Initial Covid-19 infection rate may be 80 times greater than originally reported | Hacker News Reader

Initial Covid-19 infection rate may be 80 times greater than originally reported

news.psu.edu

102 pointsburlesona194 comments

I became numb to news like this because it doesn't seem to have any reflection in the reality around me. The numbers are supposed to be huge yet hospitals are nearly empty and no one I asked knows anyone who was infected. The 80x number looks like science fiction to me.

Well, that obviously depends on where 'around you' is.

Compare to New York City, where there have been an estimated 17,000 deaths (and even that's probably undercounted, going by some studies of excess deaths compared to previous years), and at the peak there were hundreds of unclaimed bodies per week being buried in mass graves.

This is completely anecdotal, but my good friend’s brother is an ER doctor. He said the hospital required them to label the cause of death for all patients in the hospital as covid if there was as much as one symptom.

I don’t want to downplay the sadness of the deaths, but I think it is a bit foolish for us to base our number of deaths of off untested patients...

Except you can see the excess total deaths compared to previous years and how well it correlates and is otherwise unexplained [1].

A lot of the labeling occurred because people couldn’t get tested yet presented symptoms that indicated covid. In that situation, you can’t say 100% without a test, yet it’s the reasonable conclusion in a pandemic.

[1] https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm

Something worth keeping in mind is how many fewer people died of other causes compared to previous years [1]. Yes, the data will show an excess number of people died versus previous years but I believe the parent comment is saying we should pay close attention to what the cause of death really means in terms of age and comorbidity.

[1] https://i.imgur.com/HfaMhcK.jpg

One further thing to bear in mind here is that some causes of death can be expected to be decreased on account of lockdowns e.g. accidents - less people out and about, less people driving etc. will naturally lead to less accidents. Of course on the flip side, more people stuck at home & using the time to do renovation work etc. could lead to an increase in e.g. power tool related accidents.

Other causes of death such as flu can likely also be assumed to be decreased as a side-effect of lockdown

Contrariwise, people are avoiding treatment for other illnesses for fear of catching COVID in a hospital. Many people are depressed or even suicidal. And people are less active, which aggravates other health problems. All of these factors could increase the number of deaths.

If it was significant in comparison, we would not see a sharp drop in deaths after the lockdowns.

Do people get depressed and die because of a lovkdown? Sure, I got depressed as well. But the numbers show that this issue is far less than the number of people that would die otherwise.

3 months of lower activity is not killing people in those 3 months.

Any effects will be felt on a much longer timeframe.

Most office workers have very sedentary lives anyways, that didn’t become significantly more sedentary when they replaced their drive with a walk to another room and working in an office with working in that room.

Throw in the fact that they are likely cooking more because restaurants and all were shut and not just having lunch delivered to their office, they may even be getting more activity in.

Plus no commute leaves more free time in the evenings for exercise etc. Obviously not everyone will be doing that, but anecdotally a few people I've talked to from work are going for more walks & cycles etc.

Curious if we know specifically what caused the tens of thousands of excess deaths that showed up around January 2018? Was that a particularly bad flu season?

The most reliable number is "excess deaths", since that's hard to fake even if it's not specific.

You can just look at the all cause excess deaths and see that the number of people that have died so far this year is much higher than previous years in New York. So whether you agree that person A died from covid or not, there were many more deaths due to something.

What is the effect of fear? Cortisol spikes and avoiding going to the doctor for what would normally be a good reason need to be researched.

That is something worth researching, but even then, it's still justifiable to count a death by fear as a death by pandemic, given that it wouldn't have happened without the pandemic.

You can have a pandemic without fear though.

Really? Has there ever been one? Or is the fear a natural human response to an invisible, omnipresent killer?

Well, I guess I should say you can have a pandemic without a fear-mongering news media that significantly exacerbates it.

I personally am not "fearful" of COVID-19, as are many (most) people I know, so it is clearly possible for the general human.

If you're not fearful and nor are most people you know, who are you claiming is fearful?

Personally, my behaviour patterns have changed. I'm more aware of when someone I don't know is near me. When I hear about the vulnerable people in my close community who suddenly have to navigate the world with significantly increased risk, I feel worried for them.

I'm not claiming anyone is fearful?

I claimed you can have a pandemic without fear.

Reduced access to healthcare, counterintuitively, reduces mortality in the short term, because it reduces complications from medical interventions.

On the medium and long term instead it increases mortality, as expected.

Moreover, lockdowns and social distancing also reduced flu deaths.

This means that the total number of deaths attributable ti Covid may in fact be higher than the excess mortality over the average of previous years, although it is difficult to quantity the difference.

Its still caused by the virus. It counts.

Not completely. Fear is very profitable, it makes people more pliable, people that are afraid are less rational. There are strong incentives to make people irrationally afraid.

woah, i just looked up excess deaths in my city vs covid19 diagnosed deaths and it is freaking me out even more.

Based on excess deaths - the difference between how many deaths from all causes would you exec and how many were reported - USA is very likely under counting deaths. Also all case mortality coincide very well with reports of COVID-19 cases.

USA is very likely to significantly under count deaths from COVID-19.

See: Preliminary Estimate of Excess Mortality During the COVID-19 Outbreak — New York City, March 11–May 2, 2020

https://www.cdc.gov/mmwr/volumes/69/wr/mm6919e5.htm

How you label the deaths is not that big of a deal in the larger scale. If you want to know the true toll of the epidemic, just look at this year's deaths vs. an average of previous years. It's simple and transparent.

Here's that data for England:

https://imgur.com/sxoolBX

I get why everyone is questioning everything, but there isn't some big conspiracy here. Lots of people died of COVID. Most of them were 80+. You probably don't know any of them if you don't hang out with 80-90 year olds.

But then we get to the question of whether those deaths were caused by COVID or other causes.

We know that traffic fatalities in some areas have risen drastically due to the lockdowns: https://abc7.com/traffic-fatalities-california-highway-patro...

We also know that doctor visits have gone down due to the coronavirus, leading to medical staff being laid off: https://www.npr.org/sections/health-shots/2020/04/02/8262324...

We also know that hospitals are financially incentivized to diagnose a patient as COVID positive: https://www.usatoday.com/story/news/factcheck/2020/04/24/fac...

And there are German serological studies that suggest a COVID death rate of 0.39%, in contrast with the NYC study that claims a death rate of 1%

Taking this altogether, and we have plenty of wiggle room to suggest that even the excess deaths don't necessarily imply that COVID is extremely deadly.

You are conflating a lot of different things.

Traffic fatalities were actually down overall (total numbers), but up per mile driven. In other words, people were driving much less and dying in lower total numbers, but the people who were driving were driving faster and thus a bit more likely to die. That article is poorly written to generate headlines and clicks.

Arguing over a specific IFR is also kind of pointless because the disease is so age and condition dependent. Whether the true overall IFR in a population is 1% or 0.4% doesn't really matter - it's a bad representation of the overall situation. COVID is a disease that kills a very large percentage of 80+ but is quite low risk for younger people. A single number doesn't capture or represent that. Demographic differences between 2 cities could easily cause a large skew in actual IFR.

Hospitals are (possibly) financially incentivized to diagnose COVID in the US. But this is a world-wide disease and no other country has the insane US healthcare system where that would matter.

> Taking this altogether, and we have plenty of wiggle room to suggest that even the excess deaths don't necessarily imply that COVID is extremely deadly.

That's not correct. It's absolutely clear from the numbers across many countries that COVID is extremely deadly if you are 80+ and not deadly at all if you are 15. Make of that what you will. Arguing over IFRs and hospital reimbursement is missing the point. It's simultaneously true that COVID is very deadly for some groups but may not be deadly at all for you and your friends.

There's a good argument to be made over how much of the excess death is due to secondary effects (untreated heart attacks, delayed cancer treatments, etc). But there's no way to arrange the numbers such that COVID doesn't obviously kill a lot of old people. Just look at the death rates in care homes / retirement homes. It was like a plague ravaging them.

