COVID-19

TorontoGold

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He agrees that people are hysterical but better to overreact than not react so sees some value in it as these actions need to be voluntary (liberty is a thing). He agrees that social distancing and hand washing would be adequate, not much you can do in shitholes like NYC where avoidance is nearly impossible. He agrees the goal posts are being moved from "flattening" to OMG we have to save EVERYBODY which he KNOWS is totally unreasonable. He does not think the boogeyman is hiding behind every tree or sitting on every grocery cart handle and if it is, just wash your hands and don't touch your face to neuter him. But then again he is a Michigan fan/grad so an argument can be made he is a complete moron.

My point on the flu - with vaccines and years of action it is still very deadly across most strains. 10% of flu hospitalizations end up dead after years of battling it. What makes a Wuhan Flu death so much more noble and less tolerable than an Influenza death? And we absolutely are getting data to support common sense that way more people HAD or HAVE it than testing is catching. CDC says 25% show no symptoms ever - why would they test, how would we know? How do you know who had it three weeks ago and recovered? All the chicken littles demand everyone assumes nobody every had it who didn't test positive, except when we lay a C19 diagnosis on a dead person to help prop up numbers to validate bad decisions. I have seen ranges of 10x to 85x for numbers who have had it beyond the confirmed cases. Apply that to flu mortality and it is the same or less, unchecked out of the gate without knowing how to fight it or vaccinate. How is that more deadly than the flu again?

COVID19 comes from an inherently more benign virus family of coronavirus. Logic would tell me mutations are more likely to be milder, not meaner whereas influenza mutations are mostly mean and less often mild (IMO - I didn't source fifty studies to create that theory, just seems logical).

1. South Korea seemed to be able to handle it in Seoul. Not sure why NYC is considered a shithole.

2. Your claim is that we are getting data to support that more people have had it than testing is catching, but they you go on to say "How do we know who had it three weeks ago and recovered?" Wouldn't the same tests that test for antibodies highly suggest that those people have it and recovered? Wouldn't we want to test for people that have had it so that we can start reducing lockdown restrictions?

3. When you say bad decisions, which ones are you speaking to?
 

Kingbish01

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I'm counting diabetes and asthma as people who should be on alert, and not be out. Not just talking about nursing homes.

For as big as ATL is, and having the busiest airport in the world, you would think it would have been much worse here. I certainly did, but it wasn't. The deaths here have had extremely high rates of at risk characteristics. Those folks need to continue to stay home.

I for sure thought it would be worse here than it's been. What suburb are you in again? I'm in Roswell, closer to Sandy Springs than Alpharetta.
 

Irishize

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<blockquote class="twitter-tweet"><p lang="en" dir="ltr">This means they got the seed date wrong by at least 21 days. Incalculable what that does to contagion rate input, etc<br><br>A government seeking the truth would be rounding up blood samples, biopsies, lung scans, etc of every single “pneumonia” death from Oct 2019 on for testing. <a href="https://t.co/9fdnU5Zr27">https://t.co/9fdnU5Zr27</a></p>— ESSENTIAL Andy Swan (@AndySwan) <a href="https://twitter.com/AndySwan/status/1252832231392858114?ref_src=twsrc%5Etfw">April 22, 2020</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
 

ab2cmiller

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<blockquote class="twitter-tweet"><p lang="en" dir="ltr">This means they got the seed date wrong by at least 21 days. Incalculable what that does to contagion rate input, etc<br><br>A government seeking the truth would be rounding up blood samples, biopsies, lung scans, etc of every single “pneumonia” death from Oct 2019 on for testing. <a href="https://t.co/9fdnU5Zr27">https://t.co/9fdnU5Zr27</a></p>— ESSENTIAL Andy Swan (@AndySwan) <a href="https://twitter.com/AndySwan/status/1252832231392858114?ref_src=twsrc%5Etfw">April 22, 2020</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

Mid January, I had every COVID symptom. Tested negative for Influenza A and B. Tested negative for strep. Fever continually spiking for days, extreme exhaustion, coughing so much my stomach hurt, shortness of breath. Pnuemonia was finally diagnosed via a chest x-ray. Did I have COVID? Most likely not, but it certainly makes me wonder if it was possible.
 

