Coronavirus Statistical Games

Robert Stacy McCain writes at the Spectator Coronavirus: Statistical Stupidity Excerpts in italics with my bolds and images.

Why were “smart” people so wrong about this pandemic?

Two weeks ago, Dr. Deborah Birx warned against doomsday predictions that millions of Americans might die from coronavirus. At a White House press briefing on March 25, the coordinator of President Trump’s task force condemned media speculation based on claims that as much as half the country’s population might become infected with COVID-19. “I think the numbers that have been put out there are actually very frightening to people,” said Birx, adding that reported rates of infection in China, where the virus originated, were “nowhere close to the numbers that you see people putting out there. I think it has frightened the American people.”

Birx did not name MSNBC personality Chris Hayes, although he was one of the worst scaremongers in the media mob. On his March 23 program, Hayes warned that “millions of lives are on the line” if the economic lockdown response to the virus was not extended indefinitely: “There is no option to just let everyone go back out and go back to normal if a pandemic rages across the country and infects 50 percent of the population and kills a percentage point at the low end of those infected and also melts down all the hospitals.” Applying simple arithmetic to that sentence — treating it like one of those word problems we learned to do in middle-school math class — we find that 50 percent of the U.S. population is more than 160 million people infected with COVID-19. If just 1 percent of those infected died from the virus, that would mean a death toll of at least 1.6 million.

The word “if” signifies a hypothetical contingency, but the way Hayes used the word implied a predictive quality to his speculation about “millions of lives” at jeopardy in a rampaging coronavirus outbreak. And who can say, really, what might have happened in some imagined alternative scenario? As it happened in real life, however, Trump decided to extend the “social distancing” policy to April 30, most Americans took the recommended precautions seriously, and there is already evidence that we have begun to “flatten the curve,” so that the final U.S. death toll of COVID-19 will likely be a mere fraction of the “millions” about which Hayes warned last month.

Chris Hayes is not stupid, and neither are the scientists whose forecasting models wildly exaggerated the trajectory of this pandemic. Smart people can be wrong, too. Monday, just hours after I called attention to the failure of these doomsday prophecies (“Coronavirus: The Wrong Numbers”), the widely cited Institute for Health Metrics and Evaluation (IHME) made headlines by revising their forecast: “Key Coronavirus Model Now Predicts Many Fewer U.S. Deaths” (New York magazine), “Dramatic Reduction in COVID-19 Disaster Projections” (National Review), and “Coronavirus Model Now Estimates Fewer U.S. Deaths” (U.S. News & World Report), to cite a few.

Why were the original IMHE projections, first published March 26, so far off the mark? We don’t know. Perhaps the scientists underestimated the efficacy of the “mitigation” measures Trump announced March 16. Or possibly the use of chloroquine — which Trump controversially called a “game changer” — to combat the virus was more successful than any of the president’s critics are willing to admit. But the fact is, the projection models were wrong, and the gap between what was predicted and what actually happened became apparent within a matter of days. By April 1, as Justin Hart pointed out, the number of COVID-19 patients hospitalized was less than a third of the number projected by the IHME model. In their revised forecast issued Monday, IHME lowered its estimate of total U.S. coronavirus deaths by 12 percent, from 93,531 down to 81,766.

Even this revised forecast may be too pessimistic, however. At his Tuesday press conference, New York Gov. Andrew Cuomo, whose state is the epicenter of the U.S. outbreak, spoke of a “plateau” in the number of COVID-19 cases in the state’s hospitals, with about 17,500 patients currently hospitalized, about 4,600 of those in intensive-care units. This is very bad, but it is not the system-crashing catastrophe Cuomo was anticipating when, at a March 24 press conference, he angrily shouted that a shortage of ventilators would cause 26,000 unnecessary deaths in the state. While we cannot predict future events, it appears that New York now has more ventilators than will ever be needed to cope with the coronavirus outbreak — and this is good news.

Such hopeful signs that we have avoided the worst-case scenarios are probably little comfort to doctors and nurses working double shifts to cope with the COVID-19 patient load in New York City and its suburbs, or in other places around the country dealing with severe local outbreaks of the virus. At Monday’s White House briefing, Birx spoke of her team’s tracking of the pandemic at a “county by county” level, citing Detroit and New Orleans as examples of the hot spots where federal authorities are helping communities cope with the problem. At a time when more than 1,000 Americans are dying daily from this disease, the good news — that the pandemic is falling short of the catastrophe previously predicted — is a matter of comparison between a reality that is still quite bad and a doomsday scenario where MSNBC viewers were told that “millions of lives” might be lost.

What was Chris Hayes doing when he hyped fears of a raging pandemic that would overwhelm the health-care system and kill 1.6 million Americans, 200 times more than the 80,000 currently projected by the IMHE model? He was blaming Trump for having failed to prevent the approaching “doom and death.” The more deaths, the more blame — that was apparently why the Greek chorus of media fear-mongers (Hayes was by no means alone in this) were so eager to promote the worst-case scenarios that did not materialize. America’s coronavirus death rate (39 per 1 million residents) is currently a fraction of the rates in several European countries, including Spain (300 per million), Italy (283 per million), France (158 per million), and Belgium (176 per million). Trump’s critics accuse our president of failing to prepare America for this crisis, but where is their criticism for the leaders of the European countries, who, as measured by statistics, failed far worse? Dead people are not statistics, of course, and many thousands of Americans are now fighting for their lives against this Chinese virus.

Oh, wait — we’re not allowed to mention where this disease came from, are we? One might hope that Chris Hayes and the other media fear-mongers would spend more time blaming the communist regime in Beijing and less time accusing our president of malicious indifference to American lives. But we should not think the media’s failures prove that they’re stupid.

They’re smart people who know exactly what they’re doing. And they should be ashamed of themselves.

See Also: Canadian Flu vs. Kung Flu

A Lesson in Mortality

Coronavirus Infographics

Daily Disease Deaths 23032020

H/T Vaughn Pratt for pointing to this graphic providing context for the current pandemic.

Update March 23: CV updates and Additional slides at end

For each COVID-19 death per average day, 105 people die of worse diseases as measured by average daily death rate.

This is the 9th graphic in the Covid 19 Coronavirus Infographic Datapack at Information is Beautiful.

The final graphic is this one:Covid19 media mentions

Update March 23:  Since so much concern is driven by the death statistics, bear these facts in mind:

CV19 mild screen

 

CV19 Conditions

CV19 Conditions +Risk

Update March 29. 2020

Roger Kimball quotes Dr. John Lee regarding the implications of the above charts in his article It’s Not a Choice Between Lives or the Economy

Finally, a word about the difference between “from” and “with.” Over the past few weeks, I have been predicting a modest fatality rate from COVID-19. I began by predicting no more than a couple of hundred deaths and then upped my prediction to a 1,000-1,200. As of today, the number of deaths attributed to the virus is just over 2,000. So I was wrong about that.

Or was I? It is one thing to die from the effects of the coronavirus, quite another to die with the virus. Let’s say you are 87 years old, diabetic, with congestive heart failure and emphysema. You are infected with the coronavirus, get sick, and die. Did you die from it, or merely with it?

This is a point that Dr. John Lee, a retired professor of pathology in the United Kingdom, made in Spectator USA. “There is a big difference,” he writes, “between Covid-19 causing death, and Covid-19 being found in someone who died of other causes. . . . Much of the response to Covid-19 seems explained by the fact that we are watching this virus in a way that no virus has been watched before. The scenes from the Italian hospitals have been shocking, and make for grim television. But television is not science.”

First do no harm.” Dr. Lee is right to warn that the panicked response to this new virus has neglected that age-old medical advice. “Unless,” he notes, “we tighten criteria for recording death due only to the virus (as opposed to it being present in those who died from other conditions), the official figures may show a lot more deaths apparently caused by the virus than [are] actually the case. What then? How do we measure the health consequences of taking people’s lives, jobs, leisure and purpose away from them to protect them from an anticipated threat? Which causes the least harm?”

That is an excellent question. Also excellent is his concluding observation that “The moral debate is not lives vs. money. It is lives vs. lives.”

