Results for “Tests” 710 found
9. Model this (Australian camel plunge, multi-camel plunge in fact).
11. How do the CRISPR tests for Covid-19 work? (pretty amazing stuff).
12. Are panviral defenses a real option? (NYT)
13. The Quebec plan for school reopening — feasible or not?
The COVID-19 crisis is accelerating a long-term trend, the shift to online education. I’ve long argued that online education is superior to traditional models. In an excellent essay in the New York Times, Veronique Mintz, an eighth-grade NYC student agrees:
Talking out of turn. Destroying classroom materials. Disrespecting teachers. Blurting out answers during tests. Students pushing, kicking, hitting one another and even rolling on the ground. This is what happens in my school every single day.
You may think I’m joking, but I swear I’m not…during my three years of middle school, these sorts of disruptions occurred repeatedly in any given 42-minute class period.
That’s why I’m in favor of the distance learning the New York City school system instituted when the coronavirus pandemic hit.
…Distance learning gives me more control of my studies. I can focus more time on subjects that require greater effort and study. I don’t have to sit through a teacher fielding questions that have already been answered.
…This year I have struggled with math. The teacher rarely had the patience for questions as he spent at least a third of class time trying to maintain order. Often, when I scheduled time to meet with him before school, there would be a pileup at his door of students who also had questions. He couldn’t help us all in 20 minutes before first period. Other times he just wouldn’t show up….With distance learning, all of that wasted time is eliminated. I stop, start and even rewind the teacher’s recording when I need to and am able to understand the lesson on the day it’s taught.
Veronique’s online courses were put together in a rush. Imagine how much more she will learn when we invest millions in online classes and teach at scale. The online classes that Tyler and I teach, using Modern Principles and the Sapling/Achieve online course management system, took years to produce and feature high quality videos and sophisticated assessment tools including curve shifting (not just multiple-choice), empirical questions based on FRED, and adaptive practice–plus the videos are all subtitled in multiple languages, they can be sped up or slowed down, watched at different times of the day in different time zones and so forth. Moreover, technology is increasing the advantages of online education over time.
Those who grew up in East Germany seem to have a harder time cottoning to the realities of capitalism:
We analyze the long-term effects of living under communism and its anticapitalist doctrine on households’ financial investment decisions and attitudes towards financial markets. Utilizing comprehensive German brokerage data and bank data, we show that, decades after Reunification, East Germans still invest significantly less in the stock market than West Germans. Consistent with communist friends-and-foes propaganda, East Germans are more likely to hold stocks of companies from communist countries (China, Russia, Vietnam) and of state-owned companies, and are unlikely to invest in American companies and the financial industry. Effects are stronger for individuals exposed to positive “emotional tagging,” e.g., those living in celebrated showcase cities. Effects reverse for individuals with negative experiences, e.g., environmental pollution, religious oppression, or lack of (Western) TV entertainment. Election years trigger further divergence of East and West Germans. We provide evidence of negative welfare consequences due to less diversified portfolios, higher-fee products, and lower risk-adjusted returns.
That is from a new NBER paper by Christine Laudenbach, Ulrike Malmendier, and Alexandra Niessen-Ruenzi.
