Where Did The Social Distancing Strategy Come From?

I just read Michael Lewis’s superb 2021 book, The Premonition: A Pandemic Story.

He writes:

* The problem, as he [Richard Hatchett in 2005] framed it for the Pentagon, was how to slow the spread of a communicable disease until you can produce a vaccine. As communicable disease spreads through social networks, Richard reasoned, you had to find ways to disrupt those networks. And the easiest way to do that was to move people physically farther apart from each other. “Increasing Effective Social Distance as a Strategy,” he called it. “Social distance” had been used by anthropologists to describe kinship, but he didn’t know that at the time, and so he thought he was giving birth to a phrase. (“But I don’t think I turned it into a gerund,” he’d later say.) What he also didn’t realize was that he was giving new life, to a dead idea: that apart from isolating people who were ill, you needed to do anything you could to slow the spread of a disease before you had drugs to help. “I was this emergency room doctor,” he said. “I didn’t know that people said all this stuff had been tried in 1918 and it hadn’t worked. I wasn’t rejecting anything. I just didn’t know any better.”

* There was, most importantly, a passage that suggested what the federal government might do, at the start of a pandemic, before a vaccine was available. It would, they’d written, “provide guidance, including decision criteria and tools, to all levels of government on the range of options for infection control and containment, including those circumstances where social distancing measures, limitations on gatherings or quarantine authority may be an appropriate public health intervention.”
It was hard to imagine anyone wading into that passage voluntarily, much less giving it a second thought. The words mattered less for what they said than for what they could be made to say. Like the words in the Holy Bible or the U.S. Constitution, they invited the problem of how they might be interpreted, and by whom, and for what purposes. As read by Richard Hatchett and Carter Mecher, those words gave them cover to answer the most important medical question they’d ever faced: How do you save lives in a pandemic before you have the drugs and vaccines to do it?

* The graph illustrated the effects on a disease of various crude strategies: isolating the ill; quarantining entire households when they had a sick person in them; socially distancing adults; giving people antiviral drugs; and so on. Each of the crude strategies had some slight effect, but none by itself made much of a dent, and certainly none had the ability to halt the pandemic by driving the disease’s reproductive rate below 1. One intervention was not like the others, however: when you closed schools and put social distance between kids, the flu-like disease fell off a cliff. (The model defined “social distance” not as zero contact but as a 60 percent reduction in kids’ social interaction.) “I said, ‘Holy shit!’ ” said Carter. “Nothing big happens until you close the schools. It’s not like anything else. It’s like a phase change. It’s nonlinear. It’s like when water temperature goes from thirty-three to thirty-two. When it goes from thirty-four to thirty-three, it’s no big deal; one degree colder and it turns to ice.”

* In the end he plotted both the deaths [in the 1918 Spanish Flu] and the restrictions imposed to prevent them, and saw that the earlier the restrictions imposed in any given outbreak, the fewer the deaths. In the case of Philadelphia, he wrote, “the closing of schools and churches, banning of public meetings, and banning of large public gatherings occurred relatively late into the epidemic”—nearly one month after the outbreak began and just a week before its peak. He wondered if other cities had reacted more quickly, and if their specific reactions might explain the huge variation in the death rates from city to city.

…“Others use the stories in Barry’s book to support the position that the infection control and social distancing measures would probably be ineffective,” he wrote. “On the flight back to Atlanta I went thru Barry’s book carefully and tried to reconstruct the events in a particularly hard hit city—Philadelphia . . . The bottom line is that anyone using the 1918 Philadelphia experience to argue that infection control and social distancing measures would be of little help needs to recognize how ineffective the overall response was in Philadelphia and how late the measures were instituted (within one week of the epidemic peak and after tens of thousands and perhaps hundreds of thousands were already ill).”