Dr. Drew: Stop the Press to Stop Coronavirus Panic

At Real Clear Politics, Coronavirus Panic Must Stop, Press Needs to Be Held Accountable for Hurting People.  Excerpts in italics with my bolds.

Dr.Drew Pinsky talks with CBS Local’s DJ Sixsmith about coronavirus: “The panic must stop. And the press, they really somehow need to be held accountable because they are hurting people.”

CBS NEWS: “So you’ve seen pandemics over the decades, how does this one compare with everything?”

DR. DREW: “A bad flu season is 80,000 dead, we’ve got about 18,000 dead from influenza this year, we have a hundred from corona. Which should you be worried about influenza or Corona? A hundred versus 18,000? It’s not a trick question. And look, everything that’s going on with the New York cleaning the subways and everyone using Clorox wipes and get your flu shot, which should be the other message, that’s good. That’s a good thing, so I have no problem with the behaviors. What I have a problem with is the panic and the fact that businesses are getting destroyed that people’s lives are being upended, not by the virus, but by the panic. The panic must stop. And the press, they really somehow need to be held accountable because they are hurting people.”

CBS NEWS: “So, where do you think the panic started? Besides the press, like what was the impetus in terms of mass hysteria?”

DR. DREW: “I saw it, there’s a footage of me on a show called The Daily Blast Live a month ago, going ‘shouldn’t we be scared about this?’ and me going ‘no, there’s gonna be as potential for panic here, shut up everybody, stop talking about it, I could see the panic brewing, and I could just see it the way the innuendo and the every opportunity for drama by the press was twisted in that direction. Let me give you an example: so the World Health Organization is out now saying the fatality rate from the virus is 3.4%, right? Every publication from the WHO says 3.4% and we expect it to fall dramatically once we understand the full extent of the illness. No one ever reports the actual statement. We go 3.4% that’s 10 times more than the, whatever five times more than the flu virus and yeah it’s gonna be a little more [than the] flu probably. Still not a bad flu season.”

CBS NEWS: “Right, we’re gonna hear about more cases, more people died.”

DR. DREW: “There are probably several people in this building that probably have it and don’t know it.”

CBS NEWS: “Right, well it was also just the process of letting the public know, the stock market, the number of tests that were available, there was so much happening, I think people were freaking out as a result of that.”

DR. DREW: “I think there was it was a concerted effort by the press to capture your eyes and in doing so they did it by inducing panic. There’s, listen, the CDC and the WHO, they know what they are doing, they contain pandemics, that’s how they know how to do it, they’re doing an amazing job.”

CBS NEWS: “What about the global implications of this because we were talking off-camera about Italy, there’s China as well, there’s some little outbreaks where you should avoid.

DR. DREW: “There are, I would look out where there flus out breaking bad to. I ended up getting the bird flu, I got H1N1 and it was horrible. It was no fun. … There’s certain things having been a physician for almost forty years, there are certain things I just know … and there’s certain things I just know by virtue of all the experience I’ve had and so when I saw this one coming, the corona, I thought I know how this is gonna go, I see kind of what it is and then I saw the excessive reaction the press, so I have to respond and then people, the weird part on social media towards me as people are angry with me, angry with me for trying to get them to see reality and calm down.”

Then there are wise words from Czech Microbiologist Dr Václava Adámková , posted at Lubos Motl’s website Reference Frame Czech microbiologist on the Covid panic  Excerpts in italics with my bolds.

Well, I would criticize them for purposefully and uselessly manipulating with the populace of the laymen. And the tone in which the news are being presented – there is one case here… Well, there’s one case here, five cases a day or eight cases a day today. It’s 8 cases. During that time, much more serious infectious diseases, viral or bacterial ones, actually kill many more people. And that’s something that is not included in the context of that information. So the announcements seem populist, one-sided, and they resemble a politician’s campaign before the elections when the politician focuses on one topic and he escalates it.

I am not quite a virologist, closer to a bacteriologist. Anyway, coronaviruses have been with us from the beginning. It is a large group of viruses that cause respiratory diseases, runny nose, cough, exceptionally diseases of the lower respiratory tract. But when we statistically test the coronaviruses every year, they cause up to 18% of respiratory infections. No one talks about it. These viruses attack all age groups, from babies to seniors. That’s how things work. Sometimes they appear along with other viruses, most often with influenza viruses. The coronaviruses have always been here, are here, and will be here. When the virus mutates, merges the genes with something, that’s how Nature and biology works. They may do whatever seems good in their context. We see it in flu, too.

I don’t really believe that the Wuhan virus differs. If we look at it from the healthcare perspective, according to symptoms – Covid is mostly about mild symptoms in the upper respiratory tract, especially among young and not immunocompromised people. And even the fatalities described in the context of this virus are compatible with the biology of this virus. Even the other coronaviruses may kill a weakened individual. But the available mortality numbers, let’s accept them, simply describe the reality. In comparison with SARS and MERS, Covid has a much lower fatality rate. Nevertheless, SARS and MERS didn’t get this much attention.

Some 3 months ago, the WHO was just warning about the infectious disease, most likely a viral and not bacterial one, that may quickly spread due to the widespread travelling. The main WHO virologist just made this speculation. It’s interesting that this has happened. It may easily spread, in theory. However, in practice, the propagation of the news occurs much more quickly than the propagation of the virus itself. It is spreading like a computer virus, not a biological virus, because the numbers of infected ones remain low. Around 80,000 Chinese is a tiny fraction of China’s 1.4 billion people. If they published how many people have flu or tuberculosis at the same moment, the numbers would be vastly higher. So I think it is like the propagation of a Trojan horse or a computer virus.

Coronavirus Data is Still Misleading

The Streetlight Effect: Looking in the light is the first reaction to a crisis, but the truth may actually be in the darkness and yet to be discovered.

Joon Yu writes at Worth Coronavirus Data Is Still Misleading. Here’s What the Latest Numbers Don’t Tell You.  Excerpts in italics with my bolds.

When the existing prevalence of a virus is high and endemic, the rise in incidence of testing can create the appearance of a rise in incidence of a virus.

Photo courtesy of Shutterstock.com

The world is caught in the vortex of the coronavirus story. So what happens from here?

I don’t know, and no one else does either. That said, my intuition—based on the temporal and spatial dispersion of the first 16 domestic cases of coronavirus serologically confirmed in the United States—is that the situation is not inconsistent with a high-prevalence virus that has been endemic in America during this flu season and is still circulating. But what happens as more and more testing kits are delivered into an existing high-prevalence setting?

Prevalence starts getting counted as incidence, and that could send people running for the hills.

Consider the following analogy. Think about prevalence as the gold that was sitting in the Sierras in early 1848, and incidence as the collection of eureka moments thereafter. Just because gold diggers discover more and more gold in the Sierras doesn’t mean gold is spreading. What is spreading is the word about gold, which attracts more gold diggers, who discover more gold, forming a self-reinforcing frenzy.

The prevalence of coronavirus, of course, is more dynamic. Unlike gold, it does spread. But also unlike gold, it disappears when a patient gets better, which we know has been happening in the vast majority of cases so far. What we don’t know is the true prevalence, and how endemic it has been this season—it could be in the millions for Americans already—because we weren’t looking for it until this particular story entered our collective consciousness in recent weeks. And now the labs are playing catch up.

But here’s the catch. A surge in testing—one that seems poised to commence after a slow rollout and criticism—will inevitably show a significant increase in serologically confirmed cases. When the existing prevalence of a virus is high and endemic, the rise in incidence of testing can create the appearance of a rise in incidence of a virus.

Nonetheless, the demand for such circumspection, or any circumspection for that matter, during the current hysteria is understandably anemic. Instead, this is that part of the horror movie where the good intentions of good actors—the companies and agencies rising to the challenge of producing testing kits at an exponentially faster rate than during the 2003 SARS panic—end up serving the interest of the antagonist (the mob) rather than the protagonist (public interest). In an environment when the increasingly unhinging mob is already competing with each other to paint the worst possible portrait of the next several weeks, the bad-news industrial-complex is about to strike gold: They will soon get to spread the word “spread.”

