SVC, StorWize, FlashSystem, Spectrum Virtualize – replace a drive

I always forget, so here’s a reminder…

When you replace a drive on one of these, mdisk arrays do not auto-rebuild.

If the GUI fix procedures go away, or never show up, or whatever causes the replacement drive to not get included as a new drive in the mdisk, you can do this manually.

First, look for the candidate or spare drive you want to use.
lsmdisk

Then, make sure that drive ID is a candidate:
chdrive -use candidate 72

Then, find the missing member:
lsarraymember mdisk1

Then, set the new drive to use that missing member ID:
charraymember -member 31 -newdrive 72 mdisk1

You can watch the progress of the rebuild:
lsarraymemberprogress mdisk1


Dovecot recompress

I was getting an error about the file size being too large.

May 4 17:42:57 ns1 dovecot: imap(jdavis)<21859><XXXXXXXXX/YYYYYYYYY>: Error: Corrupted record in index cache file /home/jdavis/Maildir/.Archivedir/dovecot.index.cache: UID 1: Broken physical size in mailbox Archivedir: read(zlib(/home/jdavis/Maildir/.Archivedir/cur/1111111111.M555555P333V000000000000FD05I0001A11F_2212.mailhost,S=9794:2,SZ,Z)) failed: Cached message size larger than expected (9794 > 3254, box=Archivedir, UID=1)

I might have clobbered some things while trying to fix it, so I restored a backup to maildir.tmp, and did the following to try to repair/rebuild.

################################
### Clean up the restored mail repo
################################
cd /storage/uploads/CustomerImages/mailtemp/Maildir.tmp
for i in .[a-zA-Z]*/cur/* ; do rm cur/`basename $i` ; done

IFS=$'\n'
for i in $(find . -type f); do
   if file "$i" |grep gzip >/dev/null; then
      # echo "Extracting GZIP:" "$i" 
      mv "$i" "$i".gz
      gunzip "$i".gz
   fi
done &

for i in $(find . -type f); do
   if file "$i" |grep bzip2 >/dev/null; then
      # echo "Extracting BZIP2:" "$i"
      bunzip2 -q "$i"
      mv "$i".out "$(echo $i |sed 's/.out//')"
   fi
done &



################################
### Copy in the missing or damaged files
################################
cd /home/jdavis/Maildir
for i in .[a-zA-Z]* [a-z]* ; do rsync -avS --partial /storage/uploads/CustomerImages/mailtemp/Maildir.tmp/Maildir/"${i}" ./ ; done
for i in .[a-zA-Z]*/cur/* ; do rm cur/`basename $i` ; done

IFS=$'\n'
for i in $(find . -type f); do
   if file "$i" |grep gzip >/dev/null; then
      # echo "Extracting GZIP:" "$i" 
      mv "$i" "$i".gz
      gunzip "$i".gz
   fi
done &

for i in $(find . -type f); do
   if file "$i" |grep bzip2 >/dev/null; then
      # echo "Extracting BZIP2:" "$i"
      bunzip2 -q "$i"
      mv "$i".out "$(echo $i |sed 's/.out//')"
   fi
done &


################################
### Now, remove duplicates
################################
find /storage/uploads/CustomerImages/mailtemp/Maildir.tmp /home/jdavis/Maildir -type d -exec fdupes -dNI {} \;



################################
### Now, recompress it all
################################
compress_maildir () {
   cd $1
   DIRS=`find -maxdepth 2 -type d -name cur`
   for dir in $DIRS; do
      echo $dir
      cd $dir
      FILES=`find -type f -name “*,S=*” -not -regex “.*:2,.*Z.*”`
      #compress all files
      for FILE in $FILES; do
         NEWFILE=../tmp/${FILE}
         #echo bzip $FILE $NEWFILE
         if ! bzip2 -9 $FILE -c > $NEWFILE; then
            echo compressing failed
            exit -1;
         fi
         #reset mtime
         if ! touch -r $FILE $NEWFILE; then
            echo setting time failed
            exit -1
         fi
      done
      echo Locking $dir/..
      if PID=`/usr/lib/dovecot/maildirlock .. 120`; then
         #locking successfull, moving compressed files
         for FILE in $FILES; do
            NEWFILE=../tmp/${FILE}
            if [ -s $FILE ] && [ -s $NEWFILE ]; then
               echo mv $FILE $NEWFILE
               mv $FILE /tmp
               mv $NEWFILE ${FILE}Z
            else
               echo mv failed
               exit -1
            fi
         done
         kill $PID
      else
         echo lock failed
         exit -1
      fi
      cd – >/dev/null
   done
}