> and not deadly at all if you are 15

Very low risk, but not no risk.

Yes, not zero risk. But to give you an idea of the risk, here are the numbers from England (only, not entire UK):

- Total COVID deaths: 28,137

- Deaths, 0-19 years of age: 18

- Deaths, 0-19 years of age, no pre-existing condition: 3

You are definitely going to see individual news reports on those 3 cases because they are exceptional and scary. But you aren't going to see individual news reports on the 25,721 people aged over 60 who died of COVID during the same period.

And keep in mind that not only are the raw numbers astronomically higher for the older age ranges, but those older age ranges are also much smaller populations. So it's even worse than it appears.

For example, 15,020 people aged 80+ died of COVID. But 80+ year olds are only 4.6% of the population in England. Under 18s make up more like 25% of the population but only account for 18 deaths. That's about as close to low risk as you can get without being zero risk.

> Hospitals are (possibly) financially incentivized to diagnose COVID in the US.

That depends. Some, apparently, are incentivized to do exactly the opposite.

https://www.beckershospitalreview.com/legal-regulatory-issue...

1. My link stated that in certain areas, such as Connecticut, traffic fatalities went up.

2. My overall point is that a certain number of excess deaths are atrributable to the lockdown itself, rather than Covid. IIRC, the total number of reported deaths in NYC from heart disease, heart attacks, cancer, and a whole bunch of other diseases went down drastically; either Covid-19 magically cures all these other ailments, or a bunch of deaths are being mislabelled as Covid-related.

There is no wiggle room. The fucking deaths doubled. This is just FUD.

> And there are German serological studies that suggest a COVID death rate of 0.39%, in contrast with the NYC study that claims a death rate of 1%

That’s in the same ballpark. You can expect great precision with these estimations.

Similarly, several people I know have self-diagnosed themselves with COVID-19 due to just one symptom. In some cases the symptoms have disappeared the next day. In many cases the people are the "usual suspects" who seem to get ill several times a year anyway. I'm not aware of a single person who has definitely had COVID-19.

I also read that in Florida, the number of COVID-19 deaths is fairly low. Instead, the death rate from regular pneumonia is sky-rocketing.

> my good friend’s brother is an ER doctor

I've seen a number of rumours from brothers of friends or friends of brothers, but no actual doctors saying this.

Singapore has had a death rate of 0.06%, with ~42k cases. The main difference between them and the rest of the world has been how much they test. New York has more hospital beds per 1,000 than Singapore does for instance. There’s no other factor that could possibly explain the death rates being off by more than 3 orders of magnitude between those two places.

That doesn't explain it, though: the number of NYC deaths so far is 0.2% of its population. Assuming 100% of NYC is infected, that's a floor of 0.2% IFR. No amount of under testing can explain that.

Which isn't to say that Singapore's death rate is an undercount, but that higher testing rates can't explain it.

I think the mistake that many people keep making is trying to nail down a single IFR. There isn’t one.

The fatality rate depends heavily on the demographics of the infected population. IFR of a entirely young demographic would be below 0.01%. IFR of a nursing home would be 3 orders of magnitude higher.

If someone shows me a low IFR I can safely bet that they surely aren’t finding 50% of their cases in their nursing homes.

Conversely, if 50%+ of your cases are in nursing homes, your population IFR is going to look a lot worse than if you had kept that relatively small population safe.

The difference with Singapore probably has more to do with how (a) face mask wearing was and still is compulsory for everyone at all times outside of their homes (the fine for not doing so is the equivalent of $210 USD), and (b) every single government-run community center in the city had free reusable face masks available for months for anyone who didn't already have one.

Singapore’s actual death rate is also a much more reliable number than New York’s. The NY criteria for recording a Covid death has been pretty much anybody who could have potentially been infected at their time of death. There are some other confounding factors too, like SG infections being primarily among young people, and NY state discharging Covid patients to nursing homes. But none of that explains the monumental difference in death rates between SG and pretty much the entire rest of the world. The virus is certainly far less deadly than most reported statistics would have you believe.

The criteria don't really matter, because we can look at the total number of excess deaths to reliably see that an absurdly excess number of people died in NYC compared to previous years.

> The NY criteria for recording a Covid death has been pretty much anybody who could have potentially been infected at their time of death.

This is false. Even if it were true, you could look to NYC's excess deaths and see a huge surge in them that would correspond to a similar IFR.

> The NY criteria for recording a Covid death has been pretty much anybody who could have potentially been infected at their time of death.

This is a common "fact" asserted in these discussions, and it's never backed up with any evidence.

https://www.theguardian.com/us-news/2020/apr/15/new-york-cit...

> The soaring death toll has been fueled by the adding of 3,778 people who were not tested for Covid-19 but are presumed to have died from it.

Singapore’s organised approach is clearly going to produce much more reliable statistics than NYs presumption based approach.

"Presumed to have died from it" is quite a long way from "anybody who could have potentially been infected".

Doctor friends tell me it's usually pretty clear when they have a COVID patient.

The criteria is whatever a doctor chooses to put on the death certificate, for what ever reason they choose.

https://www.nbcnews.com/news/us-news/new-york-start-reportin...

> Asked about the numbers Wednesday, Dr. Oxiris Barbot, commissioner of the city Health Department, said the "unfortunate reality is there have been people who have died either directly because of COVID or indirectly because of COVID."

> Barbot said only time would tell what that number really meant. Some deaths, for example, could have been registered as having been caused by heart attacks because people had not yet developed coronavirus symptoms, when they should have been counted as probable COVID-19 victims, she said.

So NY officials state that their recorded death toll should reflect both direct and indirect fatalities, whatever an indirect fatality is supposed to mean, and that a person who dies without Covid symptoms, and who has not tested positive, should be counted as a fatality. So unless they have proof Covid wasn’t a contributing factor in any way, it’s counted, which does actually sound a lot like “ anybody who could have potentially been infected”...

You can't just data this stuff. There's so much nuance and context in the data that it's very hard to compare countries.

Singapore is militant on testing everyone. This presumably gives a high fidelity on the "true" spread of the virus.

What is also true is that Singapore has been extremely militant on isolating and controlling the virus. Their staff have ample PPE and their hospitals have very successfully isolated covid positive patients. For instance, anyone positive here is quarantined in a govt run facility and cannot return home until testing negative two days in a row. This may have recently relaxed but was true throughout circuit breaker/lockdown. I believe they are also trying to partition covid patients from non covid patients at the hospital level. (eg NCID)

Both anecdotally from frontline doctors, and from reading various news reports, a big problem about the first wave of covid was how the problems can snowball. Hospitals were very easily filled up with sick patients, but worse any existing patients could very easily catch covid. For example cancer patients who are immunocompromised.

So the lethality of the disease is actually a function of its local penetration as more people die if hospitals effectively experience cascading failure.

My understanding is that tipping point is quite fine, this is especially true back in March when everyone was still hoping it wouldn't reach their shores, and hospitals had very limited space for isolating covid patients and for treating patients that required ICU.

While hospitals have been empty I also know that hospitals have become extremely aggressive at not accepting patients. For example, my friend's mother was bedridden for a month but was never seen by a doctor. Meanwhile you have people dying at home and in care homes, so I think "hospitals are empty" doesn't tell the whole picture.

"There's no other factor" Yes there is. In singapore the death rate was much higher until covid moved into foreign worker dorms, where everyone is younger on average than the general population... You need to look at mortality rate by age group. South Korea also has relatively complete testing/tracing, you can find that data on the wikipedia page on covid19 in s. korea.

It's not a given that people keep dying at the same rate year after year.

Unclaimed bodies have been buried in "mass graves" in NY for many years. It's just it didn't occur to anyone to film this from a drone before to drive clicks and outrage.