From there, the panic can drive itself. As more cases are serologically confirmed, perceptions of a spreading plague will spread, triggering demand for more testing, which will lead to more confirmed cases in a self-fulfilling prophecy. Such vicious cycles that promote runaway growth of fear are the anathema of a society that relies on stability, security and confidence. Feed-forward loops are the preferred algorithms of all self-expanding beasts, including cancer.

Confidence is already in short supply in some quarters.

Even basic things like numbers and definitions are being called into question. Meanwhile, people are panic selling the stock market and panic buying the remaining stock in supermarkets. Discretionary events are being cancelled in droves and handshakes are becoming an etiquette indiscretion. Adults are working from home, and kids with sniffles of any origin are being sent home from school to join them. During this “seeing-UFOs” phase of mass hysteria, everything from allergies and anxiety can start to look like the coronavirus given the fluidity of definitions and overlapping symptoms. Imagine the specter of this potentially absurd situation: The background prevalence of endemic coronavirus may be falling as the flu season fades, but the bad news bearers keep pointing to the rising incidence of test-affirmed coronavirus.

The numbers are bound to look dramatically worse in the coming days and weeks, so the worst of the panic may be ahead of us.

If all of this feels a bit like we are in the Twilight Zone, that’s because we are. What I mean is that we are already in the twilight of the flu season. If SARS CoV2 turns out to be just a Kafka-esque guest who has been among us for the 2019 to 2020 flu season, then at some point the meticulously recorded and earnestly reported “incidence growth” of coronavirus will stall and fall—thereby releasing the spellbound public from self-captivity and other forms of quarantine. Before we know it everyone will be saying, “I knew it,” and this horror story about the plague of the century could fade into a vague memory as if it never happened.

But before that happens, we should really get to the bottom of this while we are caught in the vortex of fear lest we want to be visited by unwanted sequels every two to five years. At the center of this powerful vortex is the principal agent problem that infected human civilization at its roots at the end of the kin tribe age of human social evolution. Whereas humans were once fed, informed and governed by those who had our best interest at heart (a biological algorithm known as inclusive fitness), in post-diaspora melting pots we are fed, informed and governed by those who have their own best interest at heart. Without mutual kin skin in the game to protect against self-dealing, powerful institutions began arising all over the ancient world that ruled over instead of on behalf of the people. Today’s fake news, fake foods and fake leadership culture are all catalyzed by the same underlying cause of misaligned incentives that have been derailing human sociality and befuddling revolutionaries for thousands of years. It was The Who—not to be confused with the WHO—who pointed out that the new boss is always the same as the old boss.

So what I hope happens to the story from here is that we begin addressing the first-order cause of human social dysfunctions rather than whack-a-moling its second-order symptoms. Simply put, our family values did not scale as we globalized, but virality has. The aggregate sum of everyone’s wonderful instincts to provide for family—the profit motive in today’s world—has produced the unintended externality of the principal agent problem in the post kin tribe era of human evolution. We propose a radically different path forward: by innovating new forms of inclusive stakeholding beyond just kin skin in the game—to align institutions with the people and people with each other—competition and natural inclinations will select for race-to-the-top global outcomes rather than race-to-the-bottom ones.

That’s a self-reinforcing trend I can get behind.

Joon Yun, MD, is the president of Palo Alto Investors and coauthor of the book Essays on Inclusive Stakeholding.

Footnote: Facts on the 2003 Global SARS Outbreak (Source: CDC)

How many people contracted SARS worldwide during the 2003 outbreak? How many people died of SARS worldwide?
During November 2002 through July 2003, a total of 8,098 people worldwide became sick with severe acute respiratory syndrome that was accompanied by either pneumonia or respiratory distress syndrome (probable cases), according to the World Health Organization (WHO). Of these, 774 died. By late July 2003, no new cases were being reported, and WHO declared the global outbreak to be over. For more information on the global SARS outbreak of 2003, visit WHO’s SARS websiteExternal.

How many people contracted SARS in the United States during the 2003 outbreak? How many people died of SARS in the United States?
In the United States, only eight persons were laboratory-confirmed as SARS cases. There were no SARS-related deaths in the United States. All of the eight persons with laboratory-confirmed SARS had traveled to areas where SARS-CoV transmission was occurring.

 

 

 

 

 

 

 

 

Coronavirus 101

The best overview I have seen comes from Rud Istvan at Wuhan Coronavirus–a WUWT Scientific Commentary  Excerpts in italics with my bolds

Basic Virology

What follows perhaps oversimplifies an unavoidably complex topic, like sea level rise or atmospheric feedbacks to CO2 in climate science.

There are three main types of human infectious microorganisms: bacteria, fungi, and viruses. (I skip important complicating stuff like malaria or giardia.) Most human bacteria are helpful; the best example is the vast gut biome. In human disease some bacteria (typhoid, plague, tetanus, gangrene, sepsis, strep) and certain classes of fungi (candida yeasts) can cause serious disease, as do some human viruses (polio, smallpox, measles, yellow fever, Zika, Ebola).

There are two basic forms of bacteria (Prokaryotes and Archaea, neither having a genetic cell nucleus). Methanogens are exclusively Archaean; most methanotrophs are Prokaryotes. Membrane bound photosynthetic organelle containing cyanobacteria are the evolutionary transition from bacteria to all Eukaryotes (cells having a separate membrane bound genetic nucleus) like phytoplankton, fungi, and us. Both Prokaryote and Eukaryote single cell (and all higher) life forms have a basic thing in common—they can reproduce by themselves in an appropriate environment.

Viruses are none of the above. They are not ‘alive’; they are genetic parasites. They can only reproduce by infecting a living cell that can already reproduce itself. The ‘nonliving’ viral genetic machinery hijacks the reproductive machinery of a living host cell and uses it to replicate virions (individual virus particles) until the host cell ‘bursts’ and the new virions bud out in search of new hosts.

There are two basic virus forms, and two basic genetics.

Form

1. Viruses are either ‘naked’ or ‘enveloped’. (see image at top).  A naked virus like cold causing rhino has just two structural components, an inner genetic whatever code (only the two basic types–DNA and RNA–are important for this comment) and an outer protective ‘capsid’ protective viral protein coat. An example is cold producing rhinovirus in the family picornavirus (which also includes polio).

2.Enveloped viruses like influenza and corona (Wuhan) include a third outer lipid membrane layer outside the capsid, studded with partly viral and partly host proteins acquired from the host cell at budding. These are used to infect the next host cell by binding to cell surface proteins. The classic example is influenza (internal genetic machinery A or B) designated HxNy for the flavor of the (H) hemagglutinin and (N) neuraminidase protein variants on the lipid membrane surface.

Genetic Type

The second major distinction is the basic genetics. Viral genetic machinery can be either RNA based or DNA based. There is a huge difference. All living cells (the viral hosts) have evolved DNA copy error machinery, but not RNA copy error machinery. That means RNA based viruses will accumulate enormous ‘transcription’ errors with each budding. As an actual virology estimate, a single rhinovirus infected mucosal cell might produce 100000 HRV virion copies before budding. But say 99% are defective unviable transcription errors. That math still says each mucosal cell infected by a single HRV virion will produce about 10 infective virions despite the severe RNA mutation problem. The practical clinical implication is that when you first ‘catch’ a HRV cold, the onset to clinical symptoms (runny nose) is very fast, usually less than 24 hours.

This also explains why adenovirus is not very infective. It is a DNA virus, so mutates slowly, so the immune memory is longer lasting. In fact, in 2011 the FDA approved (for military use only) a vaccine against adeno pharyngoconjuntivitis that was a big problem in basic training. (AKA PCF, or PC Fever, highly contagious, very debilitating, and unlike similar high fever strep throat untreatable with antibiotics.) In the first two years of mandatory PCF vaccine use, military PCF disease incidence reduced 100 fold.

Upper Respiratory Tract viral infections.

So-called URI’s have only two causes in humans: common colds, and influenza. Colds have three distinguishing symptoms–runny nose, sore throat, and cough—all caused not by the virus but by the immune system response to it. Influenza adds two more symptoms: fever and muscular ache. Physicians know this well, almost never test for the actual virus seriotype, and prescribe aspirin for flu but not colds. Much of what follows in this section is based on somewhat limited actual data, since there has been little clinical motivation to do extensive research. A climate analogy would be sea surface temperature and ocean heat content before ARGO. Are there estimates? Yes. Are there good estimates? No.