################################
### Actually RUN the script to compress all maildir files
################################
./compress_maildir /home/jdavis/Maildir/ &

Related: http://omnitech.net/news/2015/11/14/compressed-dovecot-maildir/


Light and Disinfectant

So, time to crank up the UV and disinfectants into our lungs, huh? Remember folks, if you die, the virus dies too!

TRANSCRIPT: Donald J. Trump said on 4/23/20: “Supposing we hit the body with a tremendous, whether it’s ultraviolet or just very powerful light, and, I think you said, that hasn’t been checked but you’re going to test it? And then I said, supposing you brought the light INSIDE the body, which you can do either through the skin or, uh, in some other way….and then I see the disinfectant, where it knocks it out in a minute, one minute, and is there a way we can do something like that? Uh, by injection inside, or almost a cleaning, because you see it gets in the lungs and it does a tremendous number on the lungs, so it would be interesting to check that, but you’re going to have to use medical doctors for that. But it sounds interesting to me.”

EXPLANATION: UV and disinfectants kill C19, and he was suggesting introducing those to the inside of a body may be helpful. He said Brix would be looking into that.

There is zero justification for trying to say what he suggested might be valid. It is so obviously ignorant that it is valid to dismiss it on the spot. Brix’ obvious pain on her face while having to listen to this makes perfect sense.

The suggestions are also careless for not being clear to the moderately large number of people who absolutely will interpret this to mean they should resume drinking diluted bleach.

If this kind of thing worked, then no infectious disease would ever be possible anymore. It’s like saying we should boil people to cure the disease. Sure, it would destroy the germs, but also destroy the person’s cells, aka them.

The people defending what he said are doing so out of ideological loyalty, or blind faith, or abject ignorance. Think of the Golgafrenchams and their wheel. It is not worth your time trying to get understanding into their minds. Either someone understands, or they do not.


Death Rates Falling

US death rate trends since the pandemic declaration (03-11) and national emergency (03-13).  Chart attached for various areas:
Downward Death Rates
 
The raw numbers (deaths, new infections) are:
169.49% 175.73%
122.00% 139.65%
125.82% 133.45%
135.83% 130.53%
132.37% 131.24%
127.90% 123.07%
133.43% 122.40%
128.34% 127.45%
130.77% 121.26%
128.15% 119.50%
121.77% 115.98%
120.71% 114.85%
130.05% 116.29%
122.82% 113.39%
124.57% 114.10%
119.59% 113.20%
118.63% 112.07%
114.42% 109.14%
112.10% 108.76%
117.98% 108.08%

SARS2 and Animals

This CNET Article discusses research on SARS-CoV-2 in several common animals, as well as a bit of history on the virus.  The article also discusses the animal origins of this virus, and a quick summary to date. A limited number of animals have been tested for and proven to be infected by the virus.  No proof of humans catching it back from animals has happened.  Very little study has occurred on the communicablility, and it was initially thought to be no risk.
 
The jist of the research paper is that adults and juvenile cats can get it the same as humans; young cats and ferrets can get it just in the upper respiratory tract (sinuses, tonsils), but not the lower respiratory tract. Dogs can technically get it, but are not very susceptible. It does not stay in them long. Ducks, pigs, pidgeons, etc are not susceptible at all. 
 
Another group did computer modeling of 253 animals’ ACE2 receptors to see what other animals we should investigate as possible transmission vectors.  
  • Human, Flying Fox, Horseshoe Bat, Lynx, Civet, Cat, Swine, Pangolin, Cow, Buffalo, Mustela (ferrets, weasles, etc), Goats, Sheep, ACE2 were clustered with humans.
  • Mice, birds, reptiles, etc were not, and mice were proven not susceptible.
  • Civet and Bat have been implicated in SARS1 sources, and Pangolin and Bat for SARS2 sources.