But if you are looking for a contrary point of view, consider this new paper by Sascha O. Becker, Lukas Mergele, and Ludger Woessmann:
German separation in 1949 into a communist East and a capitalist West and their reunification in 1990 are commonly described as a natural experiment to study the enduring effects of communism. We show in three steps that the populations in East and West Germany were far from being randomly selected treatment and control groups. First, the later border is already visible in many socio-economic characteristics in pre-World War II data. Second, World War II and the subsequent occupying forces affected East and West differently. Third, a selective fifth of the population fled from East to West Germany before the building of the Wall in 1961. In light of our findings, we propose a more cautious interpretation of the extensive literature on the enduring effects of communist systems on economic outcomes, political preferences, cultural traits, and gender roles
That said, I still believe that communism really matters, and durably so, even if the longer history matters all the more so. And now there is yet another paper on East Germany and political path dependence, by Luis R. Martinez, Jonas Jessen, and Guo Xu:
This paper studies costly political resistance in a non-democracy. When Nazi Germany surrendered in May 1945, 40% of the designated Soviet occupation zone was initially captured by the western Allied Expeditionary Force. This occupation was short-lived: Soviet forces took over after less than two months and installed an authoritarian regime in what became the German Democratic Republic (GDR). We exploit the idiosyncratic line of contact separating Allied and Soviet troops within the GDR to show that areas brieﬂy under Allied occupation had higher incidence of protests during the only major episode of political unrest in the GDR before its demise in 1989 – the East German Uprising of 1953. These areas also exhibited lower regime support during the last free elections in 1946. We argue that even a “glimpse of freedom” can foster civilian opposition to dictatorship.
I take the core overall lesson to be that the eastern parts of Germany will experience significant problems for some time to come.
And speaking of communist persistence, why is it again that Eastern Europe is doing so well against Covid-19? Belarus is an extreme case, with hardly any restrictions on activity, and about 14,000 cases and 89 deaths. You might think that is a cover-up, but the region as a whole has been quite robust and thus it is unlikely to be a complete illusion. And no, it doesn’t seem to be a BCG effect.
Does communism mean there is less of a culture of consumption and thus people find it easier to just stay at home voluntarily? Or have all those weird, old paranoid communist pandemic ministries persisted and helped with the planning? Or what?
Double credit on this one to both Kevin Lewis and Samir Varma, neither less excellent in his conjunction with the other.
NYTimes: Around the world, scientists are racing to develop and mass produce reliable antibody tests that public health experts say are a crucial element in ending the coronavirus lockdowns that are causing economic devastation. But that effort is being hamstrung, scientists say, by a shortage of the blood samples containing antibodies to Covid-19, the disease caused by the virus, that are needed to validate the tests.
Recognizing a rare opportunity, some companies are seeking to cash in on the shortages, soliciting blood donations and selling samples at rich markups in a practice that has been condemned by medical professionals as, at the very least, unethical.
“I’ve never seen these prices before,” said Dr. Joe Fitchett, the medical director of Mologic, one of the British test manufacturers that was offered the blood samples. “It’s money being made from people’s suffering.”
I am reminded of Walter Williams who asks his students whether it is wrong to profit from the misfortune of others:
But I caution them with some examples. An orthopedist profits from your misfortune of having broken your leg skiing. When there’s news of a pending ice storm, I doubt whether it saddens the hearts of those in the collision repair business. I also tell my students that I profit from their misfortune — their ignorance of economic theory.
A price is a signal wrapped up in an incentive so if you want a strong signal and a strong incentive you need to let prices rise. The prices in this case don’t even seem that high:
From March 31 to April 22, prices asked by Cantor BioConnect for its cheapest samples — always sold by the milliliter, the equivalent of less than a quarter of a teaspoon — rose more than 40 percent, to $500 from $350.
Bear in mind the costs of collecting the sample, including nurse time and PPE. Some samples which are especially rich in antibodies, do sell for prices that are well above cost which is not surprising as those samples are in high demand as they may offer a cure.
Do the firms willing and able to pay the highest prices necessarily have the best science? No, not necessarily, but on balance the decentralized allocation process offered by markets and civil society will likely be far more effective than centralized, political allocation. We also know from field experiments around the world that higher prices for blood increase supply, a key consideration.
As Hayek said the moral rules of the tribe which appear natural to us–like don’t profit from misery–cannot maintain a civilization so we struggle between what we think is right and what actually works to prevent misery.
There can be no doubt that our innate moral emotions and instincts were acquired in the hundreds of thousand years—probably half a million years—in which Homo sapiens lived in small hunting and gathering groups and developed a physiological constitution which governed his innate instincts. These instincts are still very strong in us. Yet civilization developed by our gradually learning cultural rules which were transmitted by teaching and which served largely to restrain and suppress some of those natural instincts.