The real scandal is that NY, NJ, CT, MA and a few other states allowed C19 to spread in elderly care facilities and nursing homes. NY and NJ inexplicably _sent COVID patients_ there. As of Jun 2nd, nursing homes are responsible for 40% of all US COVID deaths: https://www.cidrap.umn.edu/news-perspective/2020/06/nursing-.... If heads don't roll for this, I don't know if we have justice in this country.

Same for Sweden.

The death rate per million in NY and NJ is almost _three times_ that of Sweden.

This article [0] says over 4,500 covid-19 patients were sent to nursing homes in NY yet Cuomo pretty much has dodged liability for it, he is still pretty much is a press darling.

[0]https://apnews.com/5ebc0ad45b73a899efa81f098330204c

This is number of infections not number of hospitalizations. This study implies the disease is orders of magnitude less deadly than we thought.

I'm actually annoyed we still don't know the exact death rate of the virus.

I am not sure if it would be that unethical to call up volunteers that reflect the general population to establish the real death rate. (even less so if you reward them economically)

If it is orders of magnitude less deadly then that should have enormous policy implications.

Diseases unfortunately don't have a real death rate; the death rate of diseases tends to vary widely between populations for inscrutable reasons. Even if we had a study determining an 0.3% death rate among a statistically representative sample, we couldn't make policy under the assumption it's below 0.5% and couldn't be absolutely certain it's not 1%.

Yes, we could and should make policy under the best data available even if we'd prefer better ones.

I don't think that's true. It's very dangerous to make epidemic policy without accounting for model uncertainty, because by the time your model's clearly and unambiguously falsified it may be too late to deal with it.

No, not at all. Of course the model may underestimate the lethality, but it may also overestimate it so it evens out.

That depends entirely on where you are and what time you started looking. Three weeks ago if you'd asked me I would have said the same things as you.

Since then, cases in my city have started increasing drastically. And now, I have at least two people I know who've tested positive.

Odd, I know a number of people who've had serious symptoms and a friend of a friend was Scotland's longest hospitalised case (well over a month). Fortunately nobody I know has died but some are reporting lingering symptoms.

In Poland there has been an outbreak among miners in multiple coal mines. 98% of them are reported to be asymptomatic and those are people often working in hazardous conditions.

Isn't this the exactly case, though?

It's not about how infectious it is, but how severe. Early reports said that 90% or more [1] people develop symptoms and that the average death rate is 3.5% (with some outlets even suggesting 10%...).

If we divide those estimates by 10 we're getting 9% of symptoms and 0.35% lethality. While I won't argue for 80 as being the number that's almost 2 degrees of magnitude. That would mean that 0.9% people have symptoms and 0.035% has severe case. This is on par of 2009 Flu pandemic and 3 times more than regular seasonal flu.

Now, I have no idea how reputable source is or how trustworthy this exact article is but that's one of the perspectives that were present since almost the beginning of pandemics.

Note: Since I don't really gather articles those might be low quality republishes

[1]: https://www.msn.com/en-us/health/medical/covid-19-symptoms-t... [2]: https://www.theblaze.com/news/german-study-shows-coronavirus...

There wasn't a consensus back in February that covid19 was the black plague. Even though we didn't have the data to justify shutdowns, governments everywhere shutdown businesses because politicians won't personally feel the pain of job loss.

> Even though we didn't have the data to justify shutdowns

0.2% of the entire population of New York City died over the course of a few months, even with a full lockdown in place.

Which is either evidence in favor of lockdowns or evidence that the lockdown was useless - one of the two.

We had data to justify shutdowns on the basis of a possible (i.e. consistent with the data that we had) worst case scenario. Doing nothing while waiting for more data to narrow down is itself a risky choice.

People want this thing to be over, so there's a desire to find reasons to believe that we are further along than we thought. Combined with this being a novel disease that no one fully understands, there's a lot of room for those theories to develop. The current best science answer to how many people remain susceptible to infection is "nobody really knows but our best guess is not to assume the best case without better evidence so act like the worst case".

But one thing that is easy to explain is your point about not knowing anyone who was infected:

- At the peak of this epidemic in hard-hit places like the UK, something like only 1 in 400 people are known to have been infected at a time.

- Many younger people (as much as 70%) show absolutely no symptoms when they are infected.

- The disease is astronomically worse for elderly people. One study said that for young person, getting COVID was as risky as going for a ~200 mile car drive but as a 90 year old it was as risky as flying a WWII bomber mission. Nearly everyone who is dying is 70+ and mostly 80+. Obviously some younger people do die, but the numbers are much, much lower. We are talking 10s of people total under 40 in most countries.

So unless you are hanging out with a social circle of 80-90 year olds, you actually aren't very likely know anyone directly affected! But that doesn't mean tons of people weren't dying. They just aren't the people you would know. It's a different social circle.

> - The disease is astronomically worse for elderly people. One study said that for young person, getting COVID was as risky as going for a ~200 mile car drive but as a 90 year old it was as risky as flying a WWII bomber mission

Interesting comparison. So here we're talking about the risk of dying from Covid-19. What about the risk of becoming seriously ill? What I'm curious is about is the percentage of people (younger or otherwise) who either develop no symptoms or develop symptoms so mild as to not be attributed to the virus. Do such people exist?

There's also not enough discussion about what happens after recovery.

I was pretty ill in March (and, to a lesser extent, in April), which necessitated some time off work. Testing availability in my country was useless at the time, so I have no formal confirmation as to what it actually was. The govt also intervened, preventing my order of a private sector antibody test being fulfilled, so who knows.

The experience after recovery for me, though, was anything but straightforward and I really struggled with lasting fatigue, breathlessness and just general exhaustion. I was only able to work half-days for a decent chunk of time. I still don't feel 100% now. My GP thinks it was likely Covid-19 and offered a diagnosis of post-viral fatigue after some tests.

I'm 23. Statistically, this should have barely affected folks in my age group.

It's not an isolated case: https://www.bbc.co.uk/news/uk-scotland-north-east-orkney-she...

It's been exactly the same story for someone I know. They had a mild-but-less-mild-than-usual flu in March that was 'strange' in all the ways covid-19 is said to be. They had 'issues' like yours well into April and still don't feel 100%. No official diagnosis though.

I've been reading lots of reports like this from young people. One person in their 20s ended up with lasting asthma when they'd never had it before. A couple have needed lung transplants.

This category of outcomes is honestly much scarier for me.

Right. I have some pre-existing breathing issues that, even though I'm an otherwise healthy adult under 30, would probably lead to my death if I catch this. Not wearing a mask seems disrespectful to the hundred thousand + dead in the US alone. If you don't wear a mask, and I get sick, I might die. That's such an easy thing to do to prevent passing the disease on by 70%.

Good luck with your recovery.

> What I'm curious is about is the percentage of people (younger or otherwise) who either develop no symptoms or develop symptoms so mild as to not be attributed to the virus. Do such people exist?

Yes, absolutely. Many countries such as England do community infection studies. Essentially they pick a random sample of people and test them every week to see many people have the disease, even if they don't know it.

In the England study, they report that ~70% of positive tests involve people who didn't report any symptoms ever. That implies there are lots of people who had it who didn't know they had it.

> Out of those people that tested positive for COVID-19 over the study period, only 23% (95% confidence interval: 15% to 32%) reported experiencing one or more of the various symptoms at the time of their test. Out of those who reported testing positive, 33% (95% confidence interval: 23% to 44%) reported experiencing symptoms at any point in the period around testing positive. This was at the time of the visit, or at either the preceding or following visits.

https://www.ons.gov.uk/peoplepopulationandcommunity/healthan...

Of course, the question is do these people get counted later in other ways - i.e. what percentage of them would show up in antibody surveys? That is currently a difficult question to answer with a high level of certainty for several reasons. Right now, we don't know for sure what level of infection causes you to develop detectable immunoglobulins, we don't know how long those stick around, and we don't know how much our immune system leans on T cells instead to fight COVID which don't show up in the existing antibody tests at all and are much more difficult to test for.