     SARS2 ACE2 Phylology Chart

This chart shows the ACE2 receptors that conserve the same binding sites as humans. They suspect that 50% and above “could” harbor the virus, but that birds generally are not a reservoir for betacoronaviruses. We see in other research that dogs, at 90%, are poor carriers, and clear the virus within 4 days. Swine were not actually susceptible, and ferrets were not able to get it into their lungs. The mechanism of those differences is unknown.

SARS2 ACE2 Phylology similarities


Ivermectin kills SARS-CoV-2 in vitro

It looks like an anti-viral drug blocks a nuclear protein import function, which halts SARS-CoV-19 replication. In cultures, a single treatment caused a 93% reduction in 24H, and 99.98% reduction at 48H.
 
It’s part of the WHO essential drugs list, and already FDA approved. That bypasses several early and time consuming steps for releasing treatments. Next steps are finding out whether this will work in humans, and what dosage is needed.
 
Somewhere in there, I hope there is a balance between keeping people safe, and killing the virus so quickly that we don’t build any immunity.
 
https://www.sciencedirect.com/science/article/pii/S0166354220302011

Cloth masks not so safe

Cloth masks increased “Influenza Like Illness” by SIX TIMES vs “standard practices” of only wearing masks sometimes, and by TWELVE TIMES vs wearing medical masks during all work shifts.  95 wards, 1600 participants, Hanoi. Cloth masks allowed infiltration of disease on 97% of the masks, vs 44% of the N95 masks. It’s expected that the moisture from exhaling is what allowed migration of contagions.
 
This goes back to the suggestion that if you *are* going to use a cloth mask, sanitize and/or replace it often throughout the day, but that procedure has not yet been tested/proven effective or not.
 

CV19 April 3

CV19 Pandemic Update for 2020-04-03

I did not make screenshots of my favorite graphs, but check out http://91-divoc.com/pages/covid-visualization/ and play with log vs normal, and etc on the interactive graphs.  Deaths and confirmations log chart is very visibly bending in the right direction. We still have a ways to go.

Executive Summary:

  • Worldwide, 1,095,917 confirmed cases and 58,787 deaths, which is within 1% of the 1-day estimate.
  • US is 275k infected, and 7382 dead, which is also within 1% of 1-day estimates.
  • China probably has ~400k unconfirmed cases, and ~16,500 unconfirmed deaths.
  • We need our confirmed and death exponents to fall to as close to 100% as possible. (vs 113% & 119% respectively).
  • US & TX confirmed exponents are stalled in the 113% range. The death date exponent has not yet fallen, averaging over 120%.
  • US deaths per confirmed case continues to increase, and will do so until as far as 47 days after the last new infection.
  • Many places in the US extended their stay-at-home plans to May 20.

1-Day Estimate for April 3
Non-China 1,018,824/56,704; Italy 120,107;14,719; USA 277,775/7,382; TX 5,900/90; ME 411/8
SD Adjusted USA 287,625/7,557; Texas 6,139/100

Actual April 3
Non-China 1,013,406/55,461; Italy 119,827/14,681; USA 275,586/7,087; TX 5,734/100; ME 432/9

1-Day Estimate for April 4
Non-China 1,103,432/61,938; Italy 124,594/15,489; USA 311,960/8,475; TX 6,486/130; ME 496/9
SD Adjusted USA 318,885/9,052; Texas 6,853/129

7-day Estimate for April 8
non-China 1,917,505/109,549; Italy 169,991/23,851; USA 745,176/25,239; Texas 15,874/306; Maine 656/26
SD Adjusted USA 707,819/21,874; Texas 14,357/317
This is falling due to our curve getting flatter. US 500k, TX 11.2k

Commentary:

Day to Day deaths are still climbing nationally. No consistent major slowing there. CA and NY/NJ/MA areas have a lot going on. It may take some time for them to dig out of this.