Common cold URI’s stem from three viral types: RNA rhinovirus (of which there are about 99 seriotypes but nobody knows for sure) causing about 75% of all common colds, RNA coronaviruses, for which (excluding SARS, MERS, and Wuhan) there are only 4 known human seriotypes causing about 20% of common colds, and DNA adenoviruses (about 60 human seriotypes, but including lots of non-cold symptom seriotypes like conjunctivitis (pink eye and pharyngoconjunctivitis) causing about 5% of common colds.

Available data says rhinovirus seriotypes are ubiquitous but individually not terribly infective, coronavirus seriotypes are few but VERY infective, and adenoviruses are neither. This explains, given the previous RNA mutation problem, why China and US are undertaking strict Wuhan quarantine measures.

This also explains why there is no possibility of a common cold vaccine: too many viral targets. You catch a cold, you get temporary (RNA viruses are constantly mutating) immunity to that virus. You next cold is simply a different virus, which is why the average adult has 2-4 colds per year.

A clinical sidebar about URI’s. Both are worse in winter, because people are more indoors in closer infectious proximity. But colds have much less seasonality than flus. Summer colds are common. Summer flus aren’t.

There is a differential route of transmission explanation for this empirical observation. Colds are spread primarily by contact, while flus are spread primarily by inhalation. You have a cold, you politely (as taught) cover your sneeze or cough with a hand, then open a door using its doorknob, depositing your fresh virions on it. The person behind you opens the door, picking up your virions, then touches the mouth or nose (or eyes) before washing hands. That person is now probably infected. This is also why alcohol hand sanitizers have been clinically proven ineffective against colds. They will denature enveloped corona and adeno, but have basically no effect on the by far more prevalent naked rhinos.

There is an important corollary to this contact transmission fact. Infectivity via the contact route of transmission depends on how long a virion remains infective on an inanimate surface. This depends on the virion, the surface (hard doorknob or ‘soft’ cardboard packaging), and the environment (humidity, temperature). The general epidemiological rule of thumb for common colds and flus is at most 4 days viability. This corollary is crucial for Wuhan containment, discussed below.

The main flu infection route is inhalation of infected aspirate. This does not require a cough, merely an infected person breathing in your vicinity. In winter, when you breathe out outside below freezing ‘smoke’ it is just aspirate that ‘freezes’ and becomes visible. Football aficionados see this at Soldier and Lambeau Fields every winter watching Bears and Packers games. The very fine micro-droplet residence time in the air depends on humidity. With higher humidity, they don’t dry out as fast, so remain heavier and sink faster to where they don’t get inhaled, typically minutes. In typical winter indoor low humidity, they dry rapidly and remain circulating in the air for much longer, typically hours. This is also why alcohol hand sanitizers are ineffective against influenza; the main route of flu transmission has nothing to do with hands.

[Note: The flu virus is contained in droplets that become air borne by sneezing or coughing.  Unless you inhale the air sneezed or coughed by an infected person, the main risk is direct skin contact with a surface on which the droplet landed.]

Wuhan Coronavirus

As of this writing, there are a reported 37500 confirmed infections and 811 deaths. Those numbers are about as reliable as GAST in climate change. Many people do not have access to definitive diagnostic kits; China has a habit of reporting an underlying comorbidity (emphysema, COPD, asthma) as cause of death, the now known disease progression means deaths lag diagnoses by 2-3 weeks. A climate analogy is the US surface temperature measurement problems uncovered by the WUWT Surface Stations project.

There are a number of important general facts we DO now know, which together provide directional guidance about whether anyone should be concerned or alarmed. The information is pulled from reasonably reliable sources like WHO, CDC, NIH, and JAMA or NEJM case reports. Plus, we have an inadvertent cruise ship laboratory experiment presently underway in Japan.

The incubation period is about 10-14 days until symptoms (fever, cough) evidence. That is VERY BAD news, because it has been demonstrated beyond question (Germany, Japan, US) that human to human transmission PRECEDES symptoms by about a week. So unlike SARS where all air travelers got a fever screening (mine was to and from a medical conference in Panama City). Since transmission did not precede symptoms, SARS fever screening sufficed; with Wuhan fever screening is futile. That is why all the 14-day quarantines imposed last week; the only way to quarantine Wuhan coronavirus with certainty is to wait for symptoms to appear or not. Quarantine is disruptive and expensive, but very effective.

Once symptoms appear, disease progression is now predictable from sufficient hundreds of case reports—usual corona cold progression for about 7-10 days. But then there is a bifurcation. 75-80% of patients start improving. In 20-25%, they begin a rapid decline into lower respiratory pneumonia. It is a subset of these where the deaths occur with or without ICU intervention. And as whistleblower Dr. Li’s death in Wuhan proves, ICU intervention is no panacea. He was an otherwise healthy 34 years old doctor.

We also now know from a JAMA report Friday 2/7/2020 analyzing spread of Wuhan coronavirus inside a Wuhan hospital, that 41% of patients were infected within the hospital—meaning the ubiquitous surgical masks DO NOT work as prevention. The shortage of masks is symptomatic of panic, not efficacy.

Scientists last week also traced the source. There are two clues. Wuhan is now known to be 96% genetically similar to an endemic Asian bat corona. Like SARS and ‘Spanish flu’, it jumped to humans via an intermediate mammal species. No bats were sold in the Huanan wet market in Wuhan. But pangolins were, and as of Friday there is a 99% genetic match between pangolin corona and Wuhan human corona. Trade in wild pangolins is illegal, but the meat is considered a delicacy in China and Vietnam and pangolins WERE sold in the Wuhan wet market. This is is similar to SARS in 2003. A bat corona jumped to humans via live civets in another Chinese wet market. Xi’s ‘simple’ permanent SARS/Wuhan coronavirus solution is to ban Chinese wet markets.

Conclusions

Should the world be concerned? Perhaps.

Will there be a terrible Wuhan pandemic? Probably not.

Again, the analogy to climate change alarm is striking. Alarm based on lack of underlying scientific knowledge plus unfounded worst case projections.

Proven human to human transmissibility and the likely (since proven) ineffectiveness of surgical masks were real early concerns. But the Wuhan virus will probably not become pandemic, or even endemic.

We know it can be isolated and transmission stopped with 14-day quarantine followed by symptomatic clinical isolation and ICU treatment if needed.

We know from infectivity duration on surfaces that it cannot be spread from China via ship cargo. And cargo ship crews can simply not be given shore leave until their symptomless ocean transit time plus port time passes 14 days.

Eliminating Chinese wet markets and the illegal trade in pangolins prevents another outbreak ever emerging from the wild, unfortunately unlike Ebola.

Footnote:  This is of particular interest to me since my wife and I are presently on a cruise in the Indian Ocean ending in Singapore.  We were supposed to fly from there to Shanghai connecting to Air Canada back to Montreal.  Those AC flights were cancelled for February and unlikely to be available for our transit.

Activist-Legal Complex Perverts Science

This article was published at the American Council on Science and Health Activist-Legal Complex Will Destroy American Science And Industry by Alex Berezow and Josh Bloom. Excerpts in italics with my bolds and added images.

American science and industry are under threat by this complex, known to be an unholy alliance of activists and trial lawyers who deploy various pseudoscientific tricks to score multibillion-dollar lawsuits against large companies. No industry is safe from these deceptions.

In his Farewell Address, President Eisenhower warned of the military-industrial complex, a partnership between the military and defense industry that was financially incentivized to promote war over peace. Today, we face a different threat – the “activist-legal complex,” which is responsible for scoring multibillion-dollar verdicts against some of America’s biggest companies.

One partner in this unholy alliance are activists who falsely claim that the food we eat, the water we drink, the air we breathe, and the products we use are all secretly killing us. They pervert scientific uncertainty to nefarious ends by magnifying hypothetical risks and downplaying relevant facts, such as level of exposure.

They exploit widespread misunderstanding of science and a general hatred of “corporations” – especially those that manufacture chemicals, drugs, or consumer products – to instill fear into the public.