* It took just a few months for them to piece together what had actually happened in 1918. Their paper appeared in the May 2007 issue of the Proceedings of the National Academy of Sciences . A coauthor and friend, the Harvard epidemiologist Marc Lipsitch, did the statistical work and the other stuff that made it seem as if it were written by proper scholars. § Titled “Public Health Interventions and Epidemic Intensity during the 1918 Influenza Pandemic,” the piece revealed, for the first time, the life-or-death importance of timing in the outcomes of 1918. Cities that intervened immediately after the arrival of the virus experienced far less disease and death. The first reported flu cases in Philadelphia had been on September 17. The first case wasn’t spotted in St. Louis until October 5—which also happened to be the day the United States surgeon general, Rupert Blue, finally acknowledged the severity of the disease and recommended that local leaders take action. The death rate in St. Louis was half that of Philadelphia because St. Louis’s leaders used the cover provided by the federal government to distance its citizens from one another.
That didn’t mean that everyone in St. Louis appreciated what had happened. “We’re reading the newspapers in St. Louis,” said Richard, “and they know for a fact that they are having a better experience than other cities, and they still couldn’t keep their interventions in place for more than four to six weeks.” The paper analyzed the effects of that inability, and showed that American cities that caved to pressure from business interests to relax their social distancing rules experienced big second waves of disease. American cities that didn’t did not. The paper offered a real-world confirmation of what Bob Glass and the other mathematical modelers had discovered in their fake worlds. However you felt about the strategy of Targeted Layered Containment, you could no longer say there was no data to show that it had any effect. “Until then, the people who hated our ideas could throw up smoke screens about modeling,” said Richard. “They couldn’t throw up smoke screens about what had happened in 1918.”
The paper’s more subtle message appeared between its lines: people have a very hard time getting their minds around pandemics. Why was it still possible, in 2006, to say something original and important about the events of 1918? Why had it taken nearly a century to see a simple truth about the single most deadly pandemic in human history? Only after three amateur historians studied the various interventions, and the various death tolls in individual American cities, did the importance of timing became obvious. Carter wondered why this had been so hard to see. A big part of the answer, he decided, was in the nature of pandemics. They were exponential processes. If you took a penny and doubled it every day for thirty days, you’d have more than five million dollars: people couldn’t imagine disease spread any better than they could imagine a penny growing like that. “I think it’s because of the way our brains are wired,” said Carter. “Take a piece of paper and fold it in half, then fold it in half again, for a total of 50 times folding it in half. If a piece of paper is 0.004 inches thick to begin with, by the time you fold it 50 times, it is more than 70 million miles thick.” Again, it feels impossible. The same mental glitch that leads people to not realize the power of compound interest blinds them to the importance of intervening before a pathogen explodes.
It was seven months before the United States public-health system fully bought into the power of social distancing. The story of those months was dear to Lisa Koonin. She saved every email and every version of the fifty or more presentations she and Carter made—to everyone from the Department of Education to state and local public-health officers who filled hotel ballrooms. She thought she might one day write a book about it.
The big theme of her book would be the power of storytelling. It had taken Lisa, Richard, and Carter some time to see that they were in a war of competing narratives, and that whoever had the best narrative would win. Public-health people who did not actually know all that much about the subject, for instance, would insist that if you closed schools, all sorts of bad things would happen: crime would rise with kids on the streets; the thirty million kids in the school-lunch program would lack nutrition; parents wouldn’t be able to go to work; and so on. American society now leaned on schools to care for children in a way that would have bewildered Americans of an earlier age, as that other institution, the family, was failing at the job. “The sub-rosa conversation was that families weren’t safe places for children,” said Lisa.
To refute knee-jerk arguments about the costs of social distancing, Carter had marshaled so much data from so many corners of the U.S. government that a senior public-health official who passed through the White House called him Rain Man. He’d show his critics that crime rates actually fell on weekends, for instance, when kids were out of school. The FBI keeps all these stats, he’d say. Juvenile crime peaks at 3:30 p.m. on weekdays. Because they’ve been cooped up all day and they’re just going nuts. He’d show his critics exactly how many households would need help minding their children—and it was not nearly as many as they had assumed. During the summers, only 2.6 million kids used the school-lunch program: Did that not suggest that the number of kids without access to proper nutrition was far smaller than the number of kids using the program? He showed them a survey that Lisa Koonin commissioned, of parents with children who used it: just one in seven, or 2.8 million, said they’d have trouble feeding their children if schools could not. If schools were closed, Carter concluded, the problem was not 30 million kids but fewer than 3 million; they could be fed with supplemental food stamps.