After lockdown, confirmed cases take 9-12 days to be affected, and deaths another 8-11 days after that. Anywhere that is overloaded will have a higher death rate, which may offset this prediction

As expected with the slow-down in spread, our mortality rate keeps climbing. 1.44%, 1.55%, 1.67%, 1.75%, 1.84%, 2.06%, 2.23%, 2.43%, 2.57%.

Inflection point for outbreaks with an R0 of 2.2 is 60% of the population becoming immune. Divide that by whatever you think our detection rate is. I think we get about 38%, so maybe 75m people in the US showing as confirmed. In other words, we are clamping down on the spread. It is not slowing due to going through the bulk of the population. If we all started mingling again tomorrow, we would see a big surge in cases 2 weeks later.

Average is 6 days to onset and 14 days from onset to death for those who do not survive. Social distancing data lags by 3-5 days. Statistics lag by 1 day. Detection lags by 9-12 days. Impact delay of social distancing on confirmations MAY BE 9 days. The correlation is fuzzy, but may be around 9 days lag.

Research for improving mortality rates could put things back to normal, but we are not there yt. Even if it is solved now, logistics of getting it deployed are not instantaneous.

Spreadsheet is updated, and downloadable here:
https://drive.google.com/file/d/1vocCN445AZyVBBLsv0kJR8ZDP9DM0UST/view

My favorite charts:
http://91-divoc.com/pages/covid-visualization/
https://www.unacast.com/covid19/social-distancing-scoreboard

Additional Data Sources:
https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data
https://github.com/COVID19Tracking/covid-tracking-data/tree/master/data
https://ourworldindata.org/covid-testing

China Underreporting Claims:
I do not think this is willful deception, so much as, they are only reporting what they can confirm. It just happens that they can confirm only a small subset of the infections prior to March.

China cremation rates, I lost the URL for the older data, but current data is here:
http://mzj.wuhan.gov.cn/tjxx/387166.jhtml
2019    Number of cremated remains    JZH014221000    56,007
It varies by about 2500 per quarter, so roughly 5k per month in Wuhan province.

The number of urns and cremations are very high, and “the funeral homes are unable to keep up.”
https://www.bloomberg.com/news/articles/2020-03-27/stacks-of-urns-in-wuhan-prompt-new-questions-of-virus-s-toll
https://english.alarabiya.net/en/features/2020/03/31/Delivery-of-5-000-urns-undermines-China-s-coronavirus-official-death-toll-Report
http://www.asianews.it/news-en/Wuhan,-endless-queues-for-ashes-of-coronavirus-dead-cast-doubts-on-numbers-49673.html

There are multiple sources indicating people who were not checked into a hospital were not counted.
Journalistic sources include
https://www.rfa.org/english/news/china/cremate-02142020105822.html
https://www.scmp.com/news/china/society/article/3050311/its-pneumonia-everybody-china-knows-about-many-deaths-will-never
https://www.who.int/bulletin/volumes/84/3/news30306/en/

I did not save teh ones from February where the WHO felt they were underestimating because they had no way to count those otuside of the hospitals. They said 4-8 times higher rates were likely.

This exclusion has been common in other countries, including Italy, Iran, etc:
https://www.wsj.com/articles/italys-coronavirus-death-toll-is-far-higher-than-reported-11585767179
https://www.space.com/iran-coronavirus-graves-satellite-images.html


But the flu…

Too much write-up to not share here, but someone had asked why we cared about COVID19 deaths right now, considering influenza had around 730k hospitalizations, and 61k deaths.
 
I’ll take a stab at it. The 730k and 62k look like preliminary estimates of the 2017-2018 flu season in the US. Flu season is October through February, or 5 months. To translate that into a hospital burden, we need to know that mean influenza hospitalization is 5.4 days. That totals 3,942,000 hospital days over what was the highest flu season in the last several years. That amounts to 17,600 hospital days per calendar day.
 
By comparison, the average COVID19 hospital days is 10 per patient, which is almost double what influenza needs. In the first three weeks of US COVID19 hospitalizations, we had a cumulative 400 hospitalizations. 10 days per hospitalization, so that’s 4000, over 21 days, so 190 hospital days per calendar day. Almost nothing. Who cares, right?
 