The other partner is the legal industry, which relies on activist scaremongering to win jackpot verdicts. They identify sympathetic patients, often suffering from cancer or some other debilitating disease, and blame their maladies on a company with deep pockets. They buy television commercials to recruit more “victims” for the inevitable class-action lawsuit.

This formula works nearly every time, and the result is always the same: A giant bag of money. In this way, the activist-legal complex recently won a $4.7 billion lawsuit against Johnson & Johnson’s baby powder for causing ovarian cancer and a $2 billion lawsuit (subsequently reduced to merely $87 million) against Monsanto’s glyphosate for non-Hodgkin’s lymphoma.

There is no credible scientific evidence in support of either verdict.

But the absence of genuine scientific evidence is typically irrelevant in trials of this type. With the aid of flawed or cherry-picked toxicological and epidemiological studies – often published by activists in low-quality journals – the activist-legal complex can subvert science using well-established pseudoscientific tricks.

The first involves undermining long-held truths about toxicity. Thanks to Paracelsus, it has been known since the 16th Century that “the dose makes the poison.” Yet, the activist-legal complex promotes an alternate theory, namely that the mere presence of a chemical is an indicator of its potential harm. It is not.

Given advances in analytical instrumentation, it is now possible to detect almost any chemical in your body or in the environment at levels as minute as “one part per trillion,” which is roughly equivalent to a drop in an Olympic-sized swimming pool. There are very few, if any, chemicals on Earth that pose a health risk at such a low concentration.

But using the activist-legal complex’s doctrine – that we are constantly swimming in a sea of harmful chemicals – it is easy for lawyers to argue that any exposure to a potential carcinogen could be responsible for a cancer that develops decades later. Usually, the chemicals that are blamed have been used for decades and have been present in our bodies in tiny amounts all along without causing health concerns.

The second trick is to play on society’s belief that regulators and activists are righteous, unbiased people with no conflicts of interest. For example, jurors in the Monsanto glyphosate trial heard that the International Agency for Research on Cancer (IARC), a subsidiary of the World Health Organization, classified glyphosate as a probable human carcinogen. What they did not hear is that one of the key members of the IARC panel received £120,000 from trial lawyers who stood to benefit financially from the classification.

The third trick is to foment conspiracy theories, usually involving a few old, obscure documents or emails taken out of context. The activist-legal complex uses this tactic to convince jurors, already eager to “punish” Big Business, that the company was engaged in malfeasance.

Game, set, match. The only question left is how big the bag of money is going to be.

Where will the activist-legal complex strike next? It could be anywhere. Maybe there will be a class action lawsuit against Coca-Cola for obesity in America. Perhaps lawyers will go after Facebook for making its social media platform too addictive. Or maybe Apple’s iPhone will be blamed for causing car accidents due to distracted driving.

As long as a company has a sufficiently large bank account, quite literally anything is possible. No industry is safe from the activist-legal complex.

Postscript:

The article points to jackpot justice in general.  A number of posts here have discussed how the same dynamic is at work in Climate Litigation (link is to posts so tagged)

Nature Mag Favors Diversity Over Merit

Lubos Motl writes at his blog Reference Frame reviewing Nature Mag proclaiming top 10 Scientists for 2019.  His article is Nature’s shocking “top ten” scientists.  Excerpts below with my bolds.

Fer137 has told us about an incredible list published at Nature Nature’s 10.which is supposed to enumerate the most influential people in science of the year. As Alex correctly said, Nature basically became a new brand of toilet paper. How will they compare to Presto!?

Well, there have been numerous indications of this “evolution of purpose” of that journal but now they have jumped the shark, indeed.

As Nature openly admits, Ricardo Galvão was chosen for his being a Latin American “Amazon” activist and for his frictions with Brazil’s president, Jair Bolsonaro, whom the leftists at Nature consider politically incorrect. He clearly didn’t do anything revolutionary in the science of forests or in biology in general. In fact, he is a physicist!

Victoria Kaspi was clearly chosen for her failure to be male in a field that is overwhelmingly advanced by males, astrophysics. You should look for “fast radio bursts” at Google Scholar to become sure that she isn’t really a leader of this subfield. Even if you add CHIME, the name of her key experiment, to the query, it doesn’t become better.

Nenad Šestan was chosen for the good old left-wing “atheist” reasons. This guy works on the fuzziness of “brain death” so he can take people from God, thus proving the ill-definedness of the religious concepts including death itself. This would be a preferred scientific topic of the leftists some 20 years ago but these days, it’s no longer too hot. And incidentally, Nature just copied the name from the New York Times, a left-wing daily, that promoted Šestan in the summer. At any rate, he is one of the 3 or so actual star scientists in the list.

Sandra Díaz is a hot Venezulean model. OK, they meant this Sandra Díaz which is somewhat less pretty. She is both female and associated with the “biodiversity” hysteria. Clearly, no important advances in the “science of biodiversity” took place in the recent year or several years and she wasn’t the key in those that took place earlier.

Jean-Jacques Muyembe-Tamfum is Congolese and a racially pure black. At least, he is an actual co-discoverer of Ebola, a disease he still fights against. How important was he in the discovery of Ebola? Well, in 1976 the disease first appeared in Sudan and then in Zaire. In Zaire, Muyembe-Tamfum was just in charge of the doctors who were supposed to respond. Among other obvious things, he sent blood samples to Peter Piot. Clearly Piot was far closer to the actual discoverer of Ebola: Muyembe-Tumfum’s role is similar to that of Rosalind Franklin (or perhaps even to the unknown miner-in-chief in Jáchymov, Bohemia who sent the radium samples to Marie Sklodowska). The situations really are analogous. I am not the only one who sees it in this way. Wikipedia mentions:

In 2012, Piot published a book entitled “No Time to Lose” [see the clickable image] which chronicles his professional work, including the discovery of the Ebolavirus. He mentions Muyembe in passing rather than as a co-discoverer.

But Piot is a white man so, according to the fanatical racists at Nature, he must be censored and destroyed, right? In fact, even Piot’s claim that a passing was a passing was a heresy because the passing was black. Why would someone confuse a true scientist with someone who sent blood samples by the USPS? It’s like Penny’s discovery of a comet.

Yohannes Haile-Selassie found an old skull somewhere – one of many old skulls – but he is Ethiopian so he must automatically make it to the top ten as well, right? At least he has done some real research into the African hominids.

Wendy Rogers is both female and an activist talking about organ transplants in China; I didn’t have enough motivation to see what she says or wants because I don’t believe it’s important. Also, I wasn’t able to add a Wikipedia link because I think that her page doesn’t even exist. You may find a Republican politician and an actress of the name much more easily than this organ transplant activist. One paper with her name and “organ” has 28 citations, others are below 10. In the field focused on “organs” where she was named a member of “top ten”, she’s technically an unknown scientist according to the high energy physics criteria.

Deng Hongkui is arguably a real HIV-focused Chinese immunologist with quite some results.

John Martins leads the Google’s “quantum supremacy” advances in quantum computing. He clearly deserves to be there. Nature probably failed to notice that he is a white supremacist according to another article in Nature.Greta Thunberg… doesn’t really surprise us. She is the role model for everything that is bad about the interactions between science and the general society in 2019. She is a whining spoiled brat who refuses to go to school and who is correspondingly scientifically illiterate because of that and who, with quite some success, persuades other people that her hateful hysterical outbursts may compensate for her laziness and caution. She is the exact opposite of a young person who is close to science. Every teenager who does at least 10% of the things that Greta does should be spanked for several hours so that he cannot sit on his bottom for a week.

Nature also adds a “list whom to watch in science in 2020” that starts with António Guterres, the boss of the United Nations who completely lost his mind and who has become a little puddy of Greta Thunberg’s. Even if he weren’t a Greta’s puddy, it would be shocking to claim that being such a politically appointed bureaucrat makes one a top scientist.

At any rate, it’s terribly disappointing to see that a journal that used to be good – although it has played no role in my interest in science whatsoever – chooses way over 50% of its “best scientists” according to some extremist political or identity politics criteria. The individuals at Nature who are responsible for this outrageous page are harmful agents and should be treated as harmful agents.

