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Risks Digest 31.89

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May 27, 2020, 9:54:09 PM5/27/20
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RISKS-LIST: Risks-Forum Digest Wednesday 27 May 2020 Volume 31 : Issue 89

ACM FORUM ON RISKS TO THE PUBLIC IN COMPUTERS AND RELATED SYSTEMS (comp.risks)
Peter G. Neumann, founder and still moderator

***** See last item for further information, disclaimers, caveats, etc. *****
This issue is archived at <http://www.risks.org> as
<http://catless.ncl.ac.uk/Risks/31.89>
The current issue can also be found at
<http://www.csl.sri.com/users/risko/risks.txt>

Contents:
Faulty Equipment, Lapsed Training, Repeated Warnings: How a Preventable
Disaster Killed Six Marines (Propublica)
A Case for Cooperation Between Machines and Humans (NYTimes)
COVID-19: 'Evidence Fiasco' (John P.A. Ioannidis)
The Pandemic Is Exposing the Limits of Science (Bloomberg)
COVID-19: Half of Canadians think their governments are deliberately hiding
information (CA National Post)
White House and Twitter (sundry sources)
Re: Map Reveals Distrust in Health Expertise Is Winning ... (anthony)
Re: Misinformation (Amos Shapir)
Abridged info on RISKS (comp.risks)

----------------------------------------------------------------------

Date: Wed, 27 May 2020 01:13:34 -0400
From: Gabe Goldberg <ga...@gabegold.com>
Subject: Faulty Equipment, Lapsed Training, Repeated Warnings: How a
Preventable Disaster Killed Six Marines (Propublica)

https://www.propublica.org/article/marines-hornet-squadron-242-crash-pacific-resilard

The Navy installed touch-screen steering systems to save money.

Ten sailors paid with their lives.

“Usually when we have a fault with that system,” Sanchez said, “their
resolution is to reboot the system.”

https://features.propublica.org/navy-uss-mccain-crash/navy-installed-touch-screen-steering-ten-sailors-paid-with-their-lives/
https://features.propublica.org/navy-accidents/us-navy-crashes-japan-cause-mccain/
https://features.propublica.org/navy-accidents/uss-fitzgerald-destroyer-crash-crystal/

------------------------------

Date: Wed, 27 May 2020 20:22:04 -0400
From: Gabe Goldberg <ga...@gabegold.com>
Subject: A Case for Cooperation Between Machines and Humans (NYTimes)

A computer scientist argues that the quest for fully automated robots is
misguided, perhaps even dangerous. His decades of warnings are gaining more
attention.

https://www.nytimes.com/2020/05/21/technology/ben-shneiderman-automation-humans.html

------------------------------

Date: Wed, 27 May 2020 11:15:44 -0700
From: Henry Baker <hba...@pipeline.com>
Subject: COVID-19: 'Evidence Fiasco' (John P.A. Ioannidis)

We were warned about overreaction by an actual epidemic expert.

Note the date on this article: the *same day* that Prof. Ferguson presented
his Imperial model to the UK PM Boris Johnson in person -- and the infected
Ferguson himself probably gave Boris his case of COVID-19! How ironic!
Ferguson himself a superspreader?

(You can't make this stuff up. Netflix writers please note this delicious
detail.)

https://www.statnews.com/2020/03/17/a-fiasco-in-the-making-as-the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-data/

John P.A. Ioannidis, A fiasco in the making? 17 Mar 2020
As the coronavirus pandemic takes hold, we are making decisions without
reliable data

The current coronavirus disease, Covid-19, has been called a
once-in-a-century pandemic. But it may also be a once-in-a-century evidence
fiasco.

At a time when everyone needs better information, from disease modelers and
governments to people quarantined or just social distancing, we lack
reliable evidence on how many people have been infected with SARS-CoV-2 or
who continue to become infected. Better information is needed to guide
decisions and actions of monumental significance and to monitor their
impact.

Draconian countermeasures have been adopted in many countries. If the
pandemic dissipates -- either on its own or because of these measures --
short-term extreme social distancing and lockdowns may be bearable. How
long, though, should measures like these be continued if the pandemic churns
across the globe unabated? How can policymakers tell if they are doing more
good than harm?

Vaccines or affordable treatments take many months (or even years) to
develop and test properly. Given such timelines, the consequences of
long-term lockdowns are entirely unknown.

The data collected so far on how many people are infected and how the
epidemic is evolving are utterly unreliable. Given the limited testing to
date, some deaths and probably the vast majority of infections due to
SARS-CoV-2 are being missed. We don't know if we are failing to capture
infections by a factor of three or 300. Three months after the outbreak
emerged, most countries, including the U.S., lack the ability to test a
large number of people and no countries have reliable data on the prevalence
of the virus in a representative random sample of the general population.