And it's also worth pointing out that it's not clear that asymptomatic infections are as infectious as symptomatic infections. So don't assume they are equal. A recent study showed that asymptomatic people could shed the virus for 3 weeks, but it's really hard to know if that's active virus that could infect someone or not. There's a lot more research to be done.

See https://blogs.sciencemag.org/pipeline/archives/2020/06/22/th...

> it's not clear that asymptomatic infections are as infectious as symptomatic infections

Yes it is clear (they're not)! Superspreading events are caused by people who are clearly symptomatic but don't act responsibly. Most spreading in total happens via nonsymptomatic or presymptomatic people, because covid19 is a coronavirus and that's how coronaviruses work. No point in pretending this is some kind of big unknown.

If you don't believe me, let's look at this story of army recruits. Those who tested positive were isolated, those who remained tested negative and trained together with masks and social distancing. Result, 8 days later 142 out of 640 tested positive. https://outline.com/dK2TWd

>> What I'm curious is about is the percentage of people (younger or otherwise) who either develop no symptoms or develop symptoms so mild as to not be attributed to the virus. Do such people exist?

My spouse and I both work in a hospital. She got covid and so did one of our two siblings. Neither of them had any symptoms (spouse is in her 50's, our sibling is twenty plus.) I never got it nor did our other sibling. I also don't have antibodies. Go figure... it makes no sense to me.

As a side note: we are not in patient care, however when this was at it's early peak here in the States--I don't know how the nurses, aides, and doctors were able to do their jobs everyday. It was fricken scary walking through the halls and passing workers dressed in plastic; what with all the unknowns at that time, and the news reports of death throughout the world. Those workers deserve respect if not outright awe and a Huge Cash Bonus... Huge.

> My spouse and I both work in a hospital. She got covid and so did one of our two siblings. Neither of them had any symptoms (spouse is in her 50's, our sibling is twenty plus.) I never got it nor did our other sibling. I also don't have antibodies. Go figure... it makes no sense to me.

I know it's anecdotal but it's interesting that your spouse contracted the virus but you did not. I'm assuming you live together. But then again I imagine it is quite common for one person in a household to catch a cold whilst everybody remains unaffected...I'm not equating covid-19 to the common cold. It came to mind as something that appears to spread in the same way.

Also not everyone who gets it will notice and they may not even generate antibodies. If the innate immune response (as opposed to the adaptive response) is strong enough the patient can get infected and recover without ever generating antibodies.

I can’t find the reference right now but I gather very few people spread the virus and it relies mainly on a small percentage of super-spreaders.

Anecdotally, I know at least one person in their early 30s who was seriously ill for a month. He got turned away from hospitals and testing, but he couldn’t sleep well for about a month because he had to consciously think about breathing. Saying “it‘s as dangerous as a 200 mile car ride” obviously doesn’t really capture the full picture.

From what I heard, about half the deaths are people under 55 (edit: I can't find that source anymore and all figures suggest it's wrong). The individual risk is still higher the older you are, but plenty of young people have died from this (610 in the US, for example).

But even if you don't know anyone who died from it, you can still know people who are ill. My ex-brother-in-law has been in and out of the hospital 4 times for COVID-19.

In many countries, old people are less likely to get infected, because those countries take special effort to protect old people. Some countries didn't or messed up, which has lead to massacres in elderly care homes.

Though the real big risk here is: it's possible to carry the virus without having any symptoms. So you can transmit it to other people without ever realising.

That's not true. All believable statistics I have seen show only very small number of deaths in age group 55 and lower.

Outrageous claims require outrageous proofs, you need to volunteer your sources if you want to convince anybody that 55 and younger are large share of deaths.

"From what I have heard" is not an outrageous proof on HN.

https://www.worldometers.info/coronavirus/coronavirus-age-se...

There's different ways of looking at statistics. Most statistics are about the death rates for infected cases per age group, which doesn't account for situations where elderly people are kept from coming into contact with the virus in the first place.

Unfortunately, I'm unable to find good global statistics on absolute number of deaths broken down per age group.

I have come across the claim I mentioned in response to a claim that young people almost never die from this. That is simply not true: young people do die, but it looks like half is indeed an exaggeration. Even so, the claim that it's in the double digits is also false; in the US, 610 people under 44 have died[0]. Claims that young people are perfectly safe are dangerous, even if the danger is a lot higher for older people.

[0] https://www.worldometers.info/coronavirus/coronavirus-age-se...

610 out of ~200 million is almost never in my book. For comparison, the average annual fatalities from lightning in the us is 43.

610 people under 44 is terrible.

But you do realise over 120 THOUSAND died in the US in total. 610 out of 120,000+ is a mere half percent.

In my country the breakdown for excess deaths is:

15 - 44 = 27

45 - 64 = 589

75 - 84 = 1356

85 + = 1761

If you are under 40 your risk of dying seems to be very very low.

> If you are under 40 your risk of dying seems to be very very low.

Based on the figures you provided I make that close to 0.7%. It is low but I wouldn't describe it as very very low :-)

You did the math incorrectly. You can't add up the total deaths and then divide by one of them to get your chance of dying in that age group.

The populations of those are ranges are different sizes. There are many fewer people alive who are in the 85+ group than there are in the 15-44 group. So if you work that out based on the relative population sizes, you'll get a much lower death rate for the under 40 group.

Exactly, for example for cases under 40 y/o:

South Korea: 5539, deaths = 5 = 0.09%

Switzerland: 8874, deaths = 5 = 0.05%

Italy: 37139, deaths = 84 = 0.22%

Netherlands: 8207, deaths = 14 = 0.17%

This is from wikipedia for the respective countries, some countries figures are more up to date than others.

> From what I heard, about half the deaths are people under 55. The individual risk is still higher the older you are, but plenty of young people have died from this.

You are incorrect. COVID is largely a disease that affects the elderly and those with pre-existing conditions. Here are the actual numbers from England (England only, not to be confused with the overall UK):

- All COVID deaths, age 0-59: 2,210

- All COVID deaths, age 60+: 25,721

And of those 2,210 people under 60 who died, only 261 didn't have known pre-existing conditions.

Also, the older age groups are actually smaller populations than the younger age groups. So the death rate is even higher than the raw numbers suggest.

If you define "young" as anyone under 40, the difference is even more stark:

- All COVID deaths, age 0-39: 224

- All COVID deaths, age 0-39, no pre-existing condition: 36

Note: Obviously the young and healthy should still avoid exposure to avoid infecting others and also because there is of course always some risk of both death and long-term damage.

Note that the person I was responding to was talking about 10s of people, you're already pointing out it's hundreds or thousands.

My point is merely: don't think you're immune just because you're young. More young people have died from this than most people think.

> The current best science answer to how many people remain susceptible to infection is "nobody really knows but our best guess is not to assume the best case without better evidence so act like the worst case".

Absolutely not. The scientific approach is to look at the new disease and see how it compares to other similar RTIs. For instance, covid19 was discovered around October at the start of the seasonal flu season in the northern hemisphere and it was a coronavirus, which makes it 95% likely to be strongly seasonal, highly infectious, and mild. It also should lead us to assume that exposure to prior viruses gives (some) protection, and that the elderly and immunocompromised are the most at risk. In addition, we know that diseases like this spread highly unevenly (powerlaw distribution) with a small number of big hotspots and many places that are left largely unaffected.

This is the BASELINE SCENARIO, based on the knowledge we have of hundreds of similar respiratory infections. Covid19 could be a different animal, but for that we'd have to carefully look at the data.