1. Black hole in the outer solar system? By Edward Witten.
5. Peruvian indigenous rap (NYT).
7. The culture that was French: France to sell some of nation’s antique furniture to support hospitals.
9. The culture that is Japan: should you video chat your local aquarium eel?
Want to know how many tuberculosis cases there were in the U.S. last year? Ask the CDC. Want to know about health-care-associated infections? Ask the CDC. It knows.
But ask how many Covid-19 tests have been done, and the CDC’s doesn’t have an answer. Want a daily update on how many people are getting hospitalized for Covid-19? The CDC isn’t tracking it. Want to know if social distancing is making a difference? The CDC doesn’t know.
During this pandemic, when accurate, timely, nationwide information is the lifeblood of our response, the CDC has largely disappeared.
The performance of the world’s leading public health agency has been surprising, and by that I mean surprisingly disappointing. When the outbreak began, the CDC decided to forgo using the World Health Organization’s testing kit for Covid-19 and build its own. The test it shipped out to states was faulty, creating problems that stretched for weeks and slowed response as states waited for replacement tests.
Here is more from Ashish K. Jha. As I’ve said before, our regulatory state has been failing us.
Most of epidemiological models applied for COVID-19 do not consider heterogeneity in infectiousness and impact of superspreaders, despite the broad viral loading distributions amongst COVID-19 positive people (1-1 000 000 per mL). Also, mass group testing is not used regardless to existing shortage of tests. I propose new strategy for early detection of superspreaders with reasonable number of RT-PCR tests, which can dramatically mitigate development COVID-19 pandemic and even turn it endemic. Methods I used stochastic social-epidemiological SEIAR model, where S-suspected, E-exposed, I-infectious, A-admitted (confirmed COVID-19 positive, who are admitted to hospital or completely isolated), R-recovered. The model was applied to real COVID-19 dynamics in London, Moscow and New York City. Findings Viral loading data measured by RT-PCR were fitted by broad log-normal distribution, which governed high importance of superspreaders. The proposed full scale model of a metropolis shows that top 10% spreaders (100+ higher viral loading than median infector) transmit 45% of new cases. Rapid isolation of superspreaders leads to 4-8 fold mitigation of pandemic depending on applied quarantine strength and amount of currently infected people. High viral loading allows efficient group matrix pool testing of population focused on detection of the superspreaders requiring remarkably small amount of tests. Interpretation The model and new testing strategy may prevent thousand or millions COVID-19 deaths requiring just about 5000 daily RT-PCR test for big 12 million city such as Moscow.
Speculative, but I believe this is the future of our war against Covid-19.
The paper is by
In the worldwide race for a vaccine to stop the coronavirus, the laboratory sprinting fastest is at Oxford University.
Most other teams have had to start with small clinical trials of a few hundred participants to demonstrate safety. But scientists at the university’s Jenner Institute had a head start on a vaccine, having proved in previous trials that similar inoculations — including one last year against an earlier coronavirus — were harmless to humans. That has enabled them to leap ahead and schedule tests of their new coronavirus vaccine involving more than 6,000 people by the end of next month, hoping to show not only that it is safe, but also that it works.
The Oxford scientists now say that with an emergency approval from regulators, the first few million doses of their vaccine could be available by September — at least several months ahead of any of the other announced efforts — if it proves to be effective.
Here is more from the NYT. I do not have a personal opinion on the specifics of this development, but it seems worth passing along.
The latest relief bill contains another $320 billion in small business relief and $25 billion for testing. Finally, we get some serious money to actually fight the virus. But as Paul Romer pointed out on twitter, this is less than half of what we spend on soft drinks!!! (Spending on soft drinks is about $65 billion annually). Soda is nice but it is not going to save lives and restart the economy. Despite monumental efforts by BARDA and CEPI we are also not investing enough in capacity for vaccine production so that if and when when a vaccine is available we can roll it out quickly to everyone (an issue I am working on).