Let Science Students Handle Doubt and Diversity

Jerry Ravetz writes at Nature Stop the science training that demands ‘don’t ask’. Jerry Ravetz is an associate fellow at the Institute for Science, Innovation and Society, University of Oxford, UK.Excerpts In italics with my bolds and images.

It’s time to trust students to handle doubt and diversity in science.

As a child, I realized that my parents spoke in Yiddish when they didn’t want me to know what they were talking about, so I became aware that some knowledge was intended only for grown-ups — don’t ask. In college, I was taught an elegant theory of chemical combination based on excess electrons going into holes in the orbital shell of a neighbouring atom. But what about diatomic compounds like oxygen gas? Don’t ask; students aren’t ready to know. In physics, I learnt that Newton’s second law of motion is not an empirical, approximate relation such as Boyle’s and Hooke’s laws, and instead has a universal application; but what about the science of statics, in which forces are balanced and there is no acceleration? Don’t ask. Mere students are not worthy of an answer. Yet when I was moonlighting in the social sciences and humanities, I found my questions and opinions were respected, even if only as part of my learning experience.

Observant students will notice that social problems surrounding science are seldom mentioned in official curricula. And now, these pupils are starting to act. They have shamed their seniors into including more diverse contributors as faculty members and role models. Young scholars insolently ask their superiors why they fail to address the extinction crises elucidated by their research. Such subversions are reminiscent of the mass-produced heretical pamphlets circulated by Martin Luther’s supporters at the start of the Protestant Reformation in sixteenth-century Europe.

The philosopher Thomas Kuhn once compared taught science to orthodox theology. A narrow, rigid education does not prepare anyone for the complexities of scientific research, applications and policy. If we discourage students from inquiring into the real nature of scientific truths, or exploring how society shapes the questions that researchers ask, how can we prepare them to maintain public trust in science in our ‘post-truth’ world?

Diversity and doubt produce creativity; we must make room for them, and stop funnelling future scientists into narrow specialties that value technique over thought.

In the 1990s, Silvio Funtowicz, a philosopher of science, and I developed the concept of ‘post-normal science’, building on the Kuhnian terms ‘normal’ and ‘revolutionary’ science. It outlines how to use science in a society confronted with high-stakes decisions, where both facts and values are uncertain; it requires drawing on a broad community with broad inquiries. Suppressing questions from budding scientists is sure to suppress promising ideas and solutions.

As a nonagenarian and former historian of science, I know that even foundational building blocks can be questioned. The unifying patterns of the periodic table are now seen, under closer scrutiny, to be riddled with anomalies and paradoxes (E. Scerri Nature 565, 557–559; 2019). Some scientists now wonder whether the concept of biological ‘species’ contributes more confusion than insight, and whether it should therefore be abandoned (see go.nature.com/2offaav). However, such a decision would affect conservation policy, in which identification of endangered species is crucial — so it is not just an issue for basic science.

Science students generally remain unaware that concepts such as elements and species are contested or are even contestable. In school, college and beyond, curricula highlight the technical and hide the reflective. Public arguments among scientists often presume that every problem has just one solution. When they were students, these researchers had never learnt that they have a right to be wrong.

And when scientists advise on policy, they are pressured to become attached to official stances on issues, or to shun the responsibility entirely. They then find it difficult to resist dismissing all critics as cranks or ‘denialists’, whose rejection of ‘facts’ is a sign of their depravity. (To be sure, much of science denial is cynical and self-serving.)

Nonetheless, vacillating advice on complex issues, most obviously nutrition, should be a warning that, from a future perspective, today’s total scientific consensus on some policy issue might have been the result of obduracy, a conflict of interest or worse.

Trust in established science will not be protected by exhortations, denunciations and absolutism. Just as a healthy democracy accommodates dissent and dissonance, the collective consciousness of science would do well to embrace doubt and diversity. This could start with teaching science as a great, flawed, ongoing human achievement, rather than as a collection of cut-and-dried eternal truths. There is plenty of material for such a Socratic education in science: physics and cosmology now enjoy creative ignorance; the digital and life sciences abound in moral mazes; and environmental and sustainability sciences demand recognition of complexities. The established ‘facts’ can function as tools for ongoing dialogues.

I recall a legendary chemistry professor who was inept at getting classroom demonstrations to work — but discussing what went wrong helped his students to thrive. A mathematician friend ran his classes like those in an Athenian agora: pupils discussed every statement in the textbook until all were satisfied. They did very well in exams, and taught themselves when he was absent. Treating people at all levels as committed thinkers, whose asking teaches us all, is the key to tackling the challenges to science in the post-trust age.

Footnote:  Contrast what Ravetz says with the Italian proposal to indoctrinate students with climate change dogma and activism.  Lubos Motl reports Italian schools: 33 mandatory hours of climate hysteria a year

In this week, the media have announced that starting September 2020, ten months from now, all Italian public schools will require the education in “climate science”. It was ordered by the Italian minister of education, Lorenzo Fioramonti.

If I understand well, this absolutely ludicrous new subject should be taught every year. If you spend 8 years at school and multiply it by 33 hours a year, you should be exposed to 264 hours worth of the climate science education.

This is just a breathtaking amount of time. It is very clear that the most famous person associated with the climate hysteria today, Prophet Greta Thunberg, doesn’t know even 26.4 minutes worth of climate education – assuming that the teacher doesn’t okay the idea that 27 minutes of screaming “how dare you” counts as the climate science. How can an average Italian schoolkid meaningfully learn 33 hours worth of climate science every year? It just doesn’t make the slightest sense.

Which Comes First: Story or Facts?


Facts vs Stories is written by Steven Novella at Neurologica. Excerpts in italics with my bolds.

There is a common style of journalism, that you are almost certainly very familiar with, in which the report starts with a personal story, then delves into the facts at hand often with reference to the framing story and others like it, and returns at the end to the original personal connection. This format is so common it’s a cliche, and often the desire to connect the actual new information to an emotional story takes over the reporting and undermines the facts.

This format reflects a more general phenomenon – that people are generally more interested in and influenced by a good narrative than by dry facts. Or are we? New research suggests that while the answer is still generally yes, there is some more nuance here (isn’t there always?). The researchers did three studies in which they compared the effects of strong vs weak facts presented either alone or embedded in a story. In the first two studies the information was about a fictitious new phone. The weak fact was that the phone could withstand a fall of 3 feet. The strong fact was that the phone could withstand a fall of 30 feet. What they found in both studies is that the weak fact was more persuasive when presented embedded in a story than alone, while the strong fact was less persuasive.

They then did a third study about a fictitious flu medicine, and asked subjects if they would give their e-mail address for further information. People are generally reluctant to give away their e-mail address unless it’s worth it, so this was a good test of how persuasive the information was. When a strong fact about the medicine was given alone, 34% of the participants were willing to provide their e-mail. When embedded in a story, only 18% provided their e-mail.  So, what is responsible for this reversal of the normal effect that stories are generally more persuasive than dry facts?

The authors suggest that stories may impair our ability to evaluate factual information.

This is not unreasonable, and is suggested by other research as well. To a much greater extent than you might think, cognition is a zero-sum game. When you allocate resources to one task, those resources are taken away from other mental tasks (this basic process is called “interference” by psychologists). Further, adding complexity to brain processing, even if this leads to more sophisticated analysis of information, tends to slow down the whole process. And also, parts of the brain can directly suppress the functioning of other parts of the brain. This inhibitory function is actually a critical part of how the brain works together.

Perhaps the most dramatic relevant example of this is a study I wrote about previously in which fMRI scans were used to study subjects listening to a charismatic speaker that was either from the subjects religion or not. When a charismatic speaker that matched the subject’s religion was speaking, the critical thinking part of the brain was literally suppressed. In fact this study also found opposite effects depending on context.

The contrast estimates reveal a significant increase of activity in response to the non-Christian speaker (compared to baseline) and a massive deactivation in response to the Christian speaker known for his healing powers. These results support recent observations that social categories can modulate the frontal executive network in opposite directions corresponding to the cognitive load they impose on the executive system.