Irishize

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Mid January, I had every COVID symptom. Tested negative for Influenza A and B. Tested negative for strep. Fever continually spiking for days, extreme exhaustion, coughing so much my stomach hurt, shortness of breath. Pnuemonia was finally diagnosed via a chest x-ray. Did I have COVID? Most likely not, but it certainly makes me wonder if it was possible.

First off...glad you recovered and are doing well now. Stay healthy. On a morbid note, had you passed away from your condition, you would’ve been counted as a COVID death.
 

Whiskeyjack

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Bernard Avishai just published an article in The New Yorker titled "The Pandemic Isn't a Black Swan But a Portent of a More Fragile Global System":

assim Nicholas Taleb is “irritated,” he told Bloomberg Television on March 31st, whenever the coronavirus pandemic is referred to as a “black swan,” the term he coined for an unpredictable, rare, catastrophic event, in his best-selling 2007 book of that title. “The Black Swan” was meant to explain why, in a networked world, we need to change business practices and social norms—not, as he recently told me, to provide “a cliché for any bad thing that surprises us.” Besides, the pandemic was wholly predictable—he, like Bill Gates, Laurie Garrett, and others, had predicted it—a white swan if ever there was one. “We issued our warning that, effectively, you should kill it in the egg,” Taleb told Bloomberg. Governments “did not want to spend pennies in January; now they are going to spend trillions.”

The warning that he referred to appeared in a January 26th paper that he co-authored with Joseph Norman and Yaneer Bar-Yam, when the virus was still mainly confined to China. The paper cautions that, owing to “increased connectivity,” the spread will be “nonlinear”—two key contributors to Taleb’s anxiety. For statisticians, “nonlinearity” describes events very much like a pandemic: an output disproportionate to known inputs (the structure and growth of pathogens, say), owing to both unknown and unknowable inputs (their incubation periods in humans, or random mutations), or eccentric interaction among various inputs (wet markets and airplane travel), or exponential growth (from networked human contact), or all three.

“These are ruin problems,” the paper states, exposure to which “leads to a certain eventual extinction.” The authors call for “drastically pruning contact networks,” and other measures that we now associate with sheltering in place and social distancing. “Decision-makers must act swiftly,” the authors conclude, “and avoid the fallacy that to have an appropriate respect for uncertainty in the face of possible irreversible catastrophe amounts to ‘paranoia.’ ” (“Had we used masks then”—in late January—“we could have saved ourselves the stimulus,” Taleb told me.)

Yet, for anyone who knows his work, Taleb’s irritation may seem a little forced. His profession, he says, is “probability.” But his vocation is showing how the unpredictable is increasingly probable. If he was right about the spread of this pandemic it’s because he has been so alert to the dangers of connectivity and nonlinearity more generally, to pandemics and other chance calamities for which COVID-19 is a storm signal. “I keep getting asked for a list of the next four black swans,” Taleb told me, and that misses his point entirely. In a way, focussing on his January warning distracts us from his main aim, which is building political structures so that societies will be better able to cope with mounting, random events.

Indeed, if Taleb is chronically irritated, it is by those economists, officials, journalists, and executives—the “naïve empiricists”—who think that our tomorrows are likely to be pretty much like our yesterdays. He explained in a conversation that these are the people who, consulting bell curves, focus on their bulging centers, and disregard potentially fatal “fat tails”—events that seem “statistically remote” but “contribute most to outcomes,” by precipitating chain reactions, say. (Last week, Dr. Phil told Fox’s Laura Ingraham that we should open up the country again, noting, wrongly, that “three hundred and sixty thousand people die each year “from swimming pools — but we don’t shut the country down for that.” In response, Taleb tweeted, “Drowning in swimming pools is extremely contagious and multiplicative.”) Naïve empiricists plant us, he argued in “The Black Swan,” in “Mediocristan.” We actually live in “Extremistan.”

