Ohio Prison Death Updates [pdf] | Hacker News Reader

Ohio Prison Death Updates [pdf]

coronavirus.ohio.gov

60 pointsburgreblast56 comments

17 days ago we heard that 3,330 inmates tested positive, 96% without symptoms.

https://news.ycombinator.com/item?id=22980932

There was much speculation, but many people agreed that in 2 weeks we would have super interesting data.

It's been 17 days. We have an update from ohio.gov that tested individuals climbed to 7536, 4439 are positive (59%), total 49 deaths (.01)

Not an epidemiologist. Does this data fit the Diamond Princess model? Or more broadly, which model fits this data best?

Is there other data to show how many became symptomatic? How do we interpret this update, more than 2 weeks after initial reports?

Diamond Princess had a far higher percentage of older (over 70) people. I also would like to know if the HVAC system is as centralize in a prison as it is on a cruise ship.

HVAC is not the problem.

The problem is that prisoners routinely share common spaces. It doesn't matter how the air circulates, when they all cook, eat, work, shower, and exercise in the exact same communal rooms.

Combine that with insufficient sanitation, and it's a miracle that only half of them got sick.

Cruise ships are pretty similar in that people are eating and recreating in the same areas.

HVAC might be a problem, there was a CDC article demonstrating how A/C was attributed to specific cases in China https://wwwnc.cdc.gov/eid/article/26/7/20-0764_article

I agree that HVAC can cause spread. My point is that prison life does not allow for social distancing, and that the HVAC is irrelevant when everyone is living in essentially the same space.

I'd like to know the ages of the deceased, and if they had any other serious health issues. If the majority of the deceased are indeed old or in poor health, perhaps isolating those from the general prison population would be a prudent precautionary measure to implement.

I’ve been thinking about the asymptotic cases in situations like this and the Roosevelt. I think if folks are monitored very closely for symptoms we might learn more about how it impacts people and what percentage of cases stay asymptotic.

The number of "inmates currently Positive for COVID-19" is 1,112, not 4,439.

I think you're counting tests, not people. Those numbers double count inmates who receive multiple tests, and it's likely that those who have tested positive will receive frequent retests.

FYI there's just under 40k total inmates.

There have been other state prisons that have released prisoners that were severe cases, so as to lower their death numbers. Look for that.

> total 49 deaths (.01)

If you're going to report other ratios as percentages, could you please be consistent? I initially erroneously read this as 0.01% deaths, which would be an absolutely enormous update, but 1% isn't surprising at all.

Don't forget we can't really acquire complete mortality data until the coronavirus run their courses in infected individual.

I keep seeing reports that after an outbreak has played out about 25% of infected never show symptoms and 60% have something between a mild cold and a bad case of influenza. The remaining 15% get really sick and ~1% die.

If you just look at the stats initially you run into the problem that a lot of infected are preasymptomatic are in the early course of infection. So retrospective stats are very important.

Keep in mind this is deaths so far. This number will change as some may take more time to die. So maybe the radio could be around 1% to 2%.

What's the average number of natural/usual death, though. You have to subtract that. It might be small/none or substantial.

Just as an extra wrench in the works, an unknown number of prisoners have been released or transferred, probably after being deemed higher risk: https://www.google.com/amp/s/thehill.com/regulation/court-ba...

So death rates may still be reduced by interventions. Take care, arm chair statisticians.

> Take care, arm chair statisticians

FWIW, during this whole process, people reasonably described as “arm chair statisticians” have been putting out higher-quality and more accurate statistical analysis than any public-facing government or media source. The only high-quality analysis I’ve seen has been from “amateurs” (I.e. not employed by institutional sources of narrative information) and expensive subscription-only financial analysis services.

eh lots of people could tell ihme model was wrong/doing inappropriate curve fitting, but los alamos model for example seems pretty good to me, as an armchair statistician.

What is the size of the population of amateurs and what is the size of the population of experts? I am guessing the former is a lot bigger than the latter meaning more outcomes to pick from when retroactively trying to assign credit for accuracy.

If that’s the case, then I must have a really good selection algorithm, because the people I talk with/pay attention to are pretty uniformly good.

Any recommendations?

The best I know of:

http://www.arnoldkling.com/blog/?s=covid

https://www.arnoldkling.com/

https://marginalrevolution.com/?s=covid

https://marginalrevolution.com/about

Those are two blogs that I think everyone should subscribe to.

arnoldkling.com is particularly interesting because it seems to have unusually high quality in the comments section.

I opened the first link and went to the post exactly from a month ago to see what it said. This part was strangely fitting considering your original complaint:

>Having said all that, I am also dismayed that laymen put such pressure on epidemiologists to make forecasts. Imagine if it was your job when you see a leaf falling from a tree 40 feet overhead to place your foot on the exact spot where you “forecast” that the leaf will land.

