Medical staff say virus stigma driving Tokyo hospitals to edge of collapse
japantimes.co.jp
japantimes.co.jp
Edited to add: thanks for the posters below who pointed me at relevant articles concerning workers similarly stigmatised elsewhere. Shameful and depressing are words that spring easily to mind :-(
Daily Beast isn't a real newspaper of record, but I've seen similar articles in reputable papers: https://www.thedailybeast.com/coronavirus-nurses-face-evicti...
The Doctor Came to Save Lives. The Co-op Board Told Him to Get Lost.
To be fair this is not specific to the US e.g. in france at least one nurse was harassed into leaving (heating and hot water shut off) by their landlords, in belgium one was expelled by their co-tenants, in germany one got thrown out of a supermarket, in australia a doctor got evicted, healthcare workers got assaulted in india, …
Not sure what a solution might be.
https://www.cnbc.com/2020/03/18/coronavirus-lives-for-hours-...
E.g. If one sneezes uncovered into air with the right humidity, etc. it COULD survive for a while airborne. That's not to say merely by breathing a person's usual exhalations they could get it.
The virus is transmitted through droplets, or little bits of liquid, mostly through sneezing or coughing, Dr. Maria Van Kerkhove, head of WHO’s emerging diseases and zoonosis unit, told reporters during a virtual news conference on Monday. “When you do an aerosol-generating procedure like in a medical care facility, you have the possibility to what we call aerosolize these particles, which means they can stay in the air a little bit longer.”
https://www.cnbc.com/2020/03/18/coronavirus-lives-for-hours-...
You are aware that the virus spreads primarily through air?
Those medical workers have as much right to their place of shelter as anyone else.
This is a despicable form of NIMBYism. The people complaining expect medical professionals to save them, but don't want to treat them as equals.
I was going to mention something about housing co-op politics, but it seems that NYC co-ops are a unique beast: https://www.investopedia.com/articles/personal-finance/09011...
Either way, NYC style or regular co-ops, the politics can get pretty nasty so I'm not surprised at all...
I doubt that. Crises surface suppressed flaws (and strengths), not usually create new ones.
People who would threaten anyone with "you will be killed" for anything, got there before the crisis.
here in medellin there are several tenants in our building (estrato 4, so not uber wealthy) begging the health care workers that do live here to temporarily live elsewhere or stop working, mostly bc there are a lot of elderly people that live here and a single unavoidable set of stairs that everyone has to use.
Here in germany I have not seen it, or heard of it and rather support, but my neighbours for example would be the type, to do this as well. Fear brings out ugly sides in humans.
https://www.merkur.de/leben/karriere/angst-coronavirus-krank...
And I can understand the fear, as logically, yes, a health worker has a increased risk of infection and spreading. But it is such small minded thinking, of putting extra stress on the very people you expect to take care of you, when you finally get sick, that makes me despise those people.
So yes, everyone around a health worker need to take extra care. And if the possibility exist, for the health workers to live seperately for the crisis time, why not. If compensated adequately. But if it is not possible - and you cannot expect a mother to seperate from their family, then just make the best out of it and don't forget you are all in this together.
https://www.theguardian.com/world/2020/mar/22/nhs-paramedic-...
The same also happened to a doctor in the UK:
https://news.sky.com/story/coronavirus-nhs-doctor-evicted-fr...
And with some "journalists" relying on twitter to write their articles, it gets harder to distinct hearsay from real news.
In Montpellier, owners shutting down hot water and heating to force a nurse to move out:
https://www.la-croix.com/Sciences-et-ethique/Sante/Coronavir...
In Marseille, neighbors left an anonymous note asking to 2 sisters working as nurse and firefighter to leave the residence:
https://www.ouest-france.fr/sante/virus/coronavirus/coronavi...
https://www.cnn.com/2020/04/13/us/custody-coronavirus-er-doc...
this isn't meant to be anti-media by any measure; but we need to hold media accountable so that it can modulate future coverage appropriately.
What political connotations?
neither of those positions are reasonable, and neither will bring understanding and meaningful methods for moving forward. politics on both sides are adding so much noise that reasonable voices are getting drowned out.
this pandemic is trending toward being about 3x worse than the yearly flu. maybe it's really 5x, but it's unlikely 10x and certainly not 100x as the most panicked are fomenting over. it's also not likely less than 2x, so it's not "no worse than the flu".
that's real information that can shape our policy decisions going forward, rather than the political.
[1] https://www.zeit.de/arbeit/2020-04/intensivpflege-coronaviru...