In the fourth week, we had 2200 additional hospitalizations. Ok, that’s something. 2200 times 10 is 22k, divided by 7 days (a generous suppression of the 7th peak day), and we get 3143 hospital days per calendar day. That’s something, but it’s still only a 5th of the flu.
 
In the fifth week, we had 17,200 additional hospitalizations. That puts us at 24,571 hospital days per calendar day. Again, generously ignoring that the last day in the week is about 4x the first day, we still are 50% over influenza’s peak highest peak week in the last 10 years.
 
We’re finishing up week 6 on Monday, April 6. On that day, we’ll have 48k cumulative hospitalizations, or 28,200 additional from the prior week. That’s 282,000 additional hospital days committed, or 16x influenza’s highest peak. Any errors in my math or assumptions simply go away at this point.  Even if I’m off by half or double, we have blown past the flu by a gargantual margin.  Also, we have not reached the peak yet for COVID19.
 
Since we do not have any sort of partial herd immunity, and because its incubation period is about 3x that of the flu, without quarantine or treatment to reduce the serious and mortal cases, this sweeps through the nation in such a way that it does not slow down until we have 60% immunity, a quarter of the nation is sick at one time, and about 9.8 million US citizens die, mostly over the course of 2 months. It’s just more than our system can handle.
 
Back to the death portion of the influenza equation, the deaths happen over a certain span, such as week 48 to 23 in 2016-2107, or 42 through 22 in 2017/2018. 2017-2018 was a particularly rough year, though 2018-2019 had a longer flu season, week 41 through week 37. 2019-2020 is not fully recorded yet, and will be muddied by COVID10 this year. Either way, flu season is about 32 weeks, with a peak of 12% of the deaths in one week. It’s pretty consistent that way.
 
That means the worst week in the worst seasonal influenza cycle in the last decade had around 1100 deaths per day for one week, and everything else is an pretty steep, inverted bell curve. COVID deaths happen around day 20, and detection happen around day 12. That means we have 8 days of latency in the statistics.
 
The simple and accurate way to look at that is to project the death rate ahead by 8 days, and that’s what you will actually have. Anything further, and you might have a big fall off of cases that you cannot see yet. Also, +1 day because the official numbers always report the next day, with the WHO posting at 4am CDT, and JHU posting at 8pm CDT, and some other stats posting at 4pm EDT.  Alternatively, you can look at today’s hospitalization cumulative counts, and that is what your death count will be in 8-9 days.  That’s just how is has aligned, and is not because all of these people die.  As things slow down, that shortcut will no longer apply.
 
Well, April 2 formal number was 1100 deaths just for that day. We have already reached the peak influenza deaths per day, and our hCOV19 infection rates are still growing by 15% per day, and death rates still growing by 20% per day. That’s compounding, like a bad payday loan. So, we look ahead 8 days, and that’s 48k deaths, with 10k on April 11. That is nine times the peak influenza deaths per day.
 
Also, the deaths and hospitalizations don’t just suddenly stop. It’s not 10k one day, and zero the next. We’re on board for at least 100k deaths this year from COVID19. That assumes we have no further flare-ups. No new outbreaks. No new hot zones. None of the hospitals overload and have their death rates go up by 2-4x… You know, like NY/NJ/MA area which is already at capacity, and planning for who to refuse service to because they simply do not have beds, equipment, and staff to handle.
 
Deserving of mention is ventilator days, but that’s about 10 days for both patient types. Influenza is about 60% death from ICU and COVID19 is about 86% death from ICU, but that doesn’t matter so much as the raw numbers above.
 
What does matter is that if we listened to everyone who said “it doesn’t matter”, or “we’re overreacting”, or “there’s nothing we can do”, or “the flu is worse”, then in about 4 weeks, we will have a single day that had as many new cases and as many new deaths as the entire influenza season combined. At that point, the naysayers would say “Oh golly, why didn’t THEY do something about this!
 