> This part was strangely fitting considering your original complaint

I don't think I made any complaint, did I?

This forum is becoming more inexplicably unusual every day - provide objectively quality responses to a specific request, and get downvoted, with a side order of insult to boot.

Sorry, my fault. I mixed up usernames. It was a different person who was criticizing experts and then you came in to back up their point with examples of good amateur work, but you made no direct complaint.

> Sorry, my fault. I mixed up usernames.

So what if you did? What if I had made a criticism of experts, do you then downvote every other comment I make, regardless of its quality?

I would very much like to hear your justification.

EDIT: It might be a good idea for you to subscribe to the two blogs I mentioned above. It sounds like criticism of experts is something you haven't had a lot of exposure to.

I don't know what to tell you because I didn't downvote any comments in this thread. You can see comments by other people here were downvoted too, including a direct response to me and HN prevents you from downvoting direct responses. All I did was post a comment from the blog you linked that was directly relevant to the criticism in the first comment to which I was replying. I mistakenly assumed that original comment and the linked site were both from the same person and I already apologized for that mistake.

My apologies, I thought your apology occuring in close proximity to an upvote was suggestive that it had been you changing your mind. Sorry for the misunderstanding!

Thanks. It is rare to have an anonymous internet interaction in which we can both admit where we were wrong.

Can you point to any actual posts from these people on the ship’s? As I have seen a lot of horrifically bad statistics by random posters.

There was a comprehensive literature review posted on /r/coronavirus some two months ago that strong (and statistically robust in my opinion as a professional data scientist) indicating that smokers were less likely to be infected with the virus, with possible mechanisms from previous viruses like SARS and MERS.

In fact that was one of the earliest common sources to mention ACE2 receptors. A month or so later there is at least one study looking at nicotine patches as prophylactic and/or treatment for covid. I'm having trouble finding the reddit thread, standby.

What special knowledge do you think you need to interpret 5 months of COVID studies? That's almost two semesters of grad school.

You don't need a PhD to gain enough knowledge of covid from literature to speculate meaningfully on an internet forum, especially if you already have a graduate degree and practice research, as many people undoubtedly on HN do.

It sounds like you took offense to my comment which wasn't my intent. I was just making a lighthearted stats critique of someone complaining about statisticians.

That said, I think statistics is like most other skills in that you get better at it the more you do it. All things being equal, I would trust the person who has spent more time thinking about a subject.

The remark is mainly directed to the pile of comments already in this thread trying to naively divide column sums to get a death rate...

Can you please not spread the web cancer which is AMP?

https://thehill.com/regulation/court-battles/494266-judge-sa...

Valid point, but please tone down the language.

30 of the deaths are at PCI, which is basically a nursing home for older prisoners.

EDIT: “Marion houses a high number of older individuals, many who have pre-existing health conditions. Pickaway houses our long-term-care center similar to a nursing home, and Franklin is our state prison medical center.”

Marion is 25% of the deaths. Pickaway 59%. And Franklin 10%.

Then for the general population below whatever that age is (maybe 65?), you'd get roughly `(51-30)/4449 ≈ 0.47% FR` (non-PCI deaths/total positive). It's a bit unclear as it seems the numbers are changing as test results arrive. For the PCI cohort: 30/1258 ≈ 2.38% (deaths/recovered).

The 0.47% FR would seem much more plausible given the spread of the virus and the number of asymptomatic cases that appear to exist from serological testing.

You're hugely overestimating still. You seem to assume that all of the over-65s in the system are at PCI. In fact, only a small fraction of older people, even in late decades, need to be in long term medical care.

True, it's more of an upper-bounds of sort. There's several preprints from European researchers giving IFR's of 0.08% and 0.37%. So it works pretty well from a Fermi estimation method (https://what-if.xkcd.com/84/) (e.g. Bayesian inference really). Also, the age distribution in prison isn't necessarily the same as that of the general population. There's lots of limitations for a comparison to the general population but it gives some bounds.

I'd think the statistic of "average years of life lost" based on expected average of lifetime. Otherwise not sure of a better statistical way to measure age-adjusted IFR, which would be helpful.

One thing I’m curious about is the influence of people having symptoms being more likely to be tested. As others have mentioned this is only 15% of the total prison population.

I’m also curious how you could account for that if you could. Besides random sampling + tracking individuals afterwards even if they left the prison.

I’ve recently started digging more into statistics and probability theory and looking forward to learning how these biases might be factored in.