* Carter sat at a desk and, consulting with Richard over the phone, wrote the CDC’s new policy, which called for social distancing in the event of any pandemic. The nature of the interventions would depend on the severity of the disease, of course. The CDC recommended that schools close, for instance, only when some new communicable disease was projected to kill more than 450,000 Americans. But school closure and social distancing of kids and bans on mass gatherings and other interventions would be central to the future pandemic strategy of the United States—and not just the United States. “The CDC was the world’s leading health agency,” said Lisa. “When the CDC publishes something, it is not just the CDC talking to the U.S. but to the entire world.”

* Two months after the CDC published its new pandemic strategy, Laura Glass, now sixteen years old, returned to Washington, DC, for her final science competition. The Young Epidemiology Scholars Competition, this new contest was called. Her mom had somehow found out about it and suggested she enter her science fair project and make a trip of it. On her giant foam boards, she’d honed her mission statement. “Could the oldest of strategies, social distancing, be designed to target specific age groups and zones of high infectious contact within a social contact network and thus limit the spread of disease?” she’d written. On her boards, she walked the science fair judges through all the work she had done. She explained the computer model she had helped to build, the surveys she’d done of the citizens of Albuquerque, New Mexico, and the insights that her work had led to, with the help of the model. “I found that if schools are closed AND preschoolers, children and teens are restricted to the home epidemics that would have infected 65% of the population COULD BE REDUCED BY NEARLY 80%,” she wrote. “If adults also restrict their contacts within non-essential work environments epidemics from such highly infective strains can be ENTIRELY THWARTED!”

Posted in Corona Virus | Comments Off on Where Did The Social Distancing Strategy Come From?

Average COVID death costs 16 years of life (7-28-21)

01:00 Are US flu death figures more PR than science? https://lukeford.net/blog/?p=141529
03:00 Comparing COVID-19 Deaths to Flu Deaths Is like Comparing Apples to Oranges — The former are actual numbers; the latter are inflated statistical estimates, https://lukeford.net/blog/?p=141527
05:00 What are the stages and symptoms of COVID-19?, https://www.drugs.com/medical-answers/covid-19-symptoms-progress-death-3536264/
09:00 US Jews More Likely to Support COVID-19 Vaccine Push Compared With Other Religious Groups, https://lukeford.net/blog/?p=141509
10:00 Average Covid Death Costs 16 Years Of Life, https://lukeford.net/blog/?p=141514
15:00 Arguing about covid with a philosopher friend, https://lukeford.net/blog/?p=141500
25:00 Excess deaths during age of Covid, https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm
27:00 The “only 6%” gambit: The viral COVID-19 disinformation, https://lukeford.net/blog/?p=138146
29:00 The changing temptations of science, https://lukeford.net/blog/?p=140413
30:00 The Naked State: What the Breakdown of Normality Reveals, https://lukeford.net/blog/?p=140282
60:00 Tucker Carlson profile, https://time.com/6080432/tucker-carlson-profile/
68:00 No show has ever made you as terrified of doctors as ‘Dr. Death’ will, https://www.sfgate.com/streaming/article/dr-death-nbc-peacock-review-alec-baldwin-16343688.php
69:00 Peacock’s Dr. Death Is Based on A Chilling True Crime Podcast About a Murderous Surgeon. https://time.com/6080714/dr-death-true-story/
71:00 Chaos: Charles Manson, the CIA, and the Secret History of the Sixties, https://www.amazon.com/Chaos-Charles-History-Sixtiest-Sixties-ebook/dp/B07K6J273Q/
73:00 Barry, https://en.wikipedia.org/wiki/Barry_(TV_series)
75:00 Kyle Rowland update, https://twitter.com/rowlandkyles

Posted in America, Corona Virus | Comments Off on Average COVID death costs 16 years of life (7-28-21)

Are US flu death figures more PR than science?