But what did we do? We took seriously the doom-saying of scientists that extrapolated from comically unrepresentative cruise ship data and other hot spots. This is junk science, because data from a hot spot doesn't say --anything-- about how infectious a hotspot disease is or how deadly, except that it's possible for people to die from it, but that's also entirely unsurprising for a RTI.

> At the peak of this epidemic in hard-hit places like the UK, something like only 1 in 400 people are known to have been infected at a time.

Impossible. Covid reached Europe by December, and has spread like wildfire since.

> Many younger people (as much as 70%) show absolutely no symptoms when they are infected.

Oh no, way more than 70%. How many kids got visible symptoms? Close to zero. And many got infected because the virus is absolutely everywhere. At least 70% of people in the 50-65 age group have no visible symptoms, so for young people the number must be drastically higher.

> The disease is astronomically worse for elderly people.

All cause mortality isn't high worldwide. We had two mild flu seasons in a row and that left us with many elderly with a negative life expectancy.

> Absolutely not. The scientific approach is to look at the new disease and see how it compares to other similar RTIs.

I think the the scientific approach is to use the best data you have at a given time and update your understanding as you get new data. You make a lot of big claims that contradict multiple specific studies with published results. It's clear you hope that the epidemic is over (as we all do). But hope isn't enough.

To quote Derek Lowe [1], a scientist working in drug discovery:

"Everyone will have seen the various population surveys with antibody testing that have suggested, in most cases, that a rather small percentage of people have been exposed. Think of the various ways you could get such a result:

(1) it’s just what it looks like, and most people are unprotected because they have so far been unexposed.

(2) the antibody results are what they look like – low exposure – but people’s T-cell responses mean that there are actually more people protected than we realize.

(3) the antibody results are deceiving, because the antibody response fades over time, meaning that more people have been exposed than it looks like.

(3a) the antibody response fades, but the T-cell response is still protective

(3b) the antibody response fades and so does the T-cell response. That last one is not a happy possibility."

So we essentially have 4 plausible scenarios that explain our best study results. We all hope it's (2) or (3a). But I wouldn't say that we have a lot of actual evidence to prove that yet.

[1] https://blogs.sciencemag.org/pipeline/archives/2020/06/22/th...

Scientific consensus takes years to form, so any claim I make will be contradicted by some scientific findings and affirmed by others. What I outlined in the part you quoted is the null hypothesis: that this new coronavirus behaves like the other coronaviruses we are familiar with. That may of course turn out to be false, but it's indisputably the correct starting point for any serious analysis.

My objection was that many early predictions disregarded this null hypothesis and only looked at preliminary data thereby discarding everything we've learned about RTIs in the past 200 years. That's how you end up with predictions that are off by 1000x or more. That is a huge blunder, and really inexcusable.

You say we don't have a lot of actual evidence yet, but I think we do. For instance we see that Sweden that didn't lock down has practically indistinguishable All Cause Deaths outcomes as the neighboring Nordics[1]. Many predicted that Sweden would have catastrophically worse outcomes but it hasn't. How is that possible when clearly the virus is spreading freely in Sweden but the outcome isn't any worse? Locking down a country 5 months into the Flu season is completely pointless because by that point too large a percentage of the population is infected already, so you wouldn't expect that to make any kind of meaningful difference. And that's consistent with the data. In the VS abnormal deaths were at a 6-year high in November[2]! The notion that Covid19 was contained for --months-- in China is an absurdity, given how much we travel by air. Antibodies were also found in sewage from December all over Europe, which proves beyond a doubt that virus spread without us even realizing it for months! If I had more time I could give you countless more sources, but the evidence clearly points in one direction: New coronavirus just like other known coronaviruses.

[1] https://pbs.twimg.com/media/EZlnYQCU0AA0jkv?format=png&name=...

[2] https://pbs.twimg.com/media/EZNQ9arUEAAS9W9?format=png&name=...

I'm all for discussing how to best deal with the virus and which measures best contain the spread. Sweden is an interesting experiment. But your sources are lo-fi. I was unable to read the second picture. Check out https://euromomo.eu for a good source.

> For instance we see that Sweden that didn't lock down has practically indistinguishable All Cause Deaths outcomes as the neighboring Nordics[1].

Sweden had very high excess mortality compared to its neighbors and is still showing abnormally high. For Norway and Finland the numbers remained flat. Your plot sums up the entire winter and stops at week 18! It's decidedly not fine-grained enough to judge lock-down effects.

> New coronavirus just like other known coronaviruses.

Even for younger people we haven't seen a peak in deaths like that in a while. Looking at Euromomo the age bracket 15-44 years saw a 15% increase in deaths during a whole month. An unprecedented increase in the last five years. We don't know how much worse the numbers would be without lock-down. And it's not over yet.

Please don't say that the virus is "just like other coronaviruses". Most of them are benign and not even tracked that much. So we know little about them. SARS-Cov2 can well be compared to SARS-Cov which is extinct. Luckily.

If you're just going to ignore the charts I posted what's the point? I already provided you with a chart that shows that, in fact, Sweden does not have exceptional all cause mortality. Not compared to its neighbors and not compared to previous years in Sweden. Yes, the chart is a month old, but if nothing exceptional is going on by May and covid deaths have steadily declined since[1] there really isn't a story here.

Euromomo data is preprocessed data and not suitable for analysis. Get the raw all cause mortality statistics (by age group if possible) directly from each country health agency, and use that instead.

[1] https://adamaltmejd.se/covid/

Of course I'm ignoring your charts! After explaining that the first of your charts is too broad, and the other I can't read the labels of. I was giving you the benefit of doubt but after your answer I must presume you're picky with your sources to protect your story.

I'm not aware of a flaw in the Euromomo collection. Why discount it? I think they're more competent at collecting death-tolls than I am. What would be the benefit of me collecting the numbers myself?

Do you disagree with my estimate of 15% excess mortality in the 15-44 age-bracket? Or do you know of a Coronavirus epidemic in the past that had a comparable effect?

> Impossible. Covid reached Europe by December, and has spread like wildfire since.

Can you source this claim?

https://www.reuters.com/article/us-health-coronavirus-italy-...

That's one.

And CDC data shows that Covid was already widespread in October 2019:

https://pbs.twimg.com/media/EZNQ9arUEAAS9W9?format=png&name=...

With a spike in abnormal deaths 24 days later in November. For covid deaths to be clearly visible in November it must have been widespread a month before that, and starting its spread around September.

I have no idea where you get your graphs from - the chart you want is this one: https://www.cdc.gov/flu/weekly/weeklyarchives2019-2020/image... (pneumonia and influenza mortality, COVID kills via penumonia and as such is in that graph), the spike at 2019-50 is the normal flu reason (you can see we were having a slightly above normal one that started to decline out), the spike at week 10 onwards is COVID-19. Likewise, looking at ILI (influenza like illnesses), you can see the normal flu season spike near week 50, a decline towards baseline, and then a rise towards week 10 https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html (ILInet line graph), followed by a decline as stay at home orders began to come into effect.

COVID emphatically was not circulating in numbers in november. We would have noticed, same as the chinese did, from the massive increase in pnuemonia clusters. Genetic analysis backs this up. You don't know what you're talking about, again.

While this paper[1] doesn't attempt to provide exact dates, the phylogenetic data suggest that there were multiple seeding "events" in each country before outbreaks were actually noticeable.

[1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7199730/

You have no cause to sound as confident as you are. You're completely wrong in the first paragraph in a way that shows you don't understand the first thing that you are talking about. For example, you say " For instance, covid19 was discovered around October at the start of the seasonal flu season in the northern hemisphere and it was a coronavirus, which makes it 95% likely to be strongly seasonal, highly infectious, and mild" First, it was discovered in late December, probably jumping to humans in November. Second, there are four "mild" coronaviruses, that have been circulating for a long time, but that's neglecting to mention that there is a strong bright line between the "seasonal" circulating coronaviruses and the new coronaviruses - the name that was given to nCoV-19 gives a hint to what you should be calibrating as your reference (SARS-CoV-2) - SARS and MERS, both of which have astronomical case fatality rates (10% and 40%). SARS was contained by a massive public health effort of quarantine and lockdown, MERS the same except it seems to be less transmittable.