Taleb, who is sixty-one, came by this impatience honestly. As a young man, he lived through Lebanon’s civil war, which was precipitated by Palestinian militias escaping a Jordanian crackdown, in 1971, and led to bloody clashes between Maronite Christians and Sunni Muslims, drawing in Shiites, Druze, and the Syrians as well. The conflict lasted fifteen years and left some ninety thousand people dead. “These events were unexplainable, but intelligent people thought they were capable of providing convincing explanations for them—after the fact,” Taleb writes in “The Black Swan.” “The more intelligent the person, the better sounding the explanation.” But how could anyone have anticipated “that people who seemed a model of tolerance could become the purest of barbarians overnight?” Given the prior cruelties of the twentieth century, the question may sound ingenuous, but Taleb experienced sudden violence firsthand. He grew fascinated, and outraged, by extrapolations from an illusory normal—the evil of banality. “I later saw the exact same illusion of understanding in business success and the financial markets,” he writes.

“Later” began in 1983, when, after university in Paris, and a Wharton M.B.A., Taleb became an options trader—“my core identity,” he says. Over the next twelve years, he conducted two hundred thousand trades, and examined seventy thousand risk-management reports. Along the way, he developed an investment strategy that entailed exposure to regular, small losses, while positioning him to benefit from irregular, massive gains—something like a venture capitalist. He explored, especially, scenarios for derivatives: asset bundles where fat tails—price volatilities, say—can either enrich or impoverish traders, and do so exponentially when they increase the scale of the movement.

These were the years, moreover, when, following Japan, large U.S. manufacturing companies were converting to “just-in-time” production, which involved integrating and synchronizing supply-chains, and forgoing stockpiles of necessary components in favor of acquiring them on an as-needed basis, often relying on single, authorized suppliers. The idea was that lowering inventory would reduce costs. But Taleb, extrapolating from trading risks, believed that “managing without buffers was irresponsible,” because “fat-tail events” can never be completely avoided. As the Harvard Business Review reported this month, Chinese suppliers shut down by the pandemic have stymied the production capabilities of a majority of the companies that depend on them.

The coming of global information networks deepened Taleb’s concern. He reserved a special impatience for economists who saw these networks as stabilizing—who thought that the average thought or action, derived from an ever-widening group, would produce an increasingly tolerable standard—and who believed that crowds had wisdom, and bigger crowds more wisdom. Thus networked, institutional buyers and sellers were supposed to produce more rational markets, a supposition that seemed to justify the deregulation of derivatives, in 2000, which helped accelerate the crash of 2008.

As Taleb told me, “The great danger has always been too much connectivity.” Proliferating global networks, both physical and virtual, inevitably incorporate more fat-tail risks into a more interdependent and “fragile” system: not only risks such as pathogens but also computer viruses, or the hacking of information networks, or reckless budgetary management by financial institutions or state governments, or spectacular acts of terror. Any negative event along these lines can create a rolling, widening collapse—a true black swan—in the same way that the failure of a single transformer can collapse an electricity grid.

COVID-19 has initiated ordinary citizens into the esoteric “mayhem” that Taleb’s writings portend. Who knows what will change for countries when the pandemic ends? What we do know, Taleb says, is what cannot remain the same. He is “too much a cosmopolitan” to want global networks undone, even if they could be. But he does want the institutional equivalent of “circuit breakers, fail-safe protocols, and backup systems,” many of which he summarizes in his fourth, and favorite, book, “Antifragile,” published in 2012. For countries, he envisions political and economic principles that amount to an analogue of his investment strategy: government officials and corporate executives accepting what may seem like too-small gains from their investment dollars, while protecting themselves from catastrophic loss.

Anyone who has read the Federalist Papers can see what he’s getting at. The “separation of powers” is hardly the most efficient form of government; getting something done entails a complex, time-consuming process of building consensus among distributed centers of authority. But James Madison understood that tyranny—however distant it was from the minds of likely Presidents in his own generation—is so calamitous to a republic, and so incipient in the human condition, that it must be structurally mitigated. For Taleb, an antifragile country would encourage the distribution of power among smaller, more local, experimental, and self-sufficient entities—in short, build a system that could survive random stresses, rather than break under any particular one. (His word for this beneficial distribution is “fractal.”)

We should discourage the concentration of power in big corporations, “including a severe restriction of lobbying,” Taleb told me. “When one per cent of the people have fifty per cent of the income, that is a fat tail.” Companies shouldn’t be able to make money from monopoly power, “from rent-seeking”—using that power not to build something but to extract an ever-larger part of the surplus. There should be an expansion of the powers of state and even county governments, where there is “bottom-up” control and accountability. This could incubate new businesses and foster new education methods that emphasize “action learning and apprenticeship” over purely academic certification. He thinks that “we should have a national Entrepreneurship Day.”