This evidence fiasco creates tremendous uncertainty about the risk of dying
from Covid-19. Reported case fatality rates, like the official 3.4% rate
from the World Health Organization, cause horror -- and are
meaningless. Patients who have been tested for SARS-CoV-2 are
disproportionately those with severe symptoms and bad outcomes. As most
health systems have limited testing capacity, selection bias may even worsen
in the near future.

The one situation where an entire, closed population was tested was the
Diamond Princess cruise ship and its quarantine passengers. The case
fatality rate there was 1.0%, but this was a largely elderly population, in
which the death rate from Covid-19 is much higher.

Projecting the Diamond Princess mortality rate onto the age structure of the
U.S. population, the death rate among people infected with Covid-19 would be
0.125%. But since this estimate is based on extremely thin data -- there
were just seven deaths among the 700 infected passengers and crew -- the
real death rate could stretch from five times lower (0.025%) to five times
higher (0.625%). It is also possible that some of the passengers who were
infected might die later, and that tourists may have different frequencies
of chronic diseases -- a risk factor for worse outcomes with SARS-CoV-2
infection -- than the general population. Adding these extra sources of
uncertainty, reasonable estimates for the case fatality ratio in the general
U.S. population vary from 0.05% to 1%.

That huge range markedly affects how severe the pandemic is and what should
be done. A population-wide case fatality rate of 0.05% is lower than
seasonal influenza. If that is the true rate, locking down the world with
potentially tremendous social and financial consequences may be totally
irrational. It's like an elephant being attacked by a house cat. Frustrated
and trying to avoid the cat, the elephant accidentally jumps off a cliff and
dies.

Could the Covid-19 case fatality rate be that low? No, some say, pointing to
the high rate in elderly people. However, even some so-called mild or
common-cold-type coronaviruses that have been known for decades can have
case fatality rates as high as 8% when they infect elderly people in nursing
homes. In fact, such "mild" coronaviruses infect tens of millions of people
every year, and account for 3% to 11% of those hospitalized in the U.S. with
lower respiratory infections each winter.

These "mild" coronaviruses may be implicated in several thousands of deaths
every year worldwide, though the vast majority of them are not documented
with precise testing. Instead, they are lost as noise among 60 million
deaths from various causes every year.

Although successful surveillance systems have long existed for influenza,
the disease is confirmed by a laboratory in a tiny minority of cases. In the
U.S., for example, so far this season 1,073,976 specimens have been tested
and 222,552 (20.7%) have tested positive for influenza. In the same period,
the estimated number of influenza-like illnesses is between 36,000,000 and
51,000,000, with an estimated 22,000 to 55,000 flu deaths.

Note the uncertainty about influenza-like illness deaths: a 2.5-fold range,
corresponding to tens of thousands of deaths. Every year, some of these
deaths are due to influenza and some to other viruses, like common-cold
coronaviruses.

In an autopsy series that tested for respiratory viruses in specimens from
57 elderly persons who died during the 2016 to 2017 influenza season,
influenza viruses were detected in 18% of the specimens, while any kind of
respiratory virus was found in 47%. In some people who die from viral
respiratory pathogens, more than one virus is found upon autopsy and
bacteria are often superimposed. A positive test for coronavirus does not
mean necessarily that this virus is always primarily responsible for a
patient's demise.

If we assume that case fatality rate among individuals infected by
SARS-CoV-2 is 0.3% in the general population -- a mid-range guess from my
Diamond Princess analysis -- and that 1% of the U.S. population gets
infected (about 3.3 million people), this would translate to about 10,000
deaths. This sounds like a huge number, but it is buried within the noise of
the estimate of deaths from "influenza-like illness." If we had not known
about a new virus out there, and had not checked individuals with PCR tests,
the number of total deaths due to "influenza-like illness" would not seem
unusual this year. At most, we might have casually noted that flu this
season seems to be a bit worse than average. The media coverage would have
been less than for an NBA game between the two most indifferent teams.

Some worry that the 68 deaths from Covid-19 in the U.S. as of March 16 will
increase exponentially to 680, 6,800, 68,000, 680,000 ... along with similar
catastrophic patterns around the globe. Is that a realistic scenario, or bad
science fiction? How can we tell at what point such a curve might stop?

The most valuable piece of information for answering those questions would
be to know the current prevalence of the infection in a random sample of a
population and to repeat this exercise at regular time intervals to estimate
the incidence of new infections. Sadly, that's information we don't have.

In the absence of data, prepare-for-the-worst reasoning leads to extreme
measures of social distancing and lockdowns. Unfortunately, we do not know
if these measures work. School closures, for example, may reduce
transmission rates. But they may also backfire if children socialize anyhow,
if school closure leads children to spend more time with susceptible elderly
family members, if children at home disrupt their parents ability to work,
and more. School closures may also diminish the chances of developing herd
immunity in an age group that is spared serious disease.

