KCLarkin

Not true. Ontario's data is much more recent than most of the serology reports in that thread. Based on his chart, he seems to by using NY serology from mid-June. But this is irrelevant since Ontario's epidemic was crushed by the end of June (a few deaths per day since).

I found this argument interesting--thanks Cherzeca. Here is why yinonw's thread is a scam: HIT = 1 - 1/Ro But yinonw invented a new thing. I will call it "wild" Herd Immunity. This is the observed level of herd immunity, given current Non-Pharmaceutical Interventions (NPI), seasonality, etc. HITw = 1 -1/Rw Earlier in this thread, I posted that Florida's recent surge was the result of a relatively modest Rw ~ 1.3. So, for Florida: HITw = 1 - 1/1.3 = 23% So, if Florida maintains "reopening levels" of NPI the epidemic would start to die out once ~23% of the population is infected. (Florida has has added more NPI since, so HITw should be lower). -- But then yinonw pulls his sleight of hand: He claims that Sweden has very modest Covid restrictions, so Rw ~ Ro. Therefore, HITw = HIT. And because HITw in Sweden is similar to other countries, he assumes that HITw = HIT in other countries too. And then he claims this means that masks, lockdowns, school closures, etc have no impact on HITw. This entire chain of assumptions is B.S. But it all starts with the flawed assumption that Sweden has no NPI. This is absolutely false. https://www.krisinformation.se/en/hazards-and-risks/disasters-and-incidents/2020/official-information-on-the-new-coronavirus/restriktioner-och-forbud https://www.gstatic.com/covid19/mobility/2020-08-11_SE_Mobility_Report_en.pdf According to Google Mobility trends, traffic to "workplaces" in Stockholm is down 50%! And, it seems like Sweden's schools are closed for the summer holidays since June: https://publicholidays.se/school-holidays/stockholm/

This thread is b.s. Toronto has a similar death chart to NYC and Stockholm. But only 1.5% of Torontonians have antibodies. So "herd immunity" is an unlikely explanation. The author mentions prisons (where attack rates are much higher than 20%) but dismisses them as "unnatural". San Quentin had 66% positive last I checked. That's a range of 1.5 - 66% But this scam is also based on the false assumption that there were no regulatory or behavioural changes in Sweden.

It is B.S. She cites the CDC as her source. The CDC has their own excess deaths tracker here: https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm Not worth anyone's time debunking this one since it is very obviously garbage. But aside from the obvious (lags in reporting deaths), I don't think she included any deaths from January, but she includes those weeks (of zero deaths) in her weekly average. The CDC source she cites only include deaths from Feb 1st. Easy way to check her work: source: https://www.cdc.gov/nchs/nvss/vsrr/COVID19/ Total Deaths: 1,671,434 Weeks (Feb 1-Aug 8): 28 Deaths per week: 59,694 (undercount due to reporting lags) In her blog, she calculates 44,752 deaths per week. She can't even do simple arithmetic. Actually, she can't even count. All she needed to do was count the weeks in the CDC data (28 not 32). PLEASE DON"T POST FAKE "RESEARCH". IT IS EASY TO CREATE THIS B.S. BUT IT IS A WASTE OF TIME TO DEBUNK.

I am saying: Why don't we look at what worked in New Zealand, Iceland, South Korea, Vietnam, China, Taiwan, Canada, Germany? And your response is to post b.s. stats comparing the population density of a major city to an entire country. Jurgis isn't Canadian and you attack him because he doesn't conform to your narrow view of America. 54% of Americans disapprove of Trump and especially his approach to Covid. Jurgis' views are more representative of "real America" than yours.

Classic. Xenophobic rant when called out for using misleading stats.

How not to science: https://www.buzzfeednews.com/article/stephaniemlee/ioannidis-trump-white-house-coronavirus-lockdowns I gave Ioannidis the benefit of the doubt on this forum. But it is pretty clear he is doing junk science. He had a political opinion (lockdowns are bad and IFR lower than experts estimates). Fair enough. But then he pushed shoddy research to justify these opinions. Classic confirmation bias. What a disgrace to Stanford.

Seriously, what hot sh** is this? Did you even look at this rubbage before posting? Ignoring that this is fraudulently claiming to be from TXDSHS, the data is bullshit. Please tell me how they calculated "recovery" rates? Using latest data: Cases reported: 275,058 Recoveries: 142,398 Recoveries/cases = 57% (my calculation) Please save your alternative facts and propaganda for your gullible Facebook friends.

