patience_and_focus

This is actually quite impressive. This is (err, was) a very hard problem. I had the fortune of being part of a group of some very bright minds when they were working on this protein folding problem back in the day and participating in CASP (the competition that AlphaFold won this year by a 2.5X margin to its nearest competitor). It is a crazy and stunning advance, the effect of which cannot be overstated. This could be as significant as human genome sequencing. Because if sequencing the genome was equivalent to translating a book of "unknown" language to english then this advance is equivalent to creating a play out of the characters of the book, understanding them and see in real life how they potentially function and play their part in the human body.

This is pretty cool resource. Thank you!

Make sense though. Large city with many renters, large population of young and single people and high cost. But I bet Seattle suburbs are white hot. I'm throwing 700k cash offers at 3bed/1bath 1,000 sq ft houses in the east bay of San Francisco. I'm not even competitive apparently... Suburbs have largely lacked the price appreciating that Appartement or houses in the city areas had. I lived in Long Island and now in Boston area and in both cases, houses were still below ~2005 prices. I think RE in thr city core might have doubled with8b the same time frame. If this trend reverses, it could have a long way to go, but I somehow doubt that it will. Actually good bay area suburban housing has been on fire since a couple of years after the GFC. The suburban city of Burlingame (17 miles south of San Francisco) has seen a 2.5X price rise for single family homes in the last 10 years (Dec-2010 to now). That is annualized appreciation of nearly 10%. If you take last 25 years for this suburb that number comes to about 7.5% annualized which is rivaling S&P returns (without dividends reinvested of-course). https://www.zillow.com/burlingame-ca/home-values/ For comparison San Francisco (SF) has appreciated "only" 2X in the last 10 years for single family homes (7.5% annualized) and about 4X in the last 25 years (for a return of 6% annualized). SF Zillow: https://www.zillow.com/san-francisco-ca/home-values/ SF Case Shiller: https://fred.stlouisfed.org/series/SFXRSA

I think my comment is being taken out of context and this issue is becoming unnecessarily emotional as opposed to invoking rational thought. So let me clarify. My comment of masks not being shown to be effective so far was in the context of multiple previous posts specifically on covid studies that are being cited to argue in favor of or against effectiveness of masks to prevent infection for the wearer (not source control). I am not making any general claims about masks, especially for source control. Also I was clear that so far there is absence of evidence that is coming from gold standard randomized controlled trials that unequivocally show effectiveness in that context. I am fully aware that absence of evidence is not evidence of absence. However, given what we know so far, wearing masks just by themselves is unlikely to show very high effectiveness to prevent getting infected in such studies. This may be partly due to difficulty in getting a large enough study going for something that is behavioral or masks may be more effective when combined with other non pharmaceutical interventions. But such trials have not been conducted. By the way, I do wear mask in public. It has more to do with lack of harm doing it and potential for source control (in the unlikely situation of source being myself) than proof of preventative intervention.

First off I want to say I am of the view that there isn't currently conclusive evidence that masks are effective. There is also not conclusive evidence that masks are not effective. In this regard we may be in agreement (at least partially). Now for the sample size. It is not large. This is clear from the confidence intervals (potential range of possible outcomes in 95% confidence interval is very large). Typically you get large intervals when sample size is small. There is another very important reason why I say this. Look at the sample size of Pfizer/BioNtech or Morderna trials. They are 10X the size of this trial. Pfizer trial had ~44000 participants. The goal was very similar, to assess whether an intervention (in this case a vaccine as opposed to masks) is effective in preventing future infections. The reason why this large sample size (~44000) is needed is to be able to power the study enough to convincingly make a call one way or another in this infectious disease setting. Same is true for any other intervention study (vaccine, therapeutic or non pharmaceutical interventions such as masks).

