Covid 19 SANITY

Medium is a blog-hosting website.  That GOP-tech-bro dude had lots of neat charts but there's nothing "news" about his post.  It's an opinion piece which he posted on his blog.  Fox News amped it up so it got a lot of traffic but it's still just an opinion piece posted to a blog.  

I didn’t think the guy “debunking” it did any actual debunking. That being said, it was probably entirely too soon to draw any information from incomplete data.
Supposedly, this article from a Stanford Epidemiologist backs up the medium guy’s claims. I haven’t read it...because at this point we’re all isolating so we will see where we are in a few weeks.

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

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

FWIW 22K+ deaths/30+ Million people (US) who have had a Conventional Flu-so far this year.
Under 700 deaths/US (due to Corona) as of right now. I understand the basic factors of concern though. Conventional vs. Corona BTW.

Still the numbers don't bear "doom and gloom"-as of yet here.
Chris
P.S. In 2017 1.7+ million died of TB worldwide. Hardly heard a peep, in the News comparatively.

No one is saying you ignore this. No one.

At this point, government intervention - or perhaps I should say proposed government intervention - along with measures already in place stand a very real chance of toppling the US economy. Maybe for good. I don't know. I'm no expert. But our family does have rental properties that are paid off, and renters that probably won't pay rent very soon thanks to terrorized citizens and politicians. -- and -- we have 90+ y/o family members who reliant on that rent to live and eat. Not having to pay a mortgage doesn't help them.  From how I understand it, its a plan that favors the indebted, and penalizes the frugal.  Ugly times.

The Covid situation is grim no doubt about it. Damned if you do, damned if you don't.  But from where I'm sitting today, the "fix" may create a far bigger problem than Covid could ever be. Time will tell. But I hope none of you ever plan on retiring.

Interesting.  He's got some valid points.  But I have no idea if he's right.

Because they completely shut everything down. It will be a really good sign if it doesn’t spike right back up when they open things back up.

All this draconian stuff is just to prevent *immediate* collapse of the healthcare system. It works, short term. What happens in China as they relax restrictions will be a critically important indicator for us as far as how to proceed. Same with Italy of course, they’re just not as far along.

Good news out today about how slow the virus is mutating. Bodes well for an eventual vaccine having some longevity.

Yes - my understanding is that it was never so much about limiting infection, more about slowing infection so it didn’t all happen at once, overwhelming the hospitals. It’s a catch all to quarantine everyone. South Korea tested majorities and it allowed them to identify the sick and quarantine them. We haven’t had tests for a myriad of reasons. Bad planning, bureaucracy, over regulation, shock and more bureaucracy. But 51 mm people in South Korea is different than 350 mm people in the US.

Sorry to hear this, regarding NZ.

Hindsight is 20/20, but if the US-for example-had shut down ALL International Flights into the US (other than "essential travel")
some time back... Well you get my drift.
Chris

This from two Stanford professors:

www.google.com/amp/s/www.wsj.com/amp/articles/is-the-coronavirus-as-deadly-as-they-say-11585088464

Is the Coronavirus as Deadly as They Say?
Current estimates about the Covid-19 fatality rate may be too high by orders of magnitude.

The latter rate is misleading because of selection bias in testing. The degree of bias is uncertain because available data are limited. But it could make the difference between an epidemic that kills 20,000 and one that kills two million. If the number of actual infections is much larger than the number of cases—orders of magnitude larger—then the true fatality rate is much lower as well. That’s not only plausible but likely based on what we know so far.

Population samples from China, Italy, Iceland and the U.S. provide relevant evidence. On or around Jan. 31, countries sent planes to evacuate citizens from Wuhan, China. When those planes landed, the passengers were tested for Covid-19 and quarantined. After 14 days, the percentage who tested positive was 0.9%. If this was the prevalence in the greater Wuhan area on Jan. 31, then, with a population of about 20 million, greater Wuhan had 178,000 infections, about 30-fold more than the number of reported cases. The fatality rate, then, would be at least 10-fold lower than estimates based on reported cases.