But Taleb doesn’t believe that the government should abandon citizens buffeted by events they can’t possibly anticipate or control. (He dedicated his book “Skin in the Game,” published in 2018, to Ron Paul and Ralph Nader.) “The state,” he told me, “should not smooth out your life, like a Lebanese mother, but should be there for intervention in negative times, like a rich Lebanese uncle.” Right now, for example, the government should, indeed, be sending out checks to unemployed and gig workers. (“You don’t bail out companies, you bail out individuals.”) He would also consider a guaranteed basic income, much as Andrew Yang, whom he admires, has advocated. Crucially, the government should be an insurer of health care, though Taleb prefers not a centrally run Medicare-for-all system but one such as Canada’s, which is controlled by the provinces. And, like responsible supply-chain managers, the federal government should create buffers against public-health disasters: “If it can spend trillions stockpiling nuclear weapons, it ought to spend tens of billions stockpiling ventilators and testing kits.”

At the same time, Taleb adamantly opposes the state taking on staggering debt. He thinks, rather, that the rich should be taxed as disproportionately as necessary, “though as locally as possible.” The key is “to build on the good days,” when the economy is growing, and reduce the debt, which he calls “intergenerational dispossession.” The government should then encourage an eclectic array of management norms: drawing up political borders, even down to the level of towns, which can, in an epidemiological emergency, be closed; having banks and corporations hold larger cash reserves, so that they can be more independent of market volatility; and making sure that manufacturing, transportation, information, and health-care systems have redundant storage and processing components. (“That’s why nature gave us two kidneys.”) Taleb is especially keen to inhibit “moral hazard,” such as that of bankers who get rich by betting, and losing, other people’s money. “In the Hammurabi Code, if a house falls in and kills you, the architect is put to death,” he told me. Correspondingly, any company or bank that gets a bailout should expect its executives to be fired, and its shareholders diluted. “If the state helps you, then taxpayers own you.”

Some of Taleb’s principles seem little more than thought experiments, or fit uneasily with others. How does one tax more locally, or close a town border? If taxpayers own corporate equities, does this mean that companies might be nationalized, broken up, or severely regulated? But asking Taleb to describe antifragility to its end is a little like asking Thomas Hobbes to nail down sovereignty. The more important challenge is to grasp the peril for which political solutions must be designed or improvised; society cannot endure with complacent conceptions of how things work. “It would seem most efficient to drive home at two hundred miles an hour,” he put it to me.“But odds are you’d never get there.”

Taleb's the closest thing we have right now to a real public intellectual/ philosopher, and he's been right about a lot of important stuff recently that virtually no one else saw coming. It's a great time to start reading his books if you're interested.
 

GrangerIrish24

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Mid January, I had every COVID symptom. Tested negative for Influenza A and B. Tested negative for strep. Fever continually spiking for days, extreme exhaustion, coughing so much my stomach hurt, shortness of breath. Pnuemonia was finally diagnosed via a chest x-ray. Did I have COVID? Most likely not, but it certainly makes me wonder if it was possible.

I went through the same thing in mid February.
 

DeSero

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Mid January, I had every COVID symptom. Tested negative for Influenza A and B. Tested negative for strep. Fever continually spiking for days, extreme exhaustion, coughing so much my stomach hurt, shortness of breath. Pnuemonia was finally diagnosed via a chest x-ray. Did I have COVID? Most likely not, but it certainly makes me wonder if it was possible.

I wouldn’t be so quick to assume that you didn’t have it. My brother just took the antibody test today and tested positive (meaning he had it and now should be immune). I’m not a medical professional and don’t pretend to be. In mid February he had a majority of the COVID symptoms including loss of taste and smell.
 

ab2cmiller

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I wouldn’t be so quick to assume that you didn’t have it. My brother just took the antibody test today and tested positive (meaning he had it and now should be immune). I’m not a medical professional and don’t pretend to be. In mid February he had a majority of the COVID symptoms including loss of taste and smell.