This is absolutely interesting in-depth deep dive report published by UnitedHealth group's foundation - (a) Cannot claim its leftist - although for some here if its not Brietbart or Q then its not authentic. (b) Almost all top 15 barring 2 are blue states, all bottom 15 barring 1 are red states. © The most interesting aspect to me is not the current ranking but how ranking for each moved over time in the last 30 years from 1990 to 2019 (see page 12). Most (currently) blue states improved their ranking or stayed the same. Most (currently) red states got worse. E.g.: New Jersey moved from being 21 to 8, New York from 40 to 11, Iowa from 6 to 20, and North Dakota went from #1 in 1990 to being #14. There is definitely a time correlation between becoming blue over time and better health of its residents. Inverse is also true, becoming red over time and making its residents poor in health.

From the article - "AI should not waste time trying to understand the viewpoints of people who distrust artificial intelligence for a living." Who has the day time job as "distruster" of AI?? GPT-3, are you looking at me. :o

AstraZeneca Covid-19 vaccine study put on hold due to suspected adverse reaction in participant in the U.K. https://www.statnews.com/2020/09/08/astrazeneca-covid-19-vaccine-study-put-on-hold-due-to-suspected-adverse-reaction-in-participant-in-the-u-k/

I'm not gonna defend the results. However, what in your (and author's) opinion should have been done? The simple answer is not having exams at all. Would that have worked better for poor kids? Colleges would have been forced to use the same (or similar) info for their admissions that the computer used for exam: "an array of student information, including teacher-estimated grades and past performance by students in each school". There is also a conclusion by author: "Algorithms should not be used to assign student grades." This is bullcrap. First of all, they already are with pretty much zero opposition: https://www.ets.org/gre/revised_general/scores/how/ (yeah, human is in the loop, but still) Second, the answer is to improve algorithms rather than discard them. Author also is wrong on a number of other counts: they don't agree with "Computers make neutral decisions" - yeah, computers can have bias, but human graders definitely have bias - and are susceptible to fatigue, misunderstandings, and even fraud. I'd guess that's one of the reasons why ETS uses algorithmic scorer in addition to human one. Author tries to score a lot of points with claims: "Algorithms can’t monitor or detect hate speech, ... they can’t predict crime, they can’t determine which job applicants are more suited than others, they can’t do effective facial recognition" - except that algorithms can do all of these and they do all of these and they are getting better in doing all of these. Yeah, you can prohibit using AI for facial recognition by law, but it does not mean that algorithms are or won't be better in recognizing people than people are. Anyway, it sucks to be caught in this, but the way to go is to improve algorithms rather than giving up and going back to warm and fuzzy human-graded default. Yeah, I didn't claim that use of algorithms is bad in all cases (I'm not a luddite). Also the author is certainly biased herself in many ways. But I do think the academic process such as admission is opaque to start with, has become highly political and contentious with emotions running high. We don't need another dose of opaque criterion in this mix right now. If we can lay out the rules of the game beforehand, that will help (this applies to the current process as well). The way I understood, there was no attempt to explain how the algorithm reached its decision (for example provide weight on each of the factors chosen by the algorithm). Without transparency this is a recipe for disaster.

Reviving this thread. This is unfortunate use of algorithms/machine learning/AI. When Algorithms Give Real Students Imaginary Grades https://www.nytimes.com/2020/09/08/opinion/international-baccalaureate-algorithm-grades.html

This is absolutely fascinating. Scientists, independently of this finding above, are also trying to now create a "lattice-work of models" from so many different streams of data and findings and putting them all together. Impressive that it has happened in less than 1 year of first reporting this virus. A model like this, even with some errors here and there, is going to be invaluable to further improve discovery of new treatments and medical practice. Another example of such a model is in cancer immunotherapy with the understanding of cancer immunity cycle (see https://www.roche.com/research_and_development/what_we_are_working_on/oncology/cancer-immunotherapy/cancer-immunotherapy-cycle.htm). It took at least 30 years to get here for this one.