This has been the perspective behind the different stance of the United
Kingdom keeping schools open, at least until as I write this. In the absence
of data on the real course of the epidemic, we don't know whether this
perspective was brilliant or catastrophic.

Flattening the curve to avoid overwhelming the health system is conceptually
sound -- in theory. A visual that has become viral in media and social media
shows how flattening the curve reduces the volume of the epidemic that is
above the threshold of what the health system can handle at any moment.

Yet if the health system does become overwhelmed, the majority of the extra
deaths may not be due to coronavirus but to other common diseases and
conditions such as heart attacks, strokes, trauma, bleeding, and the like
that are not adequately treated. If the level of the epidemic does overwhelm
the health system and extreme measures have only modest effectiveness, then
flattening the curve may make things worse: Instead of being overwhelmed
during a short, acute phase, the health system will remain overwhelmed for a
more protracted period. That's another reason we need data about the exact
level of the epidemic activity.

One of the bottom lines is that we don't know how long social distancing
measures and lockdowns can be maintained without major consequences to the
economy, society, and mental health. Unpredictable evolutions may ensue,
including financial crisis, unrest, civil strife, war, and a meltdown of the
social fabric. At a minimum, we need unbiased prevalence and incidence data
for the evolving infectious load to guide decision-making.

In the most pessimistic scenario, which I do not espouse, if the new
coronavirus infects 60% of the global population and 1% of the infected
people die, that will translate into more than 40 million deaths globally,
matching the 1918 influenza pandemic.

The vast majority of this hecatomb would be people with limited life
expectancies. That's in contrast to 1918, when many young people died.

One can only hope that, much like in 1918, life will continue. Conversely,
with lockdowns of months, if not years, life largely stops, short-term and
long-term consequences are entirely unknown, and billions, not just
millions, of lives may be eventually at stake.

If we decide to jump off the cliff, we need some data to inform us about the
rationale of such an action and the chances of landing somewhere safe.

John P.A. Ioannidis is professor of medicine and professor of
epidemiology and population health, as well as professor by courtesy
of biomedical data science at Stanford University School of Medicine,
professor by courtesy of statistics at Stanford University School of
Humanities and Sciences, and co-director of the Meta-Research
Innovation Center at Stanford (METRICS) at Stanford University.

John P.A. Ioannidis <jioa...@stanford.edu> @METRICStanford

------------------------------

Date: Wed, 27 May 2020 05:11:55 -1000
From: geoff goodfellow <ge...@iconia.com>
Subject: The Pandemic Is Exposing the Limits of Science (Bloomberg)

*The financial crisis tarnished the field of economics. Will the
coronavirus do the same for medicine?*

The 2008 financial crisis led the public to discover the limits of
economics. The Covid-19 pandemic risks having the same effect on scientists
and medical doctors.

Since the start of the outbreak, citizens have struggled to get clear
answers to some basic questions. Consider masks, for example: The World
Health Organization *said
<https://www.who.int/emergencies/diseases/novel-coronavirus-2019/advice-for-public/when-and-how-to-use-masks>
*early on that there was no point in encouraging healthy people to use them,
but now most doctors agree that widespread mask-wearing is a good
idea. There was also confusion around lockdowns: In the U.K., scientists
*argued* <https://www.bbc.com/news/science-environment-51892402> for weeks
over the merits of closing businesses and keeping people at home -- a
quarrel that may have cost the country lives. And now that the outbreak is
fading in Italy, there is growing debate between the country's public health
experts and doctors over whether the virus has lost strength or remains just
as deadly.

These disputes are only natural since we are dealing with a novel
coronavirus that caught most Western health-care systems off-guard.
Meanwhile, scientists across the world have raced to share data, and a
number of companies *have ramped up work*
<https://www.bloomberg.com/features/2020-coronavirus-drug-vaccine-status/> on
a vaccine, which could be one of the fastest-developed in human history.

And yet, the pandemic has reminded us that science -- and medicine in
particular -- has limits. In a way, the last few months have resembled what
occurred in the 2008 crisis, as economists fought over the right response to
the crash. The academic community split between those who said the U.S.
government should save all large banks and those who said it should let
Lehman Brothers go bust. In Europe, the controversy centered around whether
countries should pursue austerity or run large-scale budget deficits. These
divisions, and the ensuing policy mistakes, dented economists' reputation in
the eyes of the general public. [...]

https://www.bloomberg.com/opinion/articles/2020-05-25/coronavirus-the-pandemic-is-exposing-the-limits-of-scientists
https://finance.yahoo.com/news/pandemic-exposing-limits-science-050003058.html

------------------------------

Date: Wed, 27 May 2020 05:13:55 -1000
From: geoff goodfellow <ge...@iconia.com>
Subject: COVID-19: Half of Canadians think their governments are
deliberately hiding information (CA National Post)

*Some also believe conspiracy theories about where the novel coronavirus
began*

Half of Canadians believe they're not getting the whole truth from their
governments about COVID-19, a new poll suggests, and some also believe
conspiracy theories about where the novel coronavirus began.