Problem is, even if I took an antibody test now and it came back positive, someone would just say you must have gotten in March or April and must have been asymptomatic.

Sounds like the real answer to the question is to perform more autopsies of people who died from "pneumonia" in November, December and January to see how far back this thing goes.
 

dublinirish

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<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Vince Tyra says 45 <a href="https://twitter.com/hashtag/UofL?src=hash&ref_src=twsrc%5Etfw">#UofL</a> athletics employees were notified today that they are being furloughed, initially for 60-90 days. About 40 additional employees were told their one-year contracts, which end June 30, will not be renewed.</p>— Danielle Lerner (@danielle_lerner) <a href="https://twitter.com/danielle_lerner/status/1253044680301973505?ref_src=twsrc%5Etfw">April 22, 2020</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
 

NOLAIrish

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Problem is, even if I took an antibody test now and it came back positive, someone would just say you must have gotten in March or April and must have been asymptomatic.

Sounds like the real answer to the question is to perform more autopsies of people who died from "pneumonia" in November, December and January to see how far back this thing goes.

We don't need to go that far if our only interest is in the "when" of the spread -- we have the answers in our insurance data already. There's really only one thing that drives clustered community spread of bilateral pneumonia with negative flu tests right now. Insurance data also has everything you need to detect clustering -- your residential address, work address, and immediate relatives are all readily available to your carrier's analytics team. With adequate access to the data, all you would really need is to geomap the population and hunt for your earliest cluster of symptoms in their ADT data. Back up 7-10 days and you've got likely first spread in your community.

One thing that makes me very skeptical of the studies finding extraordinarily high levels of undetected spread is just how tightly clustered symptomatic populations tend to be. When we start seeing hotspots pop up, it really burns through a community and you see a lot of symptoms. Not just in familial spread but also in clusters centered around schools or businesses, which aren't as prone to genetic confounding. If we had a ton of asymptomatic spread, I would expect the clustering to be much less tightly packed (especially in younger communities). Add to that the phenomenon of countries relaxing their distancing requirements and seeing a quick return of accelerating spread, and I think we have some decent evidence against massive underdetection.

At the same time, there's very clearly a significant level of undetected spread. The lower ends of the range in most recent studies yield some fairly believable infection rates in communities with mature outbreaks. Last I looked, I think Orleans had about 6,000 known cases (the population is about 400,000). A 10x multiple would put our infected/recovered rate around 15%. The numbers in the other major parish associated with New Orleans (Jefferson) are similar.
 

Legacy

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Bernard Avishai just published an article in The New Yorker titled "The Pandemic Isn't a Black Swan But a Portent of a More Fragile Global System":

Excerpt:
assim Nicholas Taleb is “irritated,” he told Bloomberg Television on March 31st, whenever the coronavirus pandemic is referred to as a “black swan,” the term he coined for an unpredictable, rare, catastrophic event, in his best-selling 2007 book of that title. “The Black Swan” was meant to explain why, in a networked world, we need to change business practices and social norms—not, as he recently told me, to provide “a cliché for any bad thing that surprises us.” Besides, the pandemic was wholly predictable—he, like Bill Gates, Laurie Garrett, and others, had predicted it—a white swan if ever there was one. “We issued our warning that, effectively, you should kill it in the egg,” Taleb told Bloomberg. Governments “did not want to spend pennies in January; now they are going to spend trillions.”

The warning that he referred to appeared in a January 26th paper that he co-authored with Joseph Norman and Yaneer Bar-Yam, when the virus was still mainly confined to China. The paper cautions that, owing to “increased connectivity,” the spread will be “nonlinear”—two key contributors to Taleb’s anxiety. For statisticians, “nonlinearity” describes events very much like a pandemic: an output disproportionate to known inputs (the structure and growth of pathogens, say), owing to both unknown and unknowable inputs (their incubation periods in humans, or random mutations), or eccentric interaction among various inputs (wet markets and airplane travel), or exponential growth (from networked human contact), or all three.

“These are ruin problems,” the paper states, exposure to which “leads to a certain eventual extinction.” The authors call for “drastically pruning contact networks,” and other measures that we now associate with sheltering in place and social distancing. “Decision-makers must act swiftly,” the authors conclude, “and avoid the fallacy that to have an appropriate respect for uncertainty in the face of possible irreversible catastrophe amounts to ‘paranoia.’ ” (“Had we used masks then”—in late January—“we could have saved ourselves the stimulus,” Taleb told me.)