Fact check: sales of one company's divorce software are up 34%. Exactly. If only someone would do a simple click to the original source article from the ny post page, it also has following - "During the COVID-19 crisis, we experienced the highest purchase of divorce agreements per capita in the South followed by the Midwest, the West, and the North East. The rate of divorce in the south was two to three times higher than the rest of the US regions. The Southern states with the highest divorce rates were: Mississippi Oklahoma Arkansas Alabama Louisiana" Hmmmm, so states mostly resisting lockdown had higher divorce. May be we should lock down more to save marriage instead of banning gay marriage. :o

The average person should just try to find a low cost broad based index etf or similarly low cost target date fund and call it a day. Too bad many fall into traps of "advisors." :-\ Unfortunately the reality is not that simple. Many private employers do not offer good low cost index funds but only ETF's with high fee structure (my former employer did that unknowingly - thank you outsourced HR). Employees have no control in many cases and too much hassle to go outside to set up Roth IRA or something like that due matching contributions and other benefits from the employer.

Covid-19 Is Creating a Wave of Heart Disease Emerging data show that some of the coronavirus’s most potent damage is inflicted on the heart. By Haider Warraich Dr. Warraich is a cardiologist. https://www.nytimes.com/2020/08/17/opinion/covid-19-heart-disease.html "Eduardo Rodriguez was poised to start as the No. 1 pitcher for the Boston Red Sox this season. But in July the 27-year-old tested positive for Covid-19. Feeling “100 years old,” he told reporters: “I’ve never been that sick in my life, and I don’t want to get that sick again.” His symptoms abated, but a few weeks later he felt so tired after throwing about 20 pitches during practice that his team told him to stop and rest. Further investigation revealed that he had a condition many are still struggling to understand: Covid-19-associated myocarditis. Mr. Rodriguez won’t be playing baseball this season."

Nail in the coffin Malaria Drug Chloroquine Does Not Inhibit COVID-19 Infection in Human Lung Cells https://www.nature.com/articles/s41586-020-2575-3 "These results indicate that chloroquine targets a pathway for viral activation that is not operative in lung cells and is unlikely to protect against SARS-CoV-2 spread in and between patients."

If this study is independently "replicated" by other researchers, this is very valuable information not just for clinicians on the front lines but also for patients themselves. For example, imagine a person in his/her 40's or 50's has Covid-19 like symptoms, doesn't have too many co-morbidity issues like heart disease. Given the testing mess, they also don't have the results (its taking average of 5 days or more again in many hot-spots). If the telemedicine clinic they call for advice is not useful they can at least have some idea of whether they should be driving to the nearest emergency room by matching this list and overlap with their symptoms. It may save lives.

On the other hand a cheap generic drug has actually been shown to be effective in double blind randomized clinical trials for saving lives of the very sick Covid-19 patients (hint: its not HCQ) https://fivethirtyeight.com/videos/how-a-60-year-old-drug-became-our-best-hope-for-saving-people-with-covid-19/

https://www.medrxiv.org/content/10.1101/2020.07.15.20151852v1 The mortality rate is high of about 25%. The number of days since symptom onset 9 days before medicine administration On oxygen or ventilation at baseline: 67% Many doctors who use Hydroxychloroquine say 1) It works better with Zinc, and optionally Azithromycin. 2) Works when given early but not when given later when symptoms of pneumonia have started. For example Dr. Harvey Risch from Yale says: I think that there has been confusion about treating the cold versus treating the pneumonia. These medications don’t seem to work so well for treating the pneumonia. As early as possible is crucial, within the first five to six days of symptoms. https://medicine.yale.edu/news-article/25085/ I think you are on the wrong forum trying to push for HCQ+/- other agents. You are wasting everyone's and your time here. I would suggest you either talk to like minded physicians and start a trial with your design in mind and/or fund them personally with your money for this. Another option is to do a go-fund-me site to raise money for such a trial or create a social network group of like-minded people with money to pool resources for this. It is not unheard of because there are many patient and specific drug advocacy groups around that do this kind of thing in other disease areas. Also, there will be enough physicians in this country (and participants as well) that believe in this HCQ+other agent treatment and will be willing to participate/help. In-fact you can start by contacting the docs you keep citing (given the papers you keep posting). Just to be clear, I am not being sarcastic. If you so strongly believe in this, have some skin in the game by putting your own money into it. Just like we all do when investing.