And yet, according to medical staff, Tokyo is close to a collapse of the medical system. https://www.worldometers.info/coronavirus/country/japan/ says that there are currently over 12,000 reported cases in Japan and this doubled in the last 10 days. So it is likely to be in the 20-25k range by the end of the month. https://www.nbcnewyork.com/news/local/new-york-virus-deaths-... says that New York reported COVID-19 seems likely to underreport actual cases by a factor of 10. Which puts Japan at the 200,000-250,000. But as widespread reports say, Japan's testing has been extremely anemic. That can easily put us back in the ballpark discussed.
You know, that projection is looking reasonably close for having been made over a month ago.
It is about the stigma causing the medical professionals to quit, which will lead to lower, and hence exceeded, capacity. It helps when you read it.
Given antibody testing done in places like Vô, the NY results seem a bit of a stretch.
Hopefully Japan gets it together and starts testing properly, though.
Also, depending on how effective the detected antibodies are in fighting off the infection, we might get insight in to how much immunity people have and how long it lasts.
RT-PCR will not tell you any of that.
That said, IFRs in the 1% or less range have been projected for some time, and everyone who pays attention to the numbers knows that reported dramatically understates reality (the only debate is over how much).
The NY study, if it holds up, suggests an IFR in the 0.8-1.0% range for NYC (depending on whether or not you include the additional excess deaths), which is in the range most experts have been assuming (0.5%-1.0% has been a common range that's been tossed around). For example, the Imperial College model used 0.9% IFR as an input. Additionally, a 10x confirmed cases to actual cases ratio is in the range most experts were assuming.
The two CA studies were outliers (and, had significant and substantive critiques), and suggested an IFR as much as 10x lower than the NY study suggests. I wouldn't call those two studies as aligning with the NY study.
https://twitter.com/wfithian/status/1252692357788479488
> I have been corresponding with the authors of the well-known Santa Clara County COVID-19 preprint, and I am alarmed at their sloppy behavior. The confidence interval calculation in their preprint made demonstrable math errors - 'not' just questionable methodological choices.
..
> The errors are not debatable and can be seen in these two screenshots of the supplement: 0.0034, the standard error meant to measure uncertainty about prevalence pi, is not the square root of 0.039, and the variance of a binomial estimate of proportion depends on the sample size.
Another critique:
https://twitter.com/jjcherian/status/1251272333177880576
> Ok, so what's wrong with the confidence intervals in this preprint? Well they publish a confidence interval on the specificity of the test that runs between 98.3% and 99.9%, but only 1.5% of all the tests came back positive!
> That means that if the true specificity of the test lies somewhere close to 98.3%, nearly all of the positive results can be explained away as false positives (and we know next to nothing about the true prevalence of COVID-19 in Santa Clara County)
> They report a 95% confidence interval for the prevalence of COVID-19 in Santa Clara County that runs from 2.01% to 3.49% though! That seems oddly narrow, given that they have already shown that it is within the realm of possibility that the data collected are all false positives!
Andrew Gelman (Stats at Columbia) had a commonly shared piece: https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw...
Also a good dive into the issues: https://medium.com/@balajis/peer-review-of-covid-19-antibody...
Mercury News also had a good article covering a lot of this: https://www.mercurynews.com/2020/04/20/feud-over-stanford-co...
And yes, lots of twitter discussions from folks in the field, e.g. Natalie Dean of University of Florida https://twitter.com/nataliexdean/status/1251309217215942656 and Trevor Bedford (Fred Hutchinson) https://twitter.com/trvrb/status/1251332447691628545 and others.
"The data as reported are also consistent with infection rates of 2% or 4%. Indeed, as I wrote above, 3% seems like a plausible number. As I wrote above, “I’m not saying that the claims in the above-linked paper are wrong,” and I’m certainly not saying we should take our skepticism in their specific claims and use that as evidence in favor of a null hypothesis. I think we just need to accept some uncertainty here. The Bendavid et al. study is problematic if it is taken as strong evidence for those particular estimates, but it’s valuable if it’s considered as one piece of information that’s part of a big picture that remains uncertain. When I wrote that the authors of the article owe us all an apology, I didn’t mean they owed us an apology for doing the study, I meant they owed us an apology for avoidable errors in the statistical analysis that led to overconfident claims. But, again, let’s not make the opposite mistake of using uncertainty as a way to affirm a null hypothesis."
The twitterthink reaction to this study has been vicious, mostly based on amateur re-hashes of the Gelman critique, which even Gelman himself doesn't really believe.
When I made one in PyMC3 (which lined up with a commenter's approach with PyStan), the 97% CI for the prevalence based on the non-poststratified data I got had the prevalence between (-0.3%, 1.7%). What does that mean? The test just isn't certain enough to allow us to make any conclusions, not that the null hypothesis is correct or that we can reject the null hypothesis.