From the British Medical Journal, Dec. 10, 2005:

US data on influenza deaths are a mess. The Centers for Disease Control and Prevention (CDC) acknowledges a difference between flu death and flu associated death yet uses the terms interchangeably. Additionally, there are significant statistical incompatibilities between official estimates and national vital statistics data. Compounding these problems is a marketing of fear—a CDC communications strategy in which medical experts “predict dire outcomes” during flu seasons.

The CDC website states what has become commonly accepted and widely reported in the lay and scientific press: annually “about 36 000 [Americans] die from flu” (www.cdc.gov/flu/about/disease.htm) and “influenza/pneumonia” is the seventh leading cause of death in the United States (www.cdc.gov/nchs/fastats/lcod.htm). But why are flu and pneumonia bundled together? Is the relationship so strong or unique to warrant characterising them as a single cause of death?

David Rosenthal, director of Harvard University Health Services, said, “People don’t necessarily die, per se, of the [flu] virus—the viraemia. What they die of is a secondary pneumonia. So many of these pneumonias are not viral pneumonias but secondary [pneumonias].” But Dr Rosenthal agreed that the flu/pneumonia relationship was not unique. For instance, a recent study (JAMA 2004;292: 1955-60 [PubMed] [Google Scholar]) found that stomach acid suppressing drugs are associated with a higher risk of community acquired pneumonia, but such drugs and pneumonia are not compiled as a single statistic.

CDC states that the historic 1968-9 “Hong Kong flu” pandemic killed 34 000 Americans. At the same time, CDC claims 36 000 Americans annually die from flu. What is going on?

Meanwhile, according to the CDC’s National Center for Health Statistics (NCHS), “influenza and pneumonia” took 62 034 lives in 2001—61 777 of which were attributed to pneumonia and 257 to flu, and in only 18 cases was flu virus positively identified. Between 1979 and 2002, NCHS data show an average 1348 flu deaths per year (range 257 to 3006).

The NCHS data would be compatible with CDC mortality estimates if about half of the deaths classed by the NCHS as pneumonia were actually flu initiated secondary pneumonias. But the NCHS criteria indicate otherwise: “Cause-of-death statistics are based solely on the underlying cause of death… defined by WHO as `the disease or injury which initiated the train of events leading directly to death.’”

In a written statement, CDC media relations responded to the diverse statistics: “Typically, influenza causes death when the infection leads to severe medical complications.” And as most such cases “are never tested for virus infection…CDC considers these [NCHS] figures to be a very substantial undercounting of the true number of deaths from influenza. Therefore, the CDC uses indirect modelling methods to estimate the number of deaths associated with influenza.”

CDC’s model calculated an average annual 36 155 deaths from influenza associated underlying respiratory and circulatory causes (JAMA 2003;289: 179-86 [PubMed] [Google Scholar]). Less than a quarter of these (8097) were described as flu or flu associated underlying pneumonia deaths. Thus the much publicised figure of 36 000 is not an estimate of yearly flu deaths, as widely reported in both the lay and scientific press, but an estimate—generated by a model—of flu-associated death.

William Thompson of the CDC’s National Immunization Program (NIP), and lead author of the CDC’s 2003 JAMA article, explained that “influenza-associated mortality” is “a statistical association between deaths and viral data available.” He said that an association does not imply an underlying cause of death: “Based on modelling, we think it’s associated. I don’t know that we would say that it’s the underlying cause of death.”

Yet this stance is incompatible with the CDC assertion that the flu kills 36 000 people a year—a misrepresentation that is yet to be publicly corrected.

