Category: Medicine

Why are women so prominent in vaccine development?

Here is my Bloomberg column arguing that they are prominent in vaccine development, excerpt:

Then there is the vaccine from Novovax, which is based in Gaithersburg, Maryland. The Novovax results are not yet published, but early word is that they are very promising. This vaccine also is based on new ideas, using an unusual moth cell system to crank out proteins in a highly innovative manner.

Novovax’s team is led by Nita Patel, an immigrant from Gujarat, India. Her vaccine team is identified as “all-female.” Patel is from a very poor family; her father almost died of tuberculosis when she was 4 years old, and she often had to beg for bus fare.

Immigrants too, and there is much more evidence at the link.  In fact women have been prominent in vaccine research for a long time.  But why vaccines?  What is the best hypothesis here?

New CRISPR-based COVID-19 test uses smartphone cameras to spot virus RNA

This one brings us closer to the Star Trek medical universe:

Scientists at UC Berkeley and Gladstone Institutes have developed a new CRISPR-based COVID-19 diagnostic test that, with the help of a smartphone camera, can provide a positive or negative result in 15 to 30 minutes. Unlike many other tests that are available, this test also gives an estimate of viral load, or the number of virus particles in a sample, which can help doctors monitor the progression of a COVID-19 infection and estimate how contagious a patient might be.

“Monitoring the course of a patient’s infection could help health care professionals estimate the stage of infection and predict, in real time, how long is likely needed for recovery and how long the individual should quarantine,” said Daniel Fletcher, a professor of bioengineering at Berkeley and one of the leaders of the study…

The new diagnostic test takes advantage of the CRISPR Cas13 protein, which directly binds and cleaves RNA segments. This eliminates the DNA conversion and amplification steps and greatly reduces the time needed to complete the analysis.

“One reason we’re excited about CRISPR-based diagnostics is the potential for quick, accurate results at the point of need,” [Jennifer] Doudna said. “This is especially helpful in places with limited access to testing or when frequent, rapid testing is needed. It could eliminate a lot of the bottlenecks we’ve seen with COVID-19.”

In the test, CRISPR Cas13 proteins are “programmed” to recognize segments of SARS-CoV-2 viral RNA and then combined with a probe that becomes fluorescent when cleaved. When the Cas13 proteins are activated by the viral RNA, they start to cleave the fluorescent probe. With the help of a handheld device, the resulting fluorescence can be measured by the smartphone camera. The rate at which the fluorescence becomes brighter is related to the number of virus particles in the sample.

And:

Now that the CRISPR-based assay has been developed for SARS-CoV-2, it could be modified to detect RNA segments of other viral diseases, like the common cold, influenza or even human immunodeficiency virus. The team is currently working to package the test into a device that could be made available at clinics and other point-of-care settings and that one day could even be used in the home.

“The eventual goal is to have a personal device, like a mobile phone, that is able to detect a range of different viral infections and quickly determine whether you have a common cold or SARS-Cov-2 or influenza,” Fletcher said. “That possibility now exists, and further collaboration between engineers, biologists and clinicians is needed to make that a reality.”

I recall once asking Silvana Konermann: “What am I going to buy at the CRISPR store?”  Well, this is what you are going to buy at the CRISPR store.

Here is the article.  And funded by Fast Grants, I am happy to say.  Quite the week for science, yes?

Don’t Delay a Vaccine to Allay Fear

I am getting very angry at people like Anthony Fauci who say that FDA delay is necessary or useful to alleviate vaccine hesitancy.

Fauci told Fox News that the FDA “really scrutinises the data very carefully to guarantee to the American public that this is a safe and efficacious vaccine. I think if we did any less, we would add to the already existing hesitancy on the part of many people because … they’re concerned that we went too quickly.”

The WSJ says much the same thing just with a slightly different flavor:

…this regulatory rigmarole is essentially a placebo to reassure the public it will be safe to get inoculated.

The ‘we must delay to allay’ argument is deadly and wrong.

First, we should not let public policy be guided by the most risk averse, fearful, and scientifically illiterate among us. Letting the fearful lead is a recipe for stagnation, mediocrity, and eventual collapse.

Second, there is no guarantee that the risk averse, fearful and scientifically illiterate will be convinced by extra FDA investigation and there is plenty of evidence that they won’t be. Dozens of well-done studies have found no link between vaccines and autism. The scientific evidence that vaccines don’t cause autism is very strong. Yet many people don’t care. Moreover, I bet there is a significant overlap between those who think or fear that vaccines cause autism and those who fear a COVID vaccine. Will a few weeks of extra FDA investigation win these people over? No. More science won’t end science denialism.

Third, rather than alleviating fear, FDA delay may increase fear. People may reason, if the FDA is taking this long to review the evidence when thousands of people are dying every day it must be a hard decision. Delay also makes the vaccine less useful and less obviously useful. Thus, if vaccines come too late people will say that we were reaching herd immunity anyway and that vaccines are useless.

Thus, when thinking about how much investigation the FDA should