Taleb's the closest thing we have right now to a real public intellectual/ philosopher, and he's been right about a lot of important stuff recently that virtually no one else saw coming. It's a great time to start reading his books if you're interested.

I can recommend Laurie Garrett's books, starting with "THE COMING PLAGUE: Newly Emerging Diseases in a World Out of Balance" which spent 19 weeks on the New York Times bestseller list and "BETRAYAL OF TRUST: The Collapse of Global Public Health." (I'll link her bio). The point being that her, public health/medical experts and scientists have warned about pandemics like COVID 19 for over twenty-five years with subsequent legislative acts since 2005 from Congress to establish a system that could quickly respond to them interacting with state, business, and homeland security/defense for early detection and swift coordinated action to limit a pandemic's repercussions.

I have previously linked the Pandemic Response documents from a variety of agencies tasked with developing their action plans and how federal funding was granted to states to develop theirs in preparation. Influenza was considered the most likely future pandemic cause.

Here's an example of one of the plans which is for Business from 2005.
Business Pandemic Influenza Planning Checklist

as well as DoD's from 2006 and one from 2017 has been previously linked:
Department of Defense Implementation Plan for Pandemic Influenza

The structure on the federal level at the executive branch was to be coordinated through the Dept of Homeland Security with the Director of National Intelligence. Neither have had permanent Directors for at least nine months as well as their long-time deputy assistants.

The CDC also has their Pandemic response plans linked before.
 
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NDRock

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Taleb's the closest thing we have right now to a real public intellectual/ philosopher, and he's been right about a lot of important stuff recently that virtually no one else saw coming. It's a great time to start reading his books if you're interested.

Any particular one to start with?
 

Legacy

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As far as pre-existing or underlying conditions for ICU patients that would be of most concern, you'd be most concerned with cardio-pulmonary ones - Congestive Heart Failure (CHF), Chronic Obstructive Pulmonary Disease (COPD) from long-term smoking as well as coronary and peripheral vascular disease manifested by hypertension. End stage kidney disease would make management very difficult in coronavirus patients as hemodialysis usually runs about four hours.

Diabetes and asthma could be managed without much difficulty except in those severe asthmatics who have had lung changes over decades. Vaping would definitely be problematic and should be a risk factor.

SARS-CoV-2 seems to have a greater propensity to attack the heart muscle that could also lead to heart rhythm disturbances, heart attacks as well as interfering with the heart’s ability to pump blood optimally, which is impaired in CHF to begin with. The usual interventions to monitor fluid overload and peripheral oxygenation are probably not feasible in a clinical setting where the disease proceeds so rapidly and the critical care units are so overwhelmed with the same type of patients.

But the cardiac manifestations are why many of those previously thought to have heart attacks on presentation are being examined for COVID-19 diagnoses.
 

irishff1014

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In our area the Haitian community is taking a hit. But no surprise because hygiene isn't there thing.
 

arahop

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Taleb's the closest thing we have right now to a real public intellectual/ philosopher, and he's been right about a lot of important stuff recently that virtually no one else saw coming. It's a great time to start reading his books if you're interested.[/QUOTE

He's spot on.
 

SonofOahu

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SonofOahu

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Mid January, I had every COVID symptom. Tested negative for Influenza A and B. Tested negative for strep. Fever continually spiking for days, extreme exhaustion, coughing so much my stomach hurt, shortness of breath. Pnuemonia was finally diagnosed via a chest x-ray. Did I have COVID? Most likely not, but it certainly makes me wonder if it was possible.

I went through the same thing in mid February.

You both probably had it.
 

GrangerIrish24

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You both probably had it.

Both flu tests came back negative. I had a fever for 2 days and for four days i was sleeping 16 hours at a time. Cough only lasted a day. I was given a z pack, amoxicillin, and told to stay home for a week. The weird thing was, i felt fine. I was just exhausted.
 

PerthDomer

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Where in the country do you live? While possible, mid January is exceedingly unlikely anywhere. Even in Seattle, the flu study was barely picking it up after then.
 

