptions based on this wouldn't be super reliable.
If it's true that men are more susceptible to infection/complications/death, the only way the population could be better would be if the ship were staffed entirely by women. That would be an interesting scenario for military leadership to plan.
Sailor - noun: a person whose job it is to work as a member of the crew of a commercial or naval ship or boat, especially one who is below the rank of officer.
Language evolves. Computers used to be people, my cellular telephone rarely conveys my voice, my laptop seldom touches my lap, I virtually never write anything at my desk.
There are multiple, dynamic risk-factors being discovered, treatment options, and different genomes of this species of virus circulating.
1) Being overweight is a major risk-factor for requiring critical care, and most US military folks aren't weight-enabled.
2) Being older is another risk factor. Also, most US military folks aren't well-aged either, typically in their 20's-30's.
3) Having type A blood group is a potential risk factor. Type O blood group is a potential protection factor.
4) Being male was a risk-factor for the L-strain. It's possible the military folks caught an S-strain that has less gender specificity, but it also may have nothing to do with it.
5) SARS-CoV-2 as a species maybe drifting genetically towards more communicability but less virulence. H1N1, HIV and others have also shown this pattern.
6) COVID-19 may not be best helped with non/invasive high-pressure ventilation that causes extreme barotrauma. In fact, it may not even be the same as previous instances of ARDS.
7) It's possible they were exposed to a variant of one of the newer genomes of S-strain that goes up to 78% "asymptomatic" community spread.
8) "Asymptomatic" means subclinical in terms of manifested, obvious symptoms. There is still the real possibility of internal organ damage regardless. Only a vaccine will be able to end this threat.
> 5) SARS-CoV-2 as a species maybe drifting genetically towards more communicability but less virulence. H1N1, HIV and others have also shown this pattern.
Given that Wuhan did not even report its first case publicly until the 31st, this seems highly unlikely. Even if you believe China was 15-30 days behind in reporting (pushing it) and that somehow a near patient zero traveler from there ended up in the bay, having it spread to "all over the bay" levels by late December would be incredibly contagious. No timeline supports your claim here.
So... you argue that 20% of the population had this disease, except that they didn't have this disease they had a close relative that is almost entirely asymptomatic in exactly the way you need it to be in order to explain away the case fatality rate measured for the disease we do know about?
I genuinely don't understand the desire on the part of so many people to... just not believe the relatively obvious (but still not remotely certain) fact that this is a very serious disease with an unmitigated doubling rate somewhere around 5 days and with somewhere in the realm of a 1% CFR. Really, the data matches that very well.
Certainly there is room for lots of uncertainty, but if your policy desires demand the invention of a second strain and whatnot... maybe it's time to revisit your priors?
There's probably hundreds or even thousands of mutations of this coronavirus. It's kinda what it does. But they're basically meaningless, although it is useful for tracking how it spreads - kinda like a family tree.
There is pretty much no evidence of what common people would call "multiple strains" - as in, immunity doesn't transfer, different infection characteristics, etc.
The paper you posted was debunked pretty much instantly by people that know what they're talking about. There's a lot of junk papers out there written by people on coronavirus that aren't even in the field.
Just read it and they were not disputing the existence of two strains but rather that the virus didnt jump from animals twice. The article disputes the claim that because L strain is 70% of the cases, that it must be more virulent.
the distinction is important here because this subthread started from the suggestion that there are multiple strains circulating, with different virulence. The fact there are multiple lineages is a natural consequence of how viruses spread
Well, that's a great thread, very informational and somewhat changed my opinion on this.
I basically figured since my symptoms aligned 100%, and also since I live and work near the largest casino in the Bay Area (which is a hub for tons of international travelers and people from SF Chinatown) that Corona was circulating around Wuhan in Nov, and made it to the Bay Area by December, and I caught it early Jan.
I still think that's a possibility, but it does seem like it would have made it to Seattle before mid-to-late February in that scenario.
This is not news. The same was already reported one month ago in the Italian village of Vo, where the entire population was tested for Corona. Summary is here: https://www.bmj.com/content/368/bmj.m1165
"In an open letter to the authorities in the Tuscany region,1 Romagnani wrote that the great majority of people infected with covid-19—50-75%—were asymptomatic, but represented “a formidable source” of contagion."
In the same report was another interesting paragraph as well:
He noted that Romagnani’s findings appeared to contradict a WHO report based on covid-19 in China.2 This suggested that “the proportion of truly asymptomatic infections is unclear but appears to be relatively rare and does not appear to be a major driver of transmission.”
edit: really, downvoted? Because of the mentioning of China?
”Roughly 60 percent of the over 600 sailors who tested positive so far have not shown symptoms of COVID-19” — note how “so far” is ambiguous in that sentence. It also states, “The Navy’s testing of the entire 4,800-member crew of the aircraft carrier - which is about 94% complete...”, which seems to indicate nowhere near enough time has elapsed to draw any sort of conclusion.
This paper [1] found that testing of all pregnancy patients in a hospital yielded 34% asymptomatic cases. That number drops to 8% “shortly after discharge”, and could be lower than 8% (Again, no timeframe is stated).
[1] https://www.sciencedirect.com/science/article/pii/S258993332...