Next, the northeastern Italian town of Vò, near the provincial capital of Padua. On March 6, all 3,300 people of Vò were tested, and 90 were positive, a prevalence of 2.7%. Applying that prevalence to the whole province (population 955,000), which had 198 reported cases, suggests there were actually 26,000 infections at that time. That’s more than 130-fold the number of actual reported cases. Since Italy’s case fatality rate of 8% is estimated using the confirmed cases, the real fatality rate could in fact be closer to 0.06%.

In Iceland, deCode Genetics is working with the government to perform widespread testing. In a sample of nearly 2,000 entirely asymptomatic people, researchers estimated disease prevalence of just over 1%. Iceland’s first case was reported on Feb. 28, weeks behind the U.S. It’s plausible that the proportion of the U.S. population that has been infected is double, triple or even 10 times as high as the estimates from Iceland. That also implies a dramatically lower fatality rate.

The best (albeit very weak) evidence in the U.S. comes from the National Basketball Association. Between March 11 and 19, a substantial number of NBA players and teams received testing. By March 19, 10 out of 450 rostered players were positive. Since not everyone was tested, that represents a lower bound on the prevalence of 2.2%. The NBA isn’t a representative population, and contact among players might have facilitated transmission. But if we extend that lower-bound assumption to cities with NBA teams (population 45 million), we get at least 990,000 infections in the U.S. The number of cases reported on March 19 in the U.S. was 13,677, more than 72-fold lower. These numbers imply a fatality rate from Covid-19 orders of magnitude smaller than it appears.

How can we reconcile these estimates with the epidemiological models? First, the test used to identify cases doesn’t catch people who were infected and recovered. Second, testing rates were woefully low for a long time and typically reserved for the severely ill. Together, these facts imply that the confirmed cases are likely orders of magnitude less than the true number of infections. Epidemiological modelers haven’t adequately adapted their estimates to account for these factors.

The epidemic started in China sometime in November or December. The first confirmed U.S. cases included a person who traveled from Wuhan on Jan. 15, and it is likely that the virus entered before that: Tens of thousands of people traveled from Wuhan to the U.S. in December. Existing evidence suggests that the virus is highly transmissible and that the number of infections doubles roughly every three days. An epidemic seed on Jan. 1 implies that by March 9 about six million people in the U.S. would have been infected. As of March 23, according to the Centers for Disease Control and Prevention, there were 499 Covid-19 deaths in the U.S. If our surmise of six million cases is accurate, that’s a mortality rate of 0.01%, assuming a two week lag between infection and death. This is one-tenth of the flu mortality rate of 0.1%. Such a low death rate would be cause for optimism.

This does not make Covid-19 a nonissue. The daily reports from Italy and across the U.S. show real struggles and overwhelmed health systems. But a 20,000- or 40,000-death epidemic is a far less severe problem than one that kills two million. Given the enormous consequences of decisions around Covid-19 response, getting clear data to guide decisions now is critical. We don’t know the true infection rate in the U.S. Antibody testing of representative samples to measure disease prevalence (including the recovered) is crucial. Nearly every day a new lab gets approval for antibody testing, so population testing using this technology is now feasible.

If we’re right about the limited scale of the epidemic, then measures focused on older populations and hospitals are sensible. Elective procedures will need to be rescheduled. Hospital resources will need to be reallocated to care for critically ill patients. Triage will need to improve. And policy makers will need to focus on reducing risks for older adults and people with underlying medical conditions.

A universal quarantine may not be worth the costs it imposes on the economy, community and individual mental and physical health. We should undertake immediate steps to evaluate the empirical basis of the current lockdowns.

Dr. Bendavid and Dr. Bhattacharya are professors of medicine at Stanford. Neeraj Sood contributed to this article.

It’s an educated opinion by two EPIDEMIOLOGISTS.

Pardon me. They’re both Medical doctors and one has a PhD in Economics as well. I see you conveniently left out that Bendavid’s Clinical Focus is on Infectious Disease. And if you think anything coming out of Stanford is right wing policy wonking, then you’ve jumped the shark.