Before 2003 CDC said that 20 000 influenza-associated deaths occurred each year. The new figure of 36 000 reported in the January 2003 JAMA paper is an estimate of influenza-associated mortality over the 1990s. Keiji Fukuda, a flu researcher and a co-author of the paper, has been quoted as offering two possible causes for this 80% increase: “One is that the number of people older than 65 is growing larger…The second possible reason is the type of virus that predominated in the 1990s [was more virulent].”

However, the 65-plus population grew just 12% between 1990 and 2000. And if flu virus was truly more virulent over the 1990s, one would expect more deaths. But flu deaths recorded by the NCHS were on average 30% lower in the 1990s than the 1980s.

If passed, the Flu Protection Act of 2005 will revamp US flu vaccine policy. The legislation will require CDC to pay makers for vaccines unsold “through routine market mechanisms.” The bill will also require CDC to conduct a “public awareness campaign” emphasising “the safety and benefit of recommended vaccines for the public good.”

Yet this bill obscures the fact that CDC is already working in manufacturers’ interest by conducting campaigns to increase flu vaccination. At the 2004 “National Influenza Vaccine Summit,” co-sponsored by CDC and the American Medical Association, Glen Nowak, associate director for communications at the NIP, spoke on using the media to boost demand for the vaccine. One step of a “Seven-Step `Recipe’ for Generating Interest in, and Demand for, Flu (or any other) Vaccination” occurs when “medical experts and public health authorities publicly…state concern and alarm (and predict dire outcomes)—and urge influenza vaccination” (www.ama-assn.org/ama1/pub/upload/mm/36/2004_flu_nowak.pdf). Another step entails “continued reports…that influenza is causing severe illness and/or affecting lots of people, helping foster the perception that many people are susceptible to a bad case of influenza.”

Preceding the summit, demand had been low early into the 2003 flu season. “At that point, the manufacturers were telling us that they weren’t receiving a lot of orders for vaccine for use in November or even December,” recalled Dr Nowak on National Public Radio. “It really did look like we needed to do something to encourage people to get a flu shot.”

If flu is in fact not a major cause of death, this public relations approach is surely exaggerated. Moreover, by arbitrarily linking flu with pneumonia, current data are statistically biased. Until corrected and until unbiased statistics are developed, the chances for sound discussion and public health policy are limited.

Posted in CDC, Corona Virus | Comments Off on Are US flu death figures more PR than science?

Comparing COVID-19 Deaths to Flu Deaths Is like Comparing Apples to Oranges — The former are actual numbers; the latter are inflated statistical estimates

Dr. Jeremy Samuel Faust writes April 28, 2020 for Scientific American:

When reports about the novel coronavirus SARS-CoV-2 began circulating earlier this year and questions were being raised about how the illness it causes, COVID-19, compared to the flu, it occurred to me that, in four years of emergency medicine residency and over three and a half years as an attending physician, I had almost never seen anyone die of the flu. I could only remember one tragic pediatric case.

Based on the CDC numbers though, I should have seen many, many more. In 2018, over 46,000 Americans died from opioid overdoses. Over 36,500 died in traffic accidents. Nearly 40,000 died from gun violence. I see those deaths all the time. Was I alone in noticing this discrepancy?

I decided to call colleagues around the country who work in other emergency departments and in intensive care units to ask a simple question: how many patients could they remember dying from the flu? Most of the physicians I surveyed couldn’t remember a single one over their careers. Some said they recalled a few. All of them seemed to be having the same light bulb moment I had already experienced: For too long, we have blindly accepted a statistic that does not match our clinical experience.

The 25,000 to 69,000 numbers that Trump cited do not represent counted flu deaths per year; they are estimates that the CDC produces by multiplying the number of flu death counts reported by various coefficients produced through complicated algorithms. These coefficients are based on assumptions of how many cases, hospitalizations, and deaths they believe went unreported. In the last six flu seasons, the CDC’s reported number of actual confirmed flu deaths—that is, counting flu deaths the way we are currently counting deaths from the coronavirus—has ranged from 3,448 to 15,620, which far lower than the numbers commonly repeated by public officials and even public health experts.