> First, it was discovered in late December, probably jumping to humans in November

The most recent phylogenetic analysis on 7000+ viral sequences from isolates points at the end of October as a possible date.

I don't think for most people dying is the scary outcome, like you say it's very very unlikely for a healthy young person.

But what is the odds that you survive but then require kidney transplant or lung transplant or have leave ICU only to face weeks or months of recovery. This latter bit is a unknown to me, so I don't know what my actual risk is.

Close to 0, if you're reasonably healthy.

> only to face weeks or months of recovery.

FTR, this also happens with other respiratory diseases. You can also take quite a bit of time (months) to fully recover from "regular" pneumonia.

Which is still really bad! Especially when wearing a mask may prevent spread by 70%. Just because other diseases are also bad is not reason to shirk personal safety and protection. I don't want the flu same as I don't want COVID.

I didn't want to downplay the fact that it can be bad. What I meant to say is that this is a respiratory disease virus, and a lot of the stuff it is supposed to cause (according to the press) is actually due to that, not because it is novel.

Even the reported brain infections (neural invasion) aren't a unique feature of this virus, but are recorded as happening with other coronaviruses (the most common ones, not SARS or MERS).

It's called flu. Which are basically two diseases, first the bacterial infection in all the dead cells the T-cells killed. In the lung this is pneumonia. Pretty serious stuff.

Second the rampage the T-cells are doing elsewhere to fight suspected virus cells. They might attack way too many healthy cells everywhere. This is called the cykotine storm, treated with standard cykotine storm suppressors. The virus itself is doing nothing, it just causes the immunosystem to overreact.

How many deaths in terms of Libraries of Congress?

> something something car drive risk wwii bomber

This line of defense completely ignores the long term damage that we know occurs in some Covid cases, even those in young people. Pneumonia can cause long term damage too. Saying the risk (I assume of death) is less ignores the incalculable risk of life long lung damage.

Definitely it can happen.

Some time ago I have to deal with a particularly annoying disease. Thousands of healthy animals dying in mass overnight by asphyxia. A few hours before they where perfectly healthy. First asymptomatic, then mostly asymptomatic, then just a mild symptoms and then massive strike and death. Covid reminds me a lot to that time.

> The numbers are supposed to be huge yet hospitals are nearly empty

Oh? Our local hospital recently had to take overflow from a neighboring county.

It depends on where you live of course. Some countries seem to have the spread of the virus well under control. Others don't.

I live in Netherland; at the height of the crisis here, Germany has to take some of our ICU cases. Now we regularly have days without any COVID-19 deaths at all, and number of cases is dropping rapidly while testing is finally increasing.

I know a lot of people who had COVID-19. I suspect I know mostly people who are healthier and young, so they don't get seriously ill.

It's the curse of the media. Infection rate might be only a few percent, death rate no more than a percent of that, but if you follow the media you get the feeling that we are in the middle of a new bubonic plague.

This is the same phenomenon that makes people to be more scared of flying than to take the car even though the latter is far more dangerous.

no one I asked knows anyone who was infected

I had this same experience early on, but now I get a reasonable hit rate asking people. I personally know about four people who had it, and probably about 10% of people I talk to know a similar number of people. More like 80% know somebody who knows somebody, but that data is less reliable.

This article is talking about several months ago, back when our testing infrastructure was severely limited. What's that got to do with now? The hospitals were absolutely overflowing back then and the daily death count was staggering. But the strict lockdowns worked and we got it under control. Now the virus is spreading rapidly again and if it continues uncontained we will end up back in that hospitals overflowing and staggering death tolls situation again in a few weeks in the worst-hit states of Arizona, South Carolina, Arkansas, Florida, Utah, and Texas.

How does this reconcile with the actual data we have on total infection rate in e.g. Spain where a representative poll was done?

Or Australia where about 10% of the population has been tested. https://www.health.gov.au/news/health-alerts/novel-coronavir...

We now know a significant amount of people have no symptoms or very light symptoms and no antibody response. An anecdote. My friend and his wife got tested when giving birth. She was positive for antibodies he was not. It is quite possible that for ever person who had antibodies there is some unknown x of people who got it and never developed antibodies.

I have seen Dr Raoult in France suggesting there was likely significant cross immunity from other coronaviruses. If it is the case, would the person develop covid19-specific antibodies after getting it?

IANAD, but you can have similar antibodies (which test positive) from previous infections with similar coronaviruses, not this one specifically.

So somebody who had no exposure to COVID-19 could test positive.

Afaik that's the main drawback of the antibody test.

The antibody test specifically tests for a protein that only exists on covid-19.

A positive test result is much more reliable than a negative result.

What is the actual effect on the world if that’s true? I’m assuming that people who were infected but never developed symptoms or antibodies were still able to infect other people who might develop symptoms and antibodies.

How would you end up without antibodies? The virus just failed to replicate in your system and died out of its own accord? Or are we suggesting the people with no symptoms are still asymptomic carriers?

You will only get detectable antibodies if the virus activated the adaptive immune system. This could be the case if the infection was successfully and quickly controlled by the innate immune system.

It doesnt mean thee are no antibodies It means the antibody test doesnt test the right protein.

People without symptoms are also much less likely to spread. So likely your friend really didn’t get infected.

How would we know that if they don't even have an antibody response? You're resorting to anecdotal evidence but there is no way to confirm this hypothesis empirically on a large scale.

I guess it depends on what you mean by "significant amount", though.

Another anecdote from NY. I had mild symptoms in mid March that didn't exactly match what was being described in the press. Spending hours at the hospital trying to get tested seemed riskier, so I was never diagnosed. In late April I got tested at Mount Sinai hospital for antibodies as part of their study and I was positive, with a high titer. A friend of mine was, too, with a low titer. In a second test two weeks ago I still had the same titer, while she was negative. As an additional anecdote, without mention of other variables, the nurse taking the second sample told me that males had a higher titer on average. I think we also have higher mortality rates, though.

It works well: from the article, "In New York, for example, the researchers’ model suggested that at least 9% of the state’s entire population was infected by the end of March. After the state conducted antibody testing on 3,000 residents, they found a 13.9% infection rate, or 2.7 million New Yorkers."

Because it's possible that there are many, many infected who don't seroconvert or ever manifest symptoms, and therefore would not have been tested with a PCR test, and would have a negative antibody test. We can see this in effect in studies of household attack rates and seroconversion. See this recent preprint and interesting thread (/r/covid19 is a strict science sub, not to be confused with /r/coronavirus) https://www.reddit.com/r/COVID19/comments/hdxwf5/intrafamili...

Excellent.

un-nerfed link: https://old.reddit.com/r/COVID19/comments/hdxwf5/intrafamili...

But does this get us a lot?

In Brooklyn and Queens between 0.2 and 0.25 percent of the total population (!) died.

So this sort of puts a floor on the IFR and 0.2 is not that far off from the IFR determined through serological testing – maybe a half or a third of that.

So yeah, maybe there is an effect – but can it really be a drastic effect? I don’t think there are orders of magnitude of difference in there, maybe a difference of a few percent (e.g. an IFR of 0.45 instead of 0.5 percent)?

My working hypothesis has been an IFR of around 0.5% for a pretty long time, which seems pretty realistic to me.

But looking at NYC now, after peaking in April, infections and deaths are way down and stabilised, in spite of rising infections in surrounding areas and very few travel restrictions. So something is going on that we don't understand, and it could have a significant impact.

If we have a higher immune population than we think, NYC might have passed the worst, if not millions will die in a second wave (though there are no signs of that yet). So this does matter.