The failure to spend on actually fighting the virus with science is mind boggling. It’s a stunning example of our inability to build. By the way, note that this failure has nothing to do with Ezra Klein’s explanation of our failure to build, the filibuster. Are we more politically divided about PCR tests than we are about unemployment insurance? I don’t think so yet we spend on the latter but not the former. The rot is deeper. A failure of imagination and boldness which is an embarrassment to the country that put a man on the moon.
In Launching the Innovation Renaissance I said the US was a welfare/warfare state and no longer an innovation state. The share of R&D in the Federal Budget, for example, has diminished from about 12% at its height in the NASA years to an all time low of about 3% in recent years. We are great at spending on welfare and warfare but all that spending has crowded out spending on innovation and now that is killing us.
That is the topic of my latest Bloomberg column, here is one excerpt:
If an infected but asymptomatic worker shows up at work and sickens coworkers, for example, should the employer be liable? The answer is far from obvious. Liability exists not to shift unmanageable risk, but rather to induce management to take possible and prudent measures of precaution.
Another problem with liability law in this context is that the potential damages are high relative to the capitalization of most businesses. Covid-19 cases often pop up in chains; there have been many cases from a single conference, or in a single church choir, or on a single cruise ship. If a business or school is host to such a chain, it could be wiped out financially by lawsuits. In these cases the liability penalties do not have their intended deterrent effect because the money to lose simply isn’t there…
Another problem with liability in this setting has to do with jury expertise. Are random members of the public really the best people to determine acceptable levels of Covid-19 risk and appropriate employer precautions? Juries are better suited for more conventional applications of liability law, such as when the handyman fixing your roof falls off your rickety ladder. Given the unprecedented nature of the current situation, many Covid-19 risk questions require experts.
Finally, there is the issue of testing. Businesses could be of immeasurable help by testing their employees for Covid-19, as additional testing can help limit the spread of the virus (if only by indicating which workers should stay home or get treatment). Yet the available tests are highly imperfect, especially with false negatives. If businesses are liable for incorrect test results, and their possible practical implications, then business will likely not perform any tests at all, to the detriment of virtually everybody.
I recommend modest liability for some sectors, and zero liability, bundled with a New Zealand-like accident compensation system, for other sectors. And of course some very dangerous sectors should not be allowed to reopen at all, though I am more sympathetic to regional experimentation than are some people on Twitter.
Led by Danielle Allen and Glen Weyl, the Safra Center for Ethics at Harvard has put out a Roadmap to Pandemic Resilience (I am a co-author along with others). It’s the most detailed plan I have yet seen on how to ramp up testing and combine with contact tracing and supported isolation to beat the virus.
One of the most useful parts of the roadmap is that choke points have been identified and solutions proposed. Three testing choke points, for example, are that nasal swaps make people sneeze which means that health care workers collecting the sample need PPE. A saliva test, such as the one just approved, could solve this problem. In addition, as I argued earlier, we need to permit home test kits especially as self-swab from near nasal appears to be just as accurate as nasal swabs taken by a nurse. Second, once collected, the swab material is classified as a bio-hazard which requires serious transport and storage safety requirements. A inactivation buffer, however, could kill the virus without killing the RNA necessary for testing and thus reduce the need for bio-safety techniques in transportation which would make testing faster and cheaper. Finally, labs are working on reducing the reagents needed for the tests.
Understanding the choke points is a big step towards increasing the quantity of tests.
2. An extensive and pretty devastating article on the testing fail of the CDC. Again, our regulatory state has been failing us. And coverage from the NYT.
3. At the margin: “Results show that informants were given approximately 70 East German marks worth of rewards more per year in the areas that had access to WGTV, as compared with areas with no reception—ironically an amount roughly equivalent to the cost of an annual East German TV subscription.”
5. Scott Sumner watch the islands. This piece seems to imply that in-migration is a major source of heterogeneity. I’ve also been receiving some emails from Xavier suggested tourist inflow is a major cause of heterogeneity, due to an ever fresh supply of hard to trace cases. No rigorous test yet of that one, but it is certainly in the running as a hypothesis. And if true, it suggests many parts of Africa may not be hit that hard.