The most recent survey from Leger and the Association for Canadian Studies
found 50 per cent of respondents felt governments were deliberately
withholding information about the pandemic of the novel coronavirus, which
has killed thousands and ground the economy to a halt.

``It's staggering, in a period where I believe trust has never been as
high,'' said Leger vice-president Christian Bourque. [...]
https://nationalpost.com/news/canada/half-of-canadians-say-governments-are-hiding-something-about-covid-19-poll

------------------------------

Date: Wed, 27 May 2020 14:53:49 -0700
From: Lauren Weinstein <lau...@vortex.com>
Subject: White House and Twitter (sundry sources)

[I have collected several related items into one. This item is clearly
relevant in our quest for truth rather than truthiness in RISKS. PGN]

White House urges harassment, attacks on Twitter employee
https://www.engadget.com/twitter-employee-targeted-harassment-trump-fact-check-210300269.html

Twitter 'Deeply Sorry' about Trump's Morning Joe Tweets, Plans Policy 'Changes'
https://www.nationalreview.com/news/twitter-deeply-sorry-about-trumps-morning-joe-tweets-plans-new-policy-changes-to-address-things-like-this/

[OK, that's a start -- but talk and tweets are cheap. Let's see the details
of the changes and how they are enforced. -L]

Trump threatens to shut down social-media platforms after Twitter put a
fact-check warning on his false tweets
https://www.businessinsider.com/trump-threatens-shut-down-platforms-after-tweets-tagged-warning-2020-5

[... the First Amendment is specifically designed to prevent such "close
down" actions. ... L]

Apparently for the first time, Twitter flags a tweet by Trump -- this time
his false rants about mail-in ballets -- and added a "get the facts about
mail-in ballots" link on his tweet.

Trump flips out on Twitter, right after Twitter fact-checked him for the
first time (BoingBoing)
https://boingboing.net/2020/05/26/trump-flips-on-on-twitter-fact.html

------------------------------

Date: Wed, 27 May 2020 11:07:33 +0100
From: anthony <ant...@youngman.org.uk>
Subject: Re: Map Reveals Distrust in Health Expertise Is Winning ...
(Vilkaitis, RISKS-31.88)

Denying "anecdata" as I call it is also a major problem. Years ago there was
a program on Radio 4 where they said that government statistics claimed
"no-one has died from the Rubella vaccine". The program gave an example of a
boy who had had the vaccine, gone home, slipped in to a coma, and died 4
weeks later. But because government guidelines state that "if it doesn't
happen within three weeks, it's unrelated", they were adamant that it wasn't
down to the vaccine. Likewise an example given of a girl who walked in to
the doctor's surgery for the vaccine, left in a wheelchair, and never walked
again. But oh no, "it can't be the vaccine's fault".

And I have personal experience of this within my circle of friends -- a
friend's son had his childhood vaccinations, came home and started behaving
strangely. It took a week or two before they realised something really was
wrong and took him to the doctor. To cut a long story short, he had Diabetes
Insipidus, and despite it starting pretty much at the same time as his
vaccinations the doctors were adamant that the two were unrelated.

> Why are the doctors not pushing C?

Things are changing, slowly ... Aspirin is now recognised as a "must do"
first response to a heart attack. I know other people who do what you do
with vitamin C.

But it really doesn't help the cause of authority when they dismiss the
vulgate's concerns, especially when those doing the dismissing probably are
far less knowledgeable than those people who are concerned! "We know best" -
except they rarely do.

------------------------------

Date: Wed, 27 May 2020 18:26:16 +0300
From: Amos Shapir <amo...@gmail.com>
Subject: Re: Misinformation (Maziuk, RISKS-31.88)

With all due respect to Mr. Maziuk, Dr. Ladkin's point is about taking data
out of context, then misrepresenting it, e.g., using a single number of
deaths out of a model's worst case scenario, and presenting it as if that
was a prediction of what would actually happen.

The "elephant in the room" is that such misinformation is done for the
explicit purpose to denigrate scientists, insinuating that "these so-called
experts don't know what they're talking about!"

------------------------------

Date: Mon, 14 Jan 2019 11:11:11 -0800
From: RISKS-...@csl.sri.com
Subject: Abridged info on RISKS (comp.risks)

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End of RISKS-FORUM Digest 31.89
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