New York obviously “benefits” from an intensive first wave. Every additional infection makes spread harder for the virus.

As many European countries show (including Germany, where the infected population is very low, much lower than the European average, much much lower than Italy or Spain) it’s very possible to keep the epidemic at a low, simmering level without extremely drastic lockdowns.

Given a probably pretty low K value it’s also often sufficient to not be super-efficient about prevention. Some efficiency goes a long way.

it’s very possible to keep the epidemic at a low, simmering level without extremely drastic lockdowns.

It's very hard to know the cause of the dramatic decline in nations that were hit hard, so I don't think we can attribute it as simply as that. It could be immunity we're unable to test (T-cell), weather meaning more are outdoors, awareness and measures like distancing and masks, or a mix of many things. We just don't know at this stage.

I'd note that Germany is still seeing outbreaks, and they were hit less hard in the initial wave in Europe. Italy in contrast, which has relaxed restrictions, is seeing very low levels of deaths and cases.

Well, this study estimates covid 19 by looking at survey data on influenza-like-illnesses. That means they were counting people who had flu-like symptoms.

Any potential people with covid19 but no symptoms would be above and beyond what’s being raised here.

Most of the people with flu like symtoms won't have had covid though.

The usual tests (including the anti-body tests) only detect the more severe cases.

This is not new data, but a re-interpretation of previously available data. With lots of assumptions. Now, if they'd gone back and analyzed samples taken in February and March with the newer tests, they'd have new data.

Anyway, all of this is about reconstructing the early days of the epidemic. With good tests now available, it's not that useful at this point.

Whats the non-COVID-19 pneumonia# for 2019-2020?

CDC Influenza and pneumonia deaths by influenza season and age: United States, 2008–2015: https://www.cdc.gov/nchs/data/health_policy/influenza-and-pn...

Even early on we had reports of some states seeing 10k+ more deaths due to pneumonia or other seasonal illness compared to prior years. Maybe the figures aren't accurate given current data, but it is worrisome:

https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm

> “The findings suggest an alternative way of thinking about the COVID-19 pandemic.

Our results suggest that the overwhelming effects of COVID-19 may have less to do with the virus’ lethality and more to do with how quickly it was able to spread through communities initially,” Silverman explained. “A lower fatality rate coupled with a higher prevalence of disease and rapid growth of regional epidemics provides an alternative explanation to the large number of deaths and overcrowding of hospitals we have seen in certain areas of the world.”

Isn't this exactly what the "flatten the curve" crowd has been saying?

yes, but the flatten the curve crowd assumes a higher lethality

Do they?

I think we have pretty ok lethality estimates somewhere in the ballpark of 0.2 to 0.5 percent.

The lethality rate without care is much higher than the lethality rate with care, and said care often needs to be exhaustive and for an extended period, which can easily fill the entire capacity of hospitals if enough people get infected at once.

Weren't doctors beginning to question whether intubation had any effect on recovery?

Not high lethality, high hospitalisation rate.

These type of studies focus on a couple of data points, ignore all others and then come up with conclusions such as these. It's impossible that the infection rate was this much less lethal as if that was the case Lombardy could not sustain the numbers it had, it would have been over 100% infected months ago.

In the article they mention that New York had 9% infection rate at the end of March. With the doubling rate they specified (3 days), New York would be fully infected by April 10th.

I argue that in Lombardia (where I live) the virus found niches of vulnerable populations (nursing care homes, hospitals like Alzano Lombardo which weren't closed after infections were found) and then proceeded to cut them down.

No, because the "flatten the curve" crowd believed that the virus was in early stages; the lockdown was to prevent uncontrolled spreading.

The virus looks super lethal when deaths are starting to pile up when only a tiny percentage of the country was believed to have been exposed. But in reality the virus had almost peaked by the time people started to panic, which made all those lockdown or flatten the curve measures pointless.

Got it thanks. This assumption is of course undermined by the fact that seroprevalence of antibodies is not that high even in countries like Sweden. At the same time I know a person who had minor symptoms, was then tested positive in PCR but negative in a later AB test. Combine this with studies on SARS1 and MERS where only half of all asymptomatic patients developed ABs and the assumption you presented seems suddenly quite possible.

If it’s true however, the pandemic should be over in a couple of weeks?

Your immune system protects against millions of diseases, but does it continuously produce antibodies for all of them? Of course not. This means that testing positive for covid19 antibodies is strong evidence that person has been infected with covid19, but the inverse is not true. That's why we don't do antibody tests for the seasonal flu: there's just no point.

Depends on what you mean by "over". Covid19 is trending down in the northern hemisphere and it will continue to trend down even after all countries stop with their ineffective lockdown measures, but the virus won't disappear completely. But life can go back to normal, except people should be a little more careful about washing their hands and not visit the elderly if they feel sick. But handwashing and consideration for the health of the vulnerable should be the default anyway, and we should do that regardless of covid.

History books will not be kind to our past and present handling of covid-19.

Incurring incredible economic and social damage without fully understanding the threat. It’s been very clear for some time that covid is not nearly as lethal as once feared AND even more clear that we over quarantined.

In the UK we have hospitals built specifically for covid that are completely unused. This isn’t flattening the curve, it’s choking it. A vaccine isn’t happening anytime soon and the only way forward is herd immunity. This means we need new infections.

You are aware that despite the world very best efforts, almost 500.000 people have already died, and in many parts of the world, its actually not slowing down, but speeding up?

These numbers would be much more useful if they were in pairs; (#people, #avg_years_lost).

https://abcnews.go.com/Health/swine-flu-h1n1-pandemic-deaths...

"Though the virus was deadly, the swine flu pandemic is still considered to have been a fairly mild one. The CDC calculates that up to 575,000 people may have died from H1N1 in 2009. The WHO estimates that the seasonal flu kills up to 500,000 people each year. Both pale in comparison to the flu pandemic of 1918, which killed an estimated 50 million people worldwide."

Sure... and then consider that, unlike swine flu or seasonal flu, COVID-19 has already killed hundreds of thousands of people even with near-total lockdowns to the point of dystopic absurdity in many countries†, has done so over the course of only a few months, and due to lackluster government response in some countries is still increasing exponentially in some places.

† See China's brief use of 'only specific designated people per apartment building are allowed to leave the building for specific designated shopping trips, under the threat of military force' policies at the worst of the peak in its cities.

You can't deduce the gravity of a threat from the state's response to it. Just consider the ~0 killed by terrorism each year in western countries vs the security theater at airports.

Terrorism isn't an infectious disease.

Your point?

That your analogy doesn't hold. We do know that infectious diseases with a median R0 of 5.7 will spread exponentially, as was the case with covid-19 in the January-March timeframe.

https://wwwnc.cdc.gov/eid/article/26/7/20-0282_article

And that means that you can deduce something about the danger of something from the reaction to it because...?

500.000 and counting WITH 'excessive' quarantine measures.

So covid-19 got to 500k, the high end of those other diseases, in 1/3rd the time and despite extreme measures to contain.

The final total for deaths due to Coronavirus is likely to be in the millions globally now, as it is spreading out of control and most countries have given up on lockdowns. Had it occurred in the conditions of 1918, it's likely millions would be dead already, but luckily we haven't just come out of a world war and healthcare is more advanced.

The one bright spot in this otherwise gloomy picture is that we don't fully understand immunity - NYC for example is seeing very low cases, despite being surrounded by plenty of infection in surrounding states and no travel lockdown - that seems to indicate heavily infected areas might escape a second wave, perhaps due to T-Cell immunity and a much higher infection rate than antibody tests would indicate. It's hard to explain the massive and continued drop in NYC otherwise after very high infection/death rates.

https://old.reddit.com/r/COVID19/comments/hdxwf5/intrafamili...

You're counting covid-19 and flu death differently.

For covid-19 you're using numbers of people who were confirmed with a test to have had covid; for flu you're looking at complex statistical modelling.