It is bullshit. Don't know if the tweet is deliberate misrepresentation or incompetence, but given its fox news reporter, it probably both. I would not recommend following twitter accounts of fox new reporters for accurate reporting. See the source here (linked in the fox new article) and specifically the table from page 25 onwards for testing by laboratory - http://ww11.doh.state.fl.us/comm/_partners/covid19_report_archive/state_reports_latest.pdf 1. The testing results by lab is sorted high to low by # of tests administered and columns show # inconclusive, # of negatives and # of positives as well. It is clear that > 90% of the data is reporting correctly all numbers - inconclusive, positive and negative numbers. 2. Not only that, this is a long tail where the first 50 or so labs (page 25) account for ~ 80% of the total test results and are correctly reported. Infact, the top lab 10 labs itself report ~ 2 million tests. 3. There are labs reporting 100% positivity (not reporting negatives - they start to show up on page 29) but they are conducting very few tests comparatively. 4. Lastly, a lot of labs have reported conducting a total of 3 tests or less (page 40 on-wards). That is a very low number of tests and it is actually quite likely that all of them turn out positive or all of them turn out negative. This is because sample size is small. In fact, many labs do report 0% positivity when # of tests are very few. Vast majority of data is solid and of-course there are labs that do not report accurately but their influence on the data is rounding error. Thankfully the FL state health dept is still competent and not yet overtly political.

NIH halts clinical trial of hydroxychloroquine https://www.nih.gov/news-events/news-releases/nih-halts-clinical-trial-hydroxychloroquine

I think we all should do some deep DD (as we do when investing) before posting on technical things like effectiveness of a treatment. Moreover, I really think these BS studies should not be published and will not be published in any reputed journal. There are plenty of substandard journals that exist where these show up and someone incompetent in the media picks it up. Here is why this is a total BS study - (a) This is an retrospective observational study, not a randomized double blind clinical trial which is the gold standard and has shown no effectiveness. (b) Look at Table 1 of this study (https://www.ijidonline.com/article/S1201-9712(20)30534-8/fulltext) - the age itself can explain the difference in mortality. The patients receiving hydroxychloroquine alone (median age = 53) were younger by 18 years on average than who received no treatment (median age = 71). We already know younger patients survive better than older ones. So the patients treated with hydroxychloroquine simply lived because they were younger. One couldn't have picked a worst retrospective dataset than this for the analysis.

It depends. Although its still unknown scientifically, one emerging trend from the data so far says that if a person gets "mild" or "moderate" disease then the antibodies fade in a few months. But in the "sufficiently" sick, they have high levels of antibodies until and after convalescent phase of the infection (recovery and after). So far, the followup time has been limited. Remember, we only have had ~5 months of real tracking of this virus in humans and the infection itself lingers for at-least month in many sick patients. So this data is very preliminary. It is well known scientifically that how long immunity will last for an infection (bacterial or viral or fungal) is very variable and depends on a lot of factors. For example polio and measles immunity (gained via an infection or a vaccine) lasts lifetime. Whereas flu lasts a year, getting tetanus infection and Hep C infection provides barely any long lasting immunity. So in short, this is so new that we don't know yet.

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". Don't think that you can attribute solely reopened bars for the increased spread. I think the widespread protests that has been occurring for a month now likely created plenty of vectors for spread. That some places are now seeing outbreaks shouldn't come as a surprise. What is a bit surprising is that NYC, by far the hardest hit city in the US, keeps seeing declines. Both are culprits but to different degrees. Bars are inside an enclosed place exposure, protests (and beaches and parks) are outside in open space exposure. This has dramatic impact on viral load and consequent spread and severity.

This is a good short read on this question - https://www.nature.com/articles/s41564-020-0690-4.pdf?proof=true1