So when listening to speech from a belief system we don’t already believe, we engaged our executive function. When listening to speech from within our existing belief system, we suppressed our executive function.

In regards to the current study, is something similar going on? Does processing the emotional content of stories impair our processing of factual information, which is a benefit for weak facts but actually a detriment to the persuasive power of strong facts that are persuasive on their own?

Another potential explanation occurs to me, however (showing how difficult it can be to interpret the results of psychological research like this). It is a reasonable premise that a strong fact is more persuasive on it’s own than a weak fact – being able to survive a 3 foot fall is not as impressive as a 30 foot fall. But, the more impressive fact may also trigger more skepticism. I may simply not believe that a phone could survive such a fall. If that fact, however, is presented in a straightforward fashion, it may seem somewhat credible. If it is presented as part of a story that is clearly meant to persuade me, then that might trigger more skepticism. In fact, doing so is inherently sketchy. The strong fact is impressive on its own, why are you trying to persuade me with this unnecessary personal story – unless the fact is BS.There is also research to support this hypothesis. When a documentary about a fringe topic, like UFOs, includes the claim that, “This is true,” that actually triggers more skepticism. It encourages the audience to think, “Wait a minute, is this true?” Meanwhile, including a scientists who says, “This is not true,” may actually increase belief, because the audience is impressed that the subject is being taken serious by a scientist, regardless of their ultimate conclusion. But the extent of such backfire effects remains controversial in psychological research – it appears to be very context dependent.

I would summarize all this by saying that – we can identify psychological effects that relate to belief and skepticism. However, there are many potential effects that can be triggered in different situations, and interact in often complex and unpredictable ways. So even when we identify a real effect, such as the persuasive power of stories, it doesn’t predict what will happen in every case. In fact, the net statistical effect may disappear or even reverse in certain contexts, because it is either neutralized or overwhelmed by another effect. I think that is what is happening here.

What do you do when you are trying to be persuasive, then? The answer has to be – it depends? Who is your audience? What claims or facts are you trying to get across? What is the ultimate goal of the persuasion (public service, education, political activism, marketing)? I don’t think we can generate any solid algorithm, but we do have some guiding rules of thumb.

First, know your audience, or at least those you are trying to persuade. No message will be persuasive to everyone.

If the facts are impressive on their own, let them speak for themselves. Perhaps put them into a little context, but don’t try to wrap them up in an emotional story. That may backfire.

Depending on context, your goal may be to not just provide facts, but to persuade your audience to reject a current narrative for a better one. In this case the research suggests you should both argue against the current narrative, and provide a replacement that provides an explanatory model.

So you can’t just debunk a myth, conspiracy theory, or misconception. You need to provide the audience with another way to make sense of their world.

When possible find common ground. Start with the premises that you think most reasonable people will agree with, then build from there.

Now, it’s not my goal to outline how to convince people of things that are not true, or that are subjective but in your personal interest. That’s not what this blog is about. I am only interested in persuading people to portion their belief to the logic and evidence. So I am not going to recommend ways to avoid triggering skepticism – I want to trigger skepticism. I just want it to be skepticism based on science and critical thinking, not emotional or partisan denial, nihilism, cynicism, or just being contrarian.

You also have to recognize that it can be difficult to persuade people. This is especially true if your message is constrained by facts and reality. Sometimes the real information is not optimized for emotional appeal, and it has to compete against messages that are so optimized (and are unconstrained by reality). But at least know the science about how people process information and form their beliefs is useful.

Postscript:  Hans Rosling demonstrates how to use data to tell the story of our rising civilization.

Bottom Line:  When it comes to science, the rule is to follow the facts.  When the story is contradicted by new facts, the story changes to fit the facts, not the other way around.

See also:  Data, Facts and Information

Too Many People, or Too Few?

A placard outside the UN headquarters in New York City, November 2011

Some years ago I read the book Boom, Bust and Echo. It described how planners for public institutions like schools and hospitals often fail to anticipate demographic shifts. The authors described how in North America, the baby Boom after WWII overcrowded schools, and governments struggled to build and staff more facilities. Just as they were catching up came the sexual revolution and the drop in fertility rates, resulting in a population Bust in children entering the education system. Now the issue was to close schools and retire teachers due to overcapacity, not easy to do with sentimental attachments. Then as the downsizing took hold came the Echo. Baby boomers began bearing children, and even at a lower birth rate, it still meant an increased cohort of students arriving at a diminished system.

The story is similar to what is happening today with world population. Zachary Karabell writes in Foreign Affairs The Population Bust: Demographic Decline and the End of Capitalism as We Know It. Excerpts in italics with my bolds.

For most of human history, the world’s population grew so slowly that for most people alive, it would have felt static. Between the year 1 and 1700, the human population went from about 200 million to about 600 million; by 1800, it had barely hit one billion. Then, the population exploded, first in the United Kingdom and the United States, next in much of the rest of Europe, and eventually in Asia. By the late 1920s, it had hit two billion. It reached three billion around 1960 and then four billion around 1975. It has nearly doubled since then. There are now some 7.6 billion people living on the planet.

Just as much of the world has come to see rapid population growth as normal and expected, the trends are shifting again, this time into reverse. Most parts of the world are witnessing sharp and sudden contractions in either birthrates or absolute population. The only thing preventing the population in many countries from shrinking more quickly is that death rates are also falling, because people everywhere are living longer. These oscillations are not easy for any society to manage. “Rapid population acceleration and deceleration send shockwaves around the world wherever they occur and have shaped history in ways that are rarely appreciated,” the demographer Paul Morland writes in The Human Tide, his new history of demographics. Morland does not quite believe that “demography is destiny,” as the old adage mistakenly attributed to the French philosopher Auguste Comte would have it. Nor do Darrell Bricker and John Ibbitson, the authors of Empty Planet, a new book on the rapidly shifting demographics of the twenty-first century. But demographics are clearly part of destiny. If their role first in the rise of the West and now in the rise of the rest has been underappreciated, the potential consequences of plateauing and then shrinking populations in the decades ahead are almost wholly ignored.

The mismatch between expectations of a rapidly growing global population (and all the attendant effects on climate, capitalism, and geopolitics) and the reality of both slowing growth rates and absolute contraction is so great that it will pose a considerable threat in the decades ahead. Governments worldwide have evolved to meet the challenge of managing more people, not fewer and not older. Capitalism as a system is particularly vulnerable to a world of less population expansion; a significant portion of the economic growth that has driven capitalism over the past several centuries may have been simply a derivative of more people and younger people consuming more stuff. If the world ahead has fewer people, will there be any real economic growth? We are not only unprepared to answer that question; we are not even starting to ask it.

BOMB OR BUST?
At the heart of The Human Tide and Empty Planet, as well as demography in general, is the odd yet compelling work of the eighteenth-century British scholar Thomas Malthus. Malthus’ 1798 Essay on the Principle of Population argued that growing numbers of people were a looming threat to social and political stability. He was convinced that humans were destined to produce more people than the world could feed, dooming most of society to suffer from food scarcity while the very rich made sure their needs were met. In Malthus’ dire view, that would lead to starvation, privation, and war, which would eventually lead to population contraction, and then the depressing cycle would begin again.

Yet just as Malthus reached his conclusions, the world changed. Increased crop yields, improvements in sanitation, and accelerated urbanization led not to an endless cycle of impoverishment and contraction but to an explosion of global population in the nineteenth century. Morland provides a rigorous and detailed account of how, in the nineteenth century, global population reached its breakout from millennia of prior human history, during which the population had been stagnant, contracting, or inching forward. He starts with the observation that the population begins to grow rapidly when infant mortality declines. Eventually, fertility falls in response to lower infant mortality—but there is a considerable lag, which explains why societies in the modern world can experience such sharp and extreme surges in population. In other words, while infant mortality is high, women tend to give birth to many children, expecting at least some of them to die before reaching maturity. When infant mortality begins to drop, it takes several generations before fertility does, too. So a woman who gives birth to six children suddenly has six children who survive to adulthood instead of, say, three. Her daughters might also have six children each before the next generation of women adjusts, deciding to have smaller families.