So far the best data we have shows that for people in their 60s covid-19 is killing them about ten years early.

See eg this from Economist: https://www.economist.com/graphic-detail/2020/05/02/would-mo...

https://www.gla.ac.uk/news/headline_720672_en.html

> “As most people dying with COVID-19 are older with underlying chronic conditions, some have speculated that the impact of the condition may have been overstated, and that the actual number of years of life lost as a result of COVID-19 are relatively low,” said Dr McAllister.

> “This new analysis found that death from COVID-19 results in over 10 years of life lost per person, even after taking account of the typical number and type of chronic conditions found in people dying of COVID-19. Among people dying of COVID-19, the number of years of life lost PER PERSON appear similar to diseases such as coronary heart disease. Information such as this is important to ensure governments and the public do not wrongly underestimate the effects of COVID-19 on individuals,” he added.

https://wellcomeopenresearch.org/articles/5-75

> Results: Using the standard WHO life tables, YLL per COVID-19 death was 14 for men and 12 for women. After adjustment for number and type of LTCs, the mean YLL was slightly lower, but remained high (13 and 11 years for men and women, respectively). The number and type of LTCs led to wide variability in the estimated YLL at a given age (e.g. at ≥80 years, YLL was >10 years for people with 0 LTCs, and <3 years for people with ≥6).

> Conclusions: Deaths from COVID-19 represent a substantial burden in terms of per-person YLL, more than a decade, even after adjusting for the typical number and type of LTCs found in people dying of COVID-19. The extent of multimorbidity heavily influences the estimated YLL at a given age. More comprehensive and standardised collection of data on LTCs is needed to better understand and quantify the global burden of COVID-19 and to guide policy-making and interventions.

So what this says, basically, that if comparing to the deaths and other effects from lockdowns on general population, given its age, covid deaths are to be divided by 5 or so, before even adjusting for age (I'd assume most would rather lose their 80ies than their 30ies).

Then you can consider even trivial DALY adjustments for e.g. starvation (at some point, it was expected to affect 130 million extra people, by some relevant UN body), unemployment, lack of "non essential" medical care (see estimates for excess cancer deaths from the last financial crisis due to lack of care), etc., and multiply by numbers affected.

What is speeding up, exactly? Our ability to detect marginal cases, certainly. Not the death rate.

Do you realize how many of those people would have perished this year anyway? Do you realize how many hundreds of millions of people die every year and that covid barely registers as a blip? Do you realize the enormous human cost of quarantine has to be weighed against this?

We have pretty good ideas of what normal death rates are like, and we see huge numbers of excess mortality.

> that covid barely registers as a blip?

What figures are you looking at for all cause mortality please?

This year, some 60m people will die of non-covid causes. Let's double the current 500k death toll AND presume that none of those fatalities would have occurred anyway. With covid: 61m deaths...out of 7b people.

Maybe. New Zealand took a different path and managed the problem with far fewer deaths.

America needs to secede from North America and close all airports and seaports...

For now. They will have second/third waves. We’re not going to cure this before we reach herd immunity. New Zealand just delayed the inevitable (which is what flattening the curve is all about: delay infections enough so that we can reasonably treat)

And there might not be a second/third wave. Some countries observe the virus weakening. People who would've died two months ago if they caught it are now showing milder symptoms. We have 80 year olds now who would need a ventilator two months ago recovering completely as per some doctors from Europe (Italy, Serbia).

And probably a better economic outcome.

Ha! That kinda flies in the face of facts. The UK and the US did NOT "over-quarantine" and this is precisely the problem.

Nations, even some bad-old-authoritarian ones, that didn't dilly-dally and turn the question of lockdown into a political issue, but took it as a public health issue, those are the nations that are re-opening now with low enough numbers to claim to be over the first wave.

The Tory's and GOP's treatment of a pandemia as a political football, instead of a public health menace, led to spotty lockdown actualities that precisely resulted in MORE spreading of the virus. I.E. The Wisconsin Supreme Courts decision and the immediate opening of the bars and no masks, no social distancing, etc. These are FAILED policies and the ideology behind them is incorrect.

What you are spouting might have been debatable several months ago, but I'm going to have to rub your nose in the reality that your entire set of talking points are demonstrably rubbish.

It seems to me that the Tories and GOP correctly understood that it was a political football, and their friends across the aisle would start organizing mass gatherings the instant it was politically convenient for them to do so. I certainly think there's something to be said for nations that were willing to reliably comply with pandemic control measures, and I'm very glad I live in a region of the US that did comply (even in our gun stores everyone's wearing masks!), but I don't think you can lay this at the feet of some particular political parties.

I'll just lay it at the feet of the people who stole ppe, shut down testing sites, encouraged people to drink bleach, refused to lockdown the nation, didn't implement contract tracing, didn't shut down the borders (only pretended to), didn't quarantine arrivals, and said that less testing will lead to less deaths. Interestingly all those assholes belong to the same political party.

> we have hospitals built specifically for covid that are completely unused.

Only the London nightingale went "unused", and that's because government is pursuing herd immunity by discharging older people to care and nursing homes, not to the Nightingale.

It wasn't "completely" unused.

And the other Nightingales were pretty full.

They were only full to keep other hospitals free and less contaminated. The overall additional capacity was hardly used.

I’m also saying something different: we should have quarantined to the lowest possible degree that kept the hospitals reasonably utilized. We need infections. We just don’t want to overload NHS. I’m glad we built new capacity. I’m frustrated we didn’t use it...and now a big second wave is likely.

You really need to cite sources to backup your claim regarding the other Nightingales being pretty full. I am struggling to find sources to prove they were used at all.

However, you do have an extremely valid point about what was going on with the care homes. The hospitals were vacated of 'bed blockers' at the same time as the Nightingale facilities were being built, so the old people were sent to their care homes and not to a Nightingale.

Exeter Nightingale going to open soon:

https://www.devonlive.com/news/devon-news/exeters-nightingal...

So that one has not been pretty full. It has been absolutely empty.

Bristol:

https://www.bristolpost.co.uk/news/bristol-news/bristols-nig...

Pretty Full?

Nope, just opened, no patients yet.

Moving to Wales:

https://www.bbc.co.uk/news/uk-wales-53082404

They had 17 field hospitals open up. A health economist from Swansea University said that, in hindsight, spending £166m on 46 patients was "not a good use of limited resources".

Although not technically 'Nightingale' you get the idea.

Northern Ireland?

https://www.bbc.co.uk/news/uk-northern-ireland-52651725

The Nightingale in Belfast peaked with 30 patients, before being mothballed.

I suspect that every Nightingale has a similar story.

HSJ has an article about use of the nightingales. I'm struggling to find it.

> History books will not be kind to our past and present handling of covid-19.

History has not been approving of the casual disregard for human life and probably won’t be in this case either.

For the US, I think history will judge us harshly for our overall lack of response. (We’re scaling back pretty much every response for short-sighted political reasons even as cases are starting to spike again.)

> History has not been approving of the casual disregard for human life and probably won’t be in this case either.

This is not disregard for human life. This is nature.

At this point every scientist in the world is throwing any random theory out there in the hope one sticks and they will be showered in new funding. The track record of Neil Ferguson‘s Group at Imperial is representative of this industry, however.

https://github.com/mrc-ide/covid-sim/issues/176

Don’t models assume a lack of action?

Given that an alarming model is going to alter our behaviour, it seems unrealistic to expect them to match what actually happens.

From infection date ~29.February till May the growthrate in Germany is behaving mathematically exact - following a Gompertz-Model.

It's not really clear if actions and visible behaviour changes did much - all of them came way too late - and there is no sign of a trendbreak that indicates any improvement.

And they are ignoring scientists that have already found models that actually work.

https://www.youtube.com/watch?v=8aHrx68IT7o

https://www.facebook.com/photo.php?fbid=10157283645163015

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