There is some logic behind the CDC’s methods. There are, of course, some flu deaths that are missed, because not everyone who contracts the flu gets a flu test. But there are little data to support the CDC’s assumption that the number of people who die of flu each year is on average six times greater than the number of flu deaths that are actually confirmed. In fact, in the fine print, the CDC’s flu numbers also include pneumonia deaths.

Posted in Corona Virus | Comments Off on Comparing COVID-19 Deaths to Flu Deaths Is like Comparing Apples to Oranges — The former are actual numbers; the latter are inflated statistical estimates

Average Covid Death Costs 16 Years Of Life

Nature magazine published this article February 18, 2021:

* We find that over 20.5 million years of life have been lost to COVID-19 globally. As of January 6, 2021, YLL in heavily affected countries are 2–9 times the average seasonal influenza; three quarters of the YLL result from deaths in ages below 75 and almost a third from deaths below 55; and men have lost 45% more life years than women. The results confirm the large mortality impact of COVID-19 among the elderly. They also call for heightened awareness in devising policies that protect vulnerable demographics losing the largest number of life-years.

* The average years of life lost per death is 16 years.

* We find that in heavily impacted highly developed countries, COVID-19 is 2–9 times that of the common seasonal influenza (as compared to a median flu year for the same country), between 2 and 8 times traffic related YLL (years of life lost) rates, between a quarter and a half of the YLL rates attributable to heart conditions in countries (with rates as high as parity to twice that of heart conditions in Latin America).

* A noted problem in attributing deaths to COVID-19 has been systematic undercounting of deaths due to COVID-19, as official death counts may reflect limitations in testing as well as difficulties in counting in out-of-hospital contexts… Our results support the claim that the true mortality burden of COVID-19 is likely to be substantially higher. Comparisons of COVID-19 attributable deaths and excess deaths approaches to calculating YLL suggests that the former on average may underestimate YLL by a factor of 3 [meaning, multiply the covid death toll by three to get a more accurate number].

* This study’s sample presents an average age-at-death of 72.9 years; yet only a fraction of the YLL can be attributed to the individuals in the oldest age brackets. Globally, 44.9% of the total YLL can be attributed to the deaths of individuals between 55 and 75 years old, 30.2% to younger than 55, and 25% to those older than 75. That is, the average figure of 16 YLL includes the years lost from individuals close to the end of their expected lives, but the majority of those years are from individuals with significant remaining life expectancy.

* These results must be understood in the context of an as-of-yet ongoing pandemic and after the implementation of unprecedented policy measures. Existing estimates on the counterfactual of no policy response suggest much higher death tolls and, consequently, YLL. Our calculations based on the projections by8 yield a total impact several orders of magnitude higher, especially considering projections based on a complete absence of interventions (see Supplementary Information for details on projections). This is in line with further evidence of the life-saving impacts of lockdowns and social distancing measures15.

There are two key sources of potential bias to our results, and these biases operate in different directions. First, COVID-19 deaths may not be accurately recorded, and most of the evidence suggests that on the aggregate level, they may be an undercount of the total death toll. As a result, our YLL estimates may be underestimates as well. We compare our YLL estimates to estimates based on excess death approaches that require more modeling assumptions but are robust to missclassification of deaths. The results of this comparison suggest that on average across countries, we might underestimate COVID-19 YLL rates by a factor of 3.

Second, those dying from COVID-19 may be an at-risk population whose remaining life expectancy is shorter than the average person’s remaining life expectancy16,17,18. This methodological concern is likely to be valid, and consequently our estimate of the total YLL due to COVID-19 may be an overestimate.

Posted in Corona Virus | Comments Off on Average Covid Death Costs 16 Years Of Life