RDU Irish

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We don't need to go that far if our only interest is in the "when" of the spread -- we have the answers in our insurance data already. There's really only one thing that drives clustered community spread of bilateral pneumonia with negative flu tests right now. Insurance data also has everything you need to detect clustering -- your residential address, work address, and immediate relatives are all readily available to your carrier's analytics team. With adequate access to the data, all you would really need is to geomap the population and hunt for your earliest cluster of symptoms in their ADT data. Back up 7-10 days and you've got likely first spread in your community.

One thing that makes me very skeptical of the studies finding extraordinarily high levels of undetected spread is just how tightly clustered symptomatic populations tend to be. When we start seeing hotspots pop up, it really burns through a community and you see a lot of symptoms. Not just in familial spread but also in clusters centered around schools or businesses, which aren't as prone to genetic confounding. If we had a ton of asymptomatic spread, I would expect the clustering to be much less tightly packed (especially in younger communities). Add to that the phenomenon of countries relaxing their distancing requirements and seeing a quick return of accelerating spread, and I think we have some decent evidence against massive underdetection.

At the same time, there's very clearly a significant level of undetected spread. The lower ends of the range in most recent studies yield some fairly believable infection rates in communities with mature outbreaks. Last I looked, I think Orleans had about 6,000 known cases (the population is about 400,000). A 10x multiple would put our infected/recovered rate around 15%. The numbers in the other major parish associated with New Orleans (Jefferson) are similar.

If we have the answers, what are they?
 

NOLAIrish

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If we have the answers, what are they?

As with the autopsy suggestion, I don't think the analysis has been performed in a systematic way yet. It has been used in much of the public health analysis, though. When you hear a public health official referencing evidence of spread in a community at a particular time, often the support for that comes from coverage data.

Insurance data tends to be difficult to get to for research (you'd need a data sharing agreement between research epidemiologists and commercial insurers, which isn't a simple arrangement) and health insurers had a massive bandwidth problem for the first several months of this outbreak. As soon as this thing hit, every state implemented massive regulatory changes that required insurers to greatly reorganize their internal systems. This is a huge undertaking, I'd liken it to trying to turn an oil tanker around in the middle of the Mississippi. So that locks down an insurer's legal and regulatory staff, who are needed to set up the terms of the arrangement. At the same time, many major insurers linked their medical, analytic, and epidemiological staff to state public health staff to work directly on disease response. Those are exactly the people who would be working with researchers to get that kind of project off the ground, and it's just been much more important in the immediate response to have them working on resource allocation and disease mitigation efforts. As we start to get our arms around this thing, though, those issues will subside, and I think that's probably our simplest course to really finding it.
 

Irishize

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If we have the answers, what are they?

NOLA is referring (I think anyway...LOL) to claims data from insurance companies. It’s probably one of the better indicators right now depending on how broad the net is cast.
 

Irishize

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4.4 million additional people file for unemployment this week, taking us to over 26 million lost jobs
 

RDU Irish

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As with the autopsy suggestion, I don't think the analysis has been performed in a systematic way yet. It has been used in much of the public health analysis, though. When you hear a public health official referencing evidence of spread in a community at a particular time, often the support for that comes from coverage data.

Insurance data tends to be difficult to get to for research (you'd need a data sharing agreement between research epidemiologists and commercial insurers, which isn't a simple arrangement) and health insurers had a massive bandwidth problem for the first several months of this outbreak. As soon as this thing hit, every state implemented massive regulatory changes that required insurers to greatly reorganize their internal systems. This is a huge undertaking, I'd liken it to trying to turn an oil tanker around in the middle of the Mississippi. So that locks down an insurer's legal and regulatory staff, who are needed to set up the terms of the arrangement. At the same time, many major insurers linked their medical, analytic, and epidemiological staff to state public health staff to work directly on disease response. Those are exactly the people who would be working with researchers to get that kind of project off the ground, and it's just been much more important in the immediate response to have them working on resource allocation and disease mitigation efforts. As we start to get our arms around this thing, though, those issues will subside, and I think that's probably our simplest course to really finding it.

Appreciate your insights - you just made it sound like this data was regularly monitored in real time. Sounds as if the groundwork was not in place to use the best data for the best result, ASAFP - not shocking.
 
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