So, what’s happened is that they have done something about it. They have chosen a reaction level which skirts the edge of how many people will refuse to comply, vs how many people can die without their re-election campaigns being affected. If it were up to the medical experts, then restrictions would have happened weeks earlier.  It’s not unpredictable, nor a surprise.  We knew China was not being forthcoming.  We knew this was coming.  The naysayers simply suppressed mitigation.
 
The WHO and the CDC are not able to control disaster funds on that level, nor financial packages to help prevent everyone from losing their houses in a lockdown. They also don’t have the authority. They had to wait for the governing bodies to make those decisions, and grant additional power by delegation. Some countries were faster, and better at reacting. We see those with low infection and death rates, and they are still open for business.
 
Others, who did like us, are suffering pretty heavily right now, many of them simply unable to report how many people died from the disease, because it overwhelmed their systems. We will have to count the deaths, cremations, burials, etc. after the fact, and subtract the normal amount year to year to find the excess deaths. Not every death will be from the disease. Many will be people who could not get medical care, or supplies, or suicides from the stress.
 
A common argument is “but Italy has an older population” and a variety of other issues. Yes, they do. That accounts for why their death rate is more than double what China’s was (both went into hospital overload). In the unconstrained mode, doubling happens every 2.2 days, so that is really not a good argument.
 
Some sources for various claims above:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4603361/ – Mechanical ventilation demand estimates for an influenza pandemic
 
https://www.ncbi.nlm.nih.gov/books/NBK63484/ – Length of hospital stays for the flu
 
https://www.cdc.gov/flu/about/burden/index.html – Number of deaths per year from the flu in the US
 
https://gis.cdc.gov/GRASP/Fluview/PedFluDeath.html – pediatric mortality by week, which I’m using as a proxy for all mortality.
 
If you want to know what the healthcare community is doing to prepare for and handle the hot zones that exist now, and the ones that will sprout up over the next couple of weeks, check out this site:
https://www.elsevier.com/clinical-solutions/covid-19-toolkit
 
This site is my favorite for easy to understand visualization of the spread of the disease. A straight line 45 degrees up on a log scale means it’s not getting better, and each unit up is 10x the previous unit. Horizontal means no more spread.
http://91-divoc.com/pages/covid-visualization/
 
If you want to play with the raw data yourself, you can get daily detail reports, as well as tables showing each day in a single row for confirmed cases, and confirmed deaths. Check here for JHU’s data:
https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data
 
Similar data for testing rates, hospitalizations, ICU usage, ventillator usage, etc is here:
https://github.com/COVID19Tracking/covid-tracking-data/tree/master/data
 
Unfortunately, there is no formal estimate on how many unreported cases there are out there, but it is probably somewhere between 3x and 10x the official counts. That dilutes the relative mortality rates to somewhere around 0.2% and 1.0%, compared to influenza which is somewhere around 0.05% according to the sources above.
 
EDIT: Fixed hospital-days math, and corrected spelling/grammar.

CV19 April 2

CV19 Pandemic Update for 2020-04-02

I did not make screenshots of my favorite graphs, but their URLs are at the bottom of this post. Deaths and confirmations log chart is very visibly bending in the right direction. We still have a ways to go.

Executive Summary:

  • Worldwide, 930,725 confirmed cases and 49,661 deaths, which is within 1% of the 1-day estimate.
  • US is 243k infected, and 5926 dead, which is also within 1% of 1-day estimates.
  • China probably has ~400k unconfirmed cases, and ~16,500 unconfirmed deaths.
  • We need our confirmed and death exponents to fall to as close to 100% as possible.
  • US confirmed exponent is stalled in the 114% range. The death date exponent has not yet fallen. I think NY and CA hot zones are affecting it.
  • TX confirmed exponent is averaging in the 115% range. The death rate exponent just fell into the 1-teens for the first time.
  • US deaths per confirmed case continues to increase, and will do so until as far as 47 days after the last new infection.
  • Many places in the US extended their stay-at-home plans to May 4.