There's nothing wrong with performing the study. Indeed, the publishing of the study allows us to have these vigorous debates about methods and informs future trials from being more exact and not suffering from the same problems as previous studies. But trying to extrapolate a conclusion for something as important as COVID based on studies with extremely high uncertainty is highly irresponsible. Sometimes we have to accept that coming up with statistically significant conclusions is difficult.
Yeah, that doesn't sound substantially different than Gelman's frequentist intuition in the blog post. I'm not sure the more complex methods are adding much here, except that you can now examine the posterior, and see what portion of the density lies below zero (i.e. probably not much of it).
IMO the "CI includes zero" was weak when Gelman advanced it, because even though it's possible, it was clear from the assay error rates that the outcome was on the tails of the distribution; even if 95% of repeated samples may include zero, very few of them actually would. So at the end of the day, as you have demonstrated, you get a non-post-stratified posterior that encompasses the point estimate they gave (1.5%), but your confidence interval is different, and perhaps the mean is lower.
Now you're just left with debating the validity of the bias adjustments they made.
That said, it's wrong to frame this in terms of a "rejecting the null hypothesis". There's no hypothesis in an observational study like this.
You cannot use confidence intervals to argue the validity of a point estimate inside of the CI. When using frequentist methods, we usually have some sort of control group where we can use a paired test to compare sample means in order to reject a hypothesis.
I wanted to use Bayesian methods not because they were more complex, but because I felt that when a control group is not available, a Bayesian analysis would be a lot more obvious about surfacing uncertainty. Bayesian methods also allow us to actually simulate P(prevalence | data). And no, just because 1.5% is in the 95th percentile of the posterior prevalence, does not mean you can say that 1.5% is a valid estimate. What the CI shows is that, with 97% confidence, the prevalence is somewhere between -0.3% and 1.7%. Additionally, the mean of this posterior came out to 0.8% prevalence, which to me is good as, to me, saying it's inconclusive. In fact, if we use the median of P(prevalence | data), then we get very close to 0.8%, so this test is basically showing that the prevalence in this population is negligible.
You're using a Bayesian method, so you have a posterior distribution. You can sample from it.
"And no, just because 1.5% is in the 95th percentile of the posterior prevalence, does not mean you can say that 1.5% is a valid estimate."
You told me that was the confidence interval on the parameter. The confidence interval contains the point estimate for the original study. It's as valid as any other point within the confidence interval. As you say: "you cannot use confidence intervals to argue the validity of a point estimate inside the CI".
"What the CI shows is that, with 97% confidence, the prevalence is somewhere between -0.3% and 1.7%."
Which includes 1.5%.
> Which includes 1.5%.
And everything else in the CI. If we're treating this like a CI, then it's like saying a dice will land on 1, just because it's equally likely to land on 6.
The actual P(1.5% | prevalence) is quite low at 3%.
You just said that you can't use a CI to estimate the likelihood of any point within the CI (you actually can, for well-behaved problems, but I digress) when I commented that 0% isn't a likely outcome within the interval.
Literally the same argument. If you want to argue that 1.5% is unlikely, then you have to accept that 0% is unlikely for the same reasons.
They estimate ~27k infections on April 17th, for comparison right now for that canton the authorities declare 213 deaths (likely undercounted afaik those are only deaths at hospital) and 4726 confirmed cases.
So a lower bound of 0.7% for IFR seems reasonable (and in line with other studies)
Nitpick: it's Vò https://it.wikipedia.org/wiki/Vo%27
I used to ride my bike through there on many a Sunday when I lived in Padova.
- the NYC antibody study one you mention, done at shopping centers, indeed likely over-represents people going out. 20%-21% of that population has antibodies.
- the SARS-CoV-2 testing study with pregnant women [1], tested just before delivery. Among those, 13% tested positive. It is reasonable to expect that this study over-represents subjects that barely go out: pregnant women to go out as little as possible to protect themselves and their future baby.
Because the sampling over-representation is opposite in the two studies, the truth is likely in between. in terms of antibodies, it is likely that the pregnant women that tested positive weeks ago have now developed antibodies or will do so in the next 1-2 weeks. Among pregnant women, the 13% also ignores women that had already developed antibodies before delivery; another phenomenon that may push the truth above 13%.
The samples were done at grocery stores. Non-essential businesses are closed in New York. Most people here still have to go out to get groceries.
There is no evidence that this has led to an oversample; these are hypotheses advanced by people on reddit and HN.