But let me be explicit on my priors here: Uncontrolled community spread causes lockdowns Uncontrolled community spread decreases mobility Uncontrolled community spread decreases economic activity So he is looking at all these correlations backwards. Denmark doesn't have low infection rates despite high mobility. They have high mobility due to low infection rates. California: https://www.cnbc.com/2020/07/13/california-to-close-indoor-restaurants-movie-theaters-and-bars-statewide-as-coronavirus-cases-rise.html Texas: https://www.texastribune.org/2020/07/10/greg-abbott-shutdown-texas-mask-order/ Arizona: https://www.theguardian.com/us-news/2020/jun/29/arizona-covid-19-shutdown-rollback-bars-gyms Florida: https://www.npr.org/sections/coronavirus-live-updates/2020/07/06/887919782/in-miami-rolling-back-openings-to-contain-the-coronavirus-surge If you want to get things back to normal, stop spreading your germs all over the place.

CDC revised their estimates again. The new best estimate for IFR is 0.65%. And this time they actually cite a source. https://www.cdc.gov/coronavirus/2019-ncov/hcp/planning-scenarios.html#table-1

I'm not defending their competence (IMO the Trump-appointed CDC director is horrific and Trump has neutered the CDC). Merely pointing out your lack of knowledge on this subject. Pretty sure WHO, Fauci, and CDC don't have any jurisdiction to regulate air flow per person. Though they are convenient scapegoats for elected politicians. -- CDC Anyway, I'm done posting on this thread. I've tried to convince my American friends on here to take this seriously. Your country has chosen another path. The best I can hope for now is that our border remains closed.

Here are the CDC guidelines for ventilation

Sorry, I didn't mean that it is solely attributable to bars. But we know from South Korea, Japan, and Austria that bars are extremely risky. I'm just using that as an example of poor budgeting. Protests are relatively lower risk. But more importantly, they are non-discretionary. "Law and Order" and curfews and police crack-downs didn't make the protests go away. Police reform is a long-term problem. So you just need to accept that you will need to slow re-opening to the extent protests create outbreaks.

It is true that 30,000 cases today is not the same as 30,000 cases in April. But, the "just doing more testing" is wrong and is essentially a cover-up. Ontario is testing at roughly the same per-capita rate as Florida. And as I posted up-thread, there is actually an inverse correlation between testing in Ontario and cases. I agree that we aren't at a "gloom and doom" phase. But Texas needed to cancel elective hospital procedures because they reopened bars. This seems like a poor use of your "Rt budget".

What's happening across the South is exactly what it looks like. Terrible management (and selfish behaviour). Climate might be a factor, but you still need to manage the pandemic. Even if you are going for a herd immunity approach, you want to avoid exponential growth. You have a risk budget that balances to Rt < 1. Here is an interesting analysis I saw on twitter @imgrund: FLORIDA*: May 19th - 502 cases daily June 25th - 5552 Rt = 1.24 ONTARIO: May 19th - 502 cases daily June 25th - 189 Rt = 0.91 A relatively small difference in Rt resulted in 30x the daily cases in one month. You don't need lockdowns. You just need competent leadership and a cooperative spirit. With Rt of only 1.24, Florida will avoid a NYC outcome. But they will have a very high base level of disease. * I am using Florida as an example here because this is the data I have. But other states are worse.

Well, that was a mistake. Everyone knows Flu is seasonal (and experts assume Covid will have a second wave in the fall). The thing that doesn't make sense is that Flu season is over! Even in Arizona and Florida.

Perhaps ... https://pbs.twimg.com/media/EbTNx76UwAA6mZV?format=jpg&name=900x900 It is very curious that U.S. is the only country showing these dynamics. Canada, as an example, has increased testing but decreased cases and hospitalizations despite reopening. And our cases are also skewing younger. And it is very strange how the sunbelt was largely spared in March but seems on the edge of a major outbreak now. So weird. Are you being sarcastic? It's hard to tell. Regardless, the video literally answers your question. There's no part of Canada that's tropical, while large swaths of the US are. Thus, the US is partially like Italy (NYC) and partially like tropical regions (Tx, AZ, etc.) and we may be seeing the death curves regionally match up. No, not being sarcastic. I’ve been to many of these states, so I agree geography and climate must be responsible but haven’t seen a great explanation why. I will give your video a chance.