Considering they probably tested everyone so there are no unrecorded cases, a 1% death rate is pretty much in line with studies finding the CFR to be in the 0.5-1.5% neighborhood [1,2]. I would guess they are younger on average, but the prison population probably has some risk factors in terms of nutrition, insufficient Vitamin D, lack of exercise, etc.

[1] https://www.bmj.com/content/369/bmj.m1327 [2] https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v...

They tested 7541 people out of 39,082 inmates in quarantine. These numbers aren't inclusive of staff -- 556 tested positive, but how many were tested? Are staff quarantined to prevent spreading the infection out of the prisons?

The most recent information I could find says that Ohio has 48,765 inmates in total. They have quarantined 80% of prisoners and tested 15%. Their infection numbers are likely artificially low due to asymptomatic or pre-symptomatic cases.

I'd also be interested in how many have detrimental side effects from the virus, after recovery. Mostly all I see from covid numbers are black & white: died/recovered.

There was an article recently on HN that talked about the possible lasting effects of the virus[0]. I am interested to know how frequently lasting effects occur

[0] https://news.ycombinator.com/item?id=23127167

The National Geographic article from a few months ago covers the lasting effects much better.

https://www.nationalgeographic.com/science/2020/02/here-is-w...

Given all we're learning, and how fast things are happening, a couple of months ago is a long time.

I think the better report to look into will be Lompac(southern california)[1], they have the higher % of infected prisoners, I think its been roughly 70% of the prison population has tested positive for covid. Analyzing these closed systems for a true death rate seems to be the only way we will get decent data regarding mortality. I don't see govt. officials going door to door in cities asking for people to prick their finger to analyze for covid antibodies. A few things to watch out for is prisoner transfers due to extreme sickness, also getting a age distribution for the prison like others have said here, another thing to note is prison food and env. is bad on health.

[1] - https://beta.trimread.com/articles/14963

It’s an interesting question: how do you figure out whether these numbers are good or bad? Ohio has a prison population of about 44,000. So these numbers (actual plus probable) represent a death rate of 120 per 100,000. That’s ten times the death rate in Ohio as a whole. But it’s about half the death rate of NYC (actual plus probable). What’s the correct reference point? NYC seems like a reasonable reference, given that prison is an inherently high density living situation.

It's also a place where you have the power to force people to follow distancing and 'shelter in place' as long as it's not a dorm style prison. [0]

[0] Though even with those you can isolate it to particular rooms if you have the testing capacity.

While this is a small dataset of tested individuals which may be proportionally representative to larger groups, it comes at odds with releasing PII with respect to individual privacy to see potential comorbities (old age, obesity, diabetes, lack of an auto-immune response, etc). We know that people with exposure to recycled airspace and live in close proximity are more likely to transmit covid to one another. Mask wearing and social distancing are actions that will have to be obeyed by everyone as a collective in order to work-- one may never know if they're an asymptomatic super-spreader without widespread testing. Cloth masks aren't for protecting yourself as much as they are everyone around you.

Within the data itself, it shows that quarantine and isolation are effective practices against spreading covid in a hotspot. This may be a good stop-gap measure while researchers are able to study it more, but government's responsibility at all levels of keeping people safe in returning to work has has greatly fallen short of expectations.

Stab in the dark - AFAIK, Testosterone level in males in Prisons is much higher than usual (I can't back up that claim right now, but have been reading posts related to it).

Then there is this - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7185012/

just the two clicked together somehow, but might not be related after all..

This is likely just about population age distribution in prisons vs the general population.

16% of the US population is 65+, but only 2.7% in (federal) prisons. So that must account for a decent chunk of it.

https://www.bop.gov/about/statistics/statistics_inmate_age.j...

I agree that the age distribution does not match society in general, but take one thing into account, you have one group of people who have an extremely low death rate not in prison(children and teenagers) so this probably evens things out, extreme old age is not represented in prisons either, 80+ .

I've read somewhere (but don't know if it's true) that prison meals are enriched with vitamins, and in particular with vitamin D. Could someone confirm?

Also, there are fewer old prisoners than old people in the general population.

Personal experience tells me that it's most likely not true. I have seen a great deal of the food that we cooked in federal prison. I'd label the beverages like fruit juice being enriched as a "maybe".

We typically had lower quality of the same food stuffs you'd buy at the grocers. Protein/canned vegetables/"fresh" fruit/rice.

I can't see the document, but when a similar story recently popped up on here the average age of prisoners was 38.

fwiw.

edit: the previous story https://news.ycombinator.com/item?id=22941493

age stats: https://www.cleveland.com/news/erry-2018/08/84f4aab48f389/oh...

(the underlying source is not accessible to me either at the moment)

Reply on news.ycombinator.com