Anemic is definitely a nice way to put it.
Japan is testing at a per capita rate below that of Iraq, Ukraine, Vietnam, Mongolia, Moldova and South Africa.
Their testing rate is so extraordinarily low, the US is testing more people per day than Japan has tested in total across the past four months.
Japan's low per-capita tests could be justified by saying they don't have many per-capita cases, but their test-to-positive ratio is similar to places which have been hit hard like Italy and Portugal. It should be easier for them to have a higher ratio given that they have so few cases compared to Italy
You'd have him die on his sword and achieve nothing just for the sake of appearances.
While I get your point (why hide a prediction that could have saved lives?), I think you're overly idealistic about what impact this same prediction would have had if released publicly at the time.
(I'm still a bit mystified by the purpose of the whole hash dropping thing. I don't really know what it achieves, aside from the potential to say "I knew it!" at some point in the future.)
I fear this is going to be an increasing problem if we continue to rely on the belief that medical personnel can be abused indefinitely.
We're spending $2+T on keeping everyone afloat in the US. We can spend a lot of that money encouraging everyone to pitch in to fight Covid.
We need ~hundreds of thousands of contact-tracers. If that were our only need, we could offer $1,000,000 to everyone who works as a contact tracer and have money left over.
I'm already volunteering ~70% of my time on FindTheMasks.com. I can only imagine how much more work could be done if unemployed people were given the opportunity to work on fixing the root cause of unemployment!
> We're spending $2+T on keeping everyone afloat in the US.
I think it's best to consider this as less "money to help fight the pandemic", and more as "money to save everyone from starvation", or alternatively "money to have a country to save from the pandemic".
> I'm already volunteering ~70% of my time on FindTheMasks.com.
My strong and sincere thanks for the hard work you do!
Australia is even introducing an open source app next week (like Singapore has) to automatically collect Bluetooth IDs of nearby devices as a person walks outdoors, so people can be more easily traced & notified / quarantined if they've been in contact with someone who has been infected.
Here's one of our Australian state government's explanation of contact tracing, in this case for Tuberculosis:
https://www.healthywa.wa.gov.au/Articles/A_E/Contact-tracing...
(Edit: and here's some info about the Australian and Singaporean contact tracing apps, if you haven't heard of them before)
https://www.theguardian.com/world/2020/apr/17/australias-cor...
But it isn't. $350 billion in PPP funds ran out in 10 days and only covered maybe 5-7% of businesses. $500 billion was just authorized by Congress and will run out in the same amount of time and maybe cover 10% of businesses.
Not even 20% of SMBs who need money due to the economic shutdown have received it - and this money only carries them across the finish line in a few months.
We're talking about double digit trillions of dollars to float the economy into Q3, much less the healthcare system. This is either impractical (my opinion) or we lack the political will to do it, but in either case, it is super unlikely to happen.
People with medical jobs not being able to get childcare is a serious problem, but we need dedicated separate childcare if we're going to keep the spread down.
Trying to explain away prejudice with science requires actual science.
Burakumin: "They were originally members of outcast communities in the Japanese feudal era, composed of those with occupations considered impure or tainted by death (such as executioners, undertakers, workers in slaughterhouses, butchers, or tanners), which have severe social stigmas of kegare (穢れ or "defilement") attached to them."
Add to this now "medical professionals".
In Argentina nurses and health care personnel have been abused by their neighbors. In one case, a nurse was harassed and threatened until she was forced to leave the apartment she was renting (yes, she filed a complaint with the law).
Unfortunately fear drives some people to get very nasty, even against people who could save them. Or maybe they always were nasty.
From cars getting degraded to harassment to eviction to assault and battery.
It also has a history of owning them as furniture, of killing them in many manners, of breaking treaties with them, of hanging them as town event, of not treating them, of banning them from states, cities, neighborhoods, of excluding them from society, public places, social benefits, … and I'm sure I'm forgetting a bunch.
I assumed not since Japan does not have “a history of confining [doctors and medical staff] to villages” So your comment could only apply to the treatment of burakumin.
> Sounds like you just want to drag a whole host of other issues into this conversation
You’re the one who made mistreatment of minorities the issue, it’s not really my problem if it also makes you uncomfortable.
They wouldn't get a pay bump by going on UI. They would get more sleep.
Only institutions (involving decision making by multiple humans) can help in these circumstances, because we need each other.
[0] https://www.pri.org/stories/2017-04-25/japans-evaporated-peo...
[1] https://www.businessinsider.com/evaporated-people-disappeari...
[2] https://www.theatlantic.com/business/archive/2017/09/japan-i...