The population bust is going global almost as quickly as the population boom did in the twentieth century.  The burgeoning of global population in the past two centuries followed almost precisely the patterns of industrialization, modernization, and, crucially, urbanization. It started in the United Kingdom at the end of the nineteenth century (hence the concerns of Malthus), before spreading to the United States and then France and Germany. The trend next hit Japan, India, and China and made its way to Latin America. It finally arrived in sub-Saharan Africa, which has seen its population surge thanks to improvements in medicine and sanitation but has not yet enjoyed the full fruits of industrialization and a rapidly growing middle class.

With the population explosion came a new wave of Malthusian fears, epitomized by the 1968 book The Population Bomb, by Paul Ehrlich, a biologist at Stanford University. Ehrlich argued that plummeting death rates had created an untenable situation of too many people who could not be fed or housed. “The battle to feed all of humanity is over,” he wrote. “In the 1970’s the world will undergo famines—hundreds of millions of people are going to starve to death in spite of any crash programs embarked on now.”

Ehrlich’s prophecy, of course, proved wrong, for reasons that Bricker and Ibbitson elegantly chart in Empty Planet. The green revolution, a series of innovations in agriculture that began in the early twentieth century, accelerated such that crop yields expanded to meet humankind’s needs. Moreover, governments around the world managed to remediate the worst effects of pollution and environmental degradation, at least in terms of daily living standards in multiple megacities, such as Beijing, Cairo, Mexico City, and New Delhi. These cities face acute challenges related to depleted water tables and industrial pollution, but there has been no crisis akin to what was anticipated.

Doesn’t anyone want my Green New Deal?

Yet visions of dystopic population bombs remain deeply entrenched, including at the center of global population calculations: in the forecasts routinely issued by the United Nations. Today, the UN predicts that global population will reach nearly ten billion by 2050. Judging from the evidence presented in Morland’s and Bricker and Ibbitson’s books, it seems likely that this estimate is too high, perhaps substantially. It’s not that anyone is purposely inflating the numbers. Governmental and international statistical agencies do not turn on a dime; they use formulas and assumptions that took years to formalize and will take years to alter. Until very recently, the population assumptions built into most models accurately reflected what was happening. But the sudden ebb of both birthrates and absolute population growth has happened too quickly for the models to adjust in real time. As Bricker and Ibbitson explain,

“The UN is employing a faulty model based on assumptions that worked in the past but that may not apply in the future.”

Population expectations aren’t merely of academic interest; they are a key element in how most societies and analysts think about the future of war and conflict. More acutely, they drive fears about climate change and environmental stability—especially as an emerging middle class numbering in the billions demands electricity, food, and all the other accoutrements of modern life and therefore produces more emissions and places greater strain on farms with nutrient-depleted soil and evaporating aquifers. Combined with warming-induced droughts, storms, and shifting weather patterns, these trends would appear to line up for some truly bad times ahead.

Except, argue Bricker and Ibbitson, those numbers and all the doomsday scenarios associated with them are likely wrong. As they write,

“We do not face the challenge of a population bomb but a population bust—a relentless, generation-after-generation culling of the human herd.”

Already, the signs of the coming bust are clear, at least according to the data that Bricker and Ibbitson marshal. Almost every country in Europe now has a fertility rate below the 2.1 births per woman that is needed to maintain a static population. The UN notes that in some European countries, the birthrate has increased in the past decade. But that has merely pushed the overall European birthrate up from 1.5 to 1.6, which means that the population of Europe will still grow older in the coming decades and contract as new births fail to compensate for deaths. That trend is well under way in Japan, whose population has already crested, and in Russia, where the same trends, plus high mortality rates for men, have led to a decline in the population.

What is striking is that the population bust is going global almost as quickly as the population boom did in the twentieth century. Fertility rates in China and India, which together account for nearly 40 percent of the world’s people, are now at or below replacement levels. So, too, are fertility rates in other populous countries, such as Brazil, Malaysia, Mexico, and Thailand. Sub-Saharan Africa remains an outlier in terms of demographics, as do some countries in the Middle East and South Asia, such as Pakistan, but in those places, as well, it is only a matter of time before they catch up, given that more women are becoming educated, more children are surviving their early years, and more people are moving to cities.

Both books note that the demographic collapse could be a bright spot for climate change. Given that carbon emissions are a direct result of more people needing and demanding more stuff—from food and water to cars and entertainment—then it would follow that fewer people would need and demand less. What’s more, larger proportions of the planet will be aging, and the experiences of Japan and the United States are showing that people consume less as they age. A smaller, older population spells some relief from the immense environmental strain of so many people living on one finite globe.

The Reinvention of Chess

That is the plus side of the demographic deflation. Whether the concomitant greening of the world will happen quickly enough to offset the worst-case climate scenarios is an open question—although current trends suggest that if humanity can get through the next 20 to 30 years without irreversibly damaging the ecosystem, the second half of the twenty-first century might be considerably brighter than most now assume.

The downside is that a sudden population contraction will place substantial strain on the global economic system.

Capitalism is, essentially, a system that maximizes more—more output, more goods, and more services. That makes sense, given that it evolved coincidentally with a population surge. The success of capitalism in providing more to more people is undeniable, as are its evident defects in providing every individual with enough. If global population stops expanding and then contracts, capitalism—a system implicitly predicated on ever-burgeoning numbers of people—will likely not be able to thrive in its current form. An aging population will consume more of certain goods, such as health care, but on the whole aging and then decreasing populations will consume less. So much of consumption occurs early in life, as people have children and buy homes, cars, and white goods. That is true not just in the more affluent parts of the world but also in any country that is seeing a middle-class surge.

The future world may be one in which capitalism at best frays and at worst breaks down completely.
But what happens when these trends halt or reverse? Think about the future cost of capital and assumptions of inflation. No capitalist economic system operates on the presumption that there will be zero or negative growth. No one deploys investment capital or loans expecting less tomorrow than today. But in a world of graying and shrinking populations, that is the most likely scenario, as Japan’s aging, graying, and shrinking absolute population now demonstrates. A world of zero to negative population growth is likely to be a world of zero to negative economic growth, because fewer and older people consume less. There is nothing inherently problematic about that, except for the fact that it will completely upend existing financial and economic systems. The future world may be one of enough food and abundant material goods relative to the population; it may also be one in which capitalism at best frays and at worst breaks down completely.

The global financial system is already exceedingly fragile, as evidenced by the 2008 financial crisis. A world with negative economic growth, industrial capacity in excess of what is needed, and trillions of dollars expecting returns when none is forthcoming could spell a series of financial crises. It could even spell the death of capitalism as we know it. As growth grinds to a halt, people may well start demanding a new and different economic system. Add in the effects of automation and artificial intelligence, which are already making millions of jobs redundant, and the result is likely a future in which capitalism is increasingly passé.

If population contraction were acknowledged as the most likely future, one could imagine policies that might preserve and even invigorate the basic contours of capitalism by setting much lower expectations of future returns and focusing society on reducing costs (which technology is already doing) rather than maximizing output.

But those policies would likely be met in the short term by furious opposition from business interests, policymakers, and governments, all of whom would claim that such attitudes are defeatist and could spell an end not just to growth but to prosperity and high standards of living, too. In the absence of such policies, the danger of the coming shift will be compounded by a complete failure to plan for it.

Different countries will reach the breaking point at different times. Right now, the demographic deflation is happening in rich societies that are able to bear the costs of slower or negative growth using the accumulated store of wealth that has been built up over generations. Some societies, such as the United States and Canada, are able to temporarily offset declining population with immigration, although soon, there won’t be enough immigrants left. As for the billions of people in the developing world, the hope is that they become rich before they become old. The alternative is not likely to be pretty: without sufficient per capita affluence, it will be extremely difficult for developing countries to support aging populations.

So the demographic future could end up being a glass half full, by ameliorating the worst effects of climate change and resource depletion, or a glass half empty, by ending capitalism as we know it. Either way, the reversal of population trends is a paradigm shift of the first order and one that is almost completely unrecognized. We are vaguely prepared for a world of more people; we are utterly unprepared for a world of fewer. That is our future, and we are heading there fast.

See also Control Population, Control the Climate. Not.