1-day Estimate for April 2
non-China 932,543/48,756; Italy 115,572/13,925; USA 241,947/5,843; Texas 4,979/81; Maine 303/5
SD Adjusted USA 256,985/5,982; Texas 5,331/83

Actual April 2
Non-China 930,725/49,661; Italy 115,242;13,915; USA 243,453/5,926; TX 5,069/77; ME 376/7

1-Day Estimate for April 3
Non-China 1,018,824/56,704; Italy 120,107;14,719; USA 277,775/7,382; TX 5,900/90; ME 411/8
SD Adjusted USA 287,625/7,557; Texas 6,139/100

7-day Estimate for April 8
non-China 1,917,505/109,549; Italy 169,991/23,851; USA 745,176/25,239; Texas 15,874/306; Maine 656/26
SD Adjusted USA 707,819/21,874; Texas 14,357/317

Commentary:

Day to Day deaths are still climbing nationally. Some states have begun slowing, but CA and NY have a lot going on. It may take some time for them to dig out of this.

After lockdown, confirmed cases take 9-12 days to be affected, and deaths another 8-11 days after that. Anywhere that is overloaded will have a higher death rate, which may offset this prediction

As expected with the slow-down in spread, our mortality rate keeps climbing. 1.44%, 1.55%, 1.67%, 1.75%, 1.84%, 2.06%, 2.23%, 243%

Inflection point for outbreaks with an R0 of 2.2 is 60% of the population becoming immune. Divide that by whatever you think our detection rate is. I think we get about 38%, so maybe 75m people in the US showing as confirmed. In other words, we are clamping down on the spread. It is not slowing due to going through the bulk of the population. If we all started mingling again tomorrow, we would see a big surge in cases 2 weeks later.

Average is 6 days to onset and 14 days from onset to death for those who do not survive. Social distancing data lags by 3-5 days. Statistics lag by 1 day. Detection lags by 9-12 days. Impact delay of social distancing on confirmations MAY BE 9 days. The correlation is a little fuzzy, but using 9 days got the estimates within 10% over 7 days.

Some good research is going on that promises to improve mortality rates, but that will probably be more for the next batch of people. Even if it is solved now, logistics of getting it deployed are not instantaneous.

Spreadsheet is updated, and downloadable here:
https://drive.google.com/file/d/1vocCN445AZyVBBLsv0kJR8ZDP9DM0UST/view

My favorite charts:
http://91-divoc.com/pages/covid-visualization/
https://www.unacast.com/covid19/social-distancing-scoreboard

Additional Data Sources:
https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data
https://github.com/COVID19Tracking/covid-tracking-data/tree/master/data
https://ourworldindata.org/covid-testing

China Underreporting Claims:
I do not think this is willful deception, so much as, they are only reporting what they can confirm. It just happens that they can confirm only a small subset of the infections prior to March.

China cremation rates, I lost the URL for the older data, but current data is here:
http://mzj.wuhan.gov.cn/tjxx/387166.jhtml
2019    Number of cremated remains    JZH014221000    56,007
It varies by about 2500 per quarter, so roughly 5k per month in Wuhan province.

The number of urns and cremations are very high, and “the funeral homes are unable to keep up.”
https://www.bloomberg.com/news/articles/2020-03-27/stacks-of-urns-in-wuhan-prompt-new-questions-of-virus-s-toll
https://english.alarabiya.net/en/features/2020/03/31/Delivery-of-5-000-urns-undermines-China-s-coronavirus-official-death-toll-Report
http://www.asianews.it/news-en/Wuhan,-endless-queues-for-ashes-of-coronavirus-dead-cast-doubts-on-numbers-49673.html

There are multiple sources indicating people who were not checked into a hospital were not counted.
Journalistic sources include
https://www.rfa.org/english/news/china/cremate-02142020105822.html
https://www.scmp.com/news/china/society/article/3050311/its-pneumonia-everybody-china-knows-about-many-deaths-will-never
https://www.who.int/bulletin/volumes/84/3/news30306/en/

I did not save teh ones from February where the WHO felt they were underestimating because they had no way to count those otuside of the hospitals. They said 4-8 times higher rates were likely.

This exclusion has been common in other countries, including Italy, Iran, etc:
https://www.wsj.com/articles/italys-coronavirus-death-toll-is-far-higher-than-reported-11585767179
https://www.space.com/iran-coronavirus-graves-satellite-images.html