10. Beloit University moves to more flexible two-course module system. For now at least.
In a post titled Defensive Gun Use and the Difficult Statistics of Rare Events I pointed out that it’s very easy to go wrong when estimating rare events.
Since defensive gun use is relatively uncommon under any reasonable scenario there are many more opportunities to miscode in a way that inflates defensive gun use than there are ways to miscode in a way that deflates defensive gun use.
Imagine, for example, that the true rate of defensive gun use is not 1% but .1%. At the same time, imagine that 1% of all people are liars. Thus, in a survey of 10,000 people, there will be 100 liars. On average, 99.9 (~100) of the liars will say that they used a gun defensively when they did not and .1 of the liars will say that they did not use a gun defensively when they did. Of the 9900 people who report truthfully, approximately 10 will report a defensive gun use and 9890 will report no defensive gun use. Adding it up, the survey will find a defensive gun use rate of approximately (100+10)/10000=1.1%, i.e. more than ten times higher than the actual rate of .1%!
Epidemiologist Trevor Bedford points out that a similar problem applies to tests of COVID-19 when prevalence is low. The recent Santa Clara study found a 1.5% rate of antibodies to COVID-19. The authors assume a false positive rate of just .005 and a false negative rate of ~.8. Thus, if you test 1000 individuals ~5 will show up as having antibodies when they actually don’t and x*.8 will show up as having antibodies when they actually do and since (5+x*.8)/1000=.015 then x=12.5 so the true rate is 12.5/1000=1.25%, thus the reported rate is pretty close to the true rate. (The authors then inflate their numbers up for population weighting which I am ignoring). On the other hand, suppose that the false positive rate is .015 which is still very low and not implausible then we can easily have ~15/1000=1.5% showing up as having antibodies to COVID when none of them in fact do, i.e. all of the result could be due to test error.
In other words, when the event is rare the potential error in the test can easily dominate the results of the test.
Addendum: For those playing at home, Bedford uses sensitivity and specificity while I am more used to thinking about false positive and false negative rates and I simplify the numbers slightly .8 instead of his .803 and so forth but the point is the same.
Here is the short essay, opening excerpt:
Every Western institution was unprepared for the coronavirus pandemic, despite many prior warnings. This monumental failure of institutional effectiveness will reverberate for the rest of the decade, but it’s not too early to ask why, and what we need to do about it.
Many of us would like to pin the cause on one political party or another, on one government or another. But the harsh reality is that it all failed — no Western country, or state, or city was prepared — and despite hard work and often extraordinary sacrifice by many people within these institutions. So the problem runs deeper than your favorite political opponent or your home nation.
Part of the problem is clearly foresight, a failure of imagination. But the other part of the problem is what we didn’t *do* in advance, and what we’re failing to do now. And that is a failure of action, and specifically our widespread inability to *build*.
We see this today with the things we urgently need but don’t have. We don’t have enough coronavirus tests, or test materials — including, amazingly, cotton swabs and common reagents. We don’t have enough ventilators, negative pressure rooms, and ICU beds. And we don’t have enough surgical masks, eye shields, and medical gowns — as I write this, New York City has put out a desperate call for rain ponchos to be used as medical gowns. Rain ponchos! In 2020! In America!
As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Italy is substantially lower than reported.
Here is a very good tweet storm on their methods, excerpt: “What I love about this paper is its humility in the face of uncertainty.” And: “…rather than trying to get exact answers using strong assumptions about who opts-in for testing, the characteristics of the tests themselves, etc, they start with what we can credibly know about each to build bounds on each of these quantities of interest.”
I genuinely cannot give a coherent account of “what is going on” with Covid-19 data issues and prevalence. But at this point I think it is safe to say that the mainstream story we have been living with for some number of weeks now just isn’t holding up.
For the pointer I thank David Joslin.