Perhaps ... https://pbs.twimg.com/media/EbTNx76UwAA6mZV?format=jpg&name=900x900 It is very curious that U.S. is the only country showing these dynamics. Canada, as an example, has increased testing but decreased cases and hospitalizations despite reopening. And our cases are also skewing younger. And it is very strange how the sunbelt was largely spared in March but seems on the edge of a major outbreak now. So weird.

The risk seems to be non-linear with age, so the absence of <20 year olds would cause less skew than the absence of >60 year olds. But the health comment is a fair point. Also, 3 deaths is not enough to draw meaningful conclusions.

Maybe I haven't seen this study, but the obvious drawback is that prisons (aircraft carriers, cruise ships, etc) aren't representative populations. I'm not sure about the stats in that prison, but in Canada the majority of prisoners are young (20-40) males. So a CFR of 0.23% in that population would be consistent with a much higher IFR in the wider population. Did Ionnidis attempt to make this adjustment? Naively, I'd think that data would support an age-adjusted IFR closer to 1%. I'd also be reluctant to compare death rates between countries. According to CIA World Factbook, the U.S. has twice the obesity rate of Italy. In the U.S., I'd also be worried about the disparity in health care coverage. IFR is also not static. It depends on how stretched health care capacity is and the quality of treatment (which is evolving quickly). If you read Prof. Ioannidis (yes he is the few I would give that respect in this drama), he stated very clearly in his articles, he is adjusting the profile of the studies to the US demographic profile. I don’t see the Trousdale prison “study” in this meta-analysis. Or is that in a different paper? Given how shoddy the Santa Clara study was, is there any reason (other than confirmation bias) why you still trust him? As far as I can tell, his reputation was largely destroyed with this one study.

I haven't seen this study, but the obvious drawback is that prisons (aircraft carriers, cruise ships, etc) aren't representative populations. I'm not sure about the stats in that prison, but in Canada the majority of prisoners are young (20-40) males. So a CFR of 0.23% in that population would be consistent with a much higher IFR in the wider population. Did Ionnidis attempt to make this adjustment? Naively, I'd think that data would support an age-adjusted IFR closer to 1%. I'd also be reluctant to compare death rates between countries. According to CIA World Factbook, the U.S. has twice the obesity rate of Italy. In the U.S., I'd also be worried about the disparity in health care coverage. IFR is also not static. It depends on how stretched health care capacity is and the quality of treatment (which is evolving quickly).

James, a model always relies on imperfect inputs. The subsequent research (e.g. Serology tests) is to improve the inputs. We are 6 months into this epidemic and we don't have a good answer to ANY of the inputs in Ferguson's model: IFR - most experts think it is 0.5-1.0. But there is a vocal group that think it is 0.05-0.5 R0 - Many experts think the initial estimate of 2.5 was too low, but nobody knows Herd immunity (with no interventions) - Some people think this could be as low as 20-30% (due to heterogenity, immune dark matter) or as high as 90% due to overshoot. And as you make clear, it is impossible to make sound economic tradeoffs if you don't have good answers. So a respected scientist like Ionnidias producing and amplifiying crappy research only muddies the waters.

Many seroprevalence studies have the same faults as the Santa Clara study. I've read a number of the studies he's included, and the bottom line is, seroprevalence studies are just not a great way of estimating IFR when the false positive rate of the serology tests is so high. NY just has some of the better statistics I've seen available--I just included as a proxy for general IFR estimating. I wouldn't hang my hat on those estimates, but even the population level death statistics show that it's higher than he's estimating. New tests are much more accurate. More serology large scale tests should be done. https://diagnostics.roche.com/us/en/news-listing/2020/roche-highly-accurate-antibody-test-for-covid-19-goes-live-at-more-than-20-initial-lab-sites-in-the-us.html It provides 99.8 percent specificity, Yes, that's my point. We should be looking at serology studies that used high quality tests. Not a meta-analysis of all serology studies (with varying quality in study design and test used). I'd rather read one good study than find the "median" of crappy studies.

Experts: test-trace-ISOLATE.

It is also important to remember that these serology tests do not require FDA approved. So the quality of the tests vary widely. So a meta-analysis without evaluating which tests were used seems reckless. -- Antibody tests for COVID-19 wrong up to half the time, CDC says https://www.ctvnews.ca/health/coronavirus/antibody-tests-for-covid-19-wrong-up-to-half-the-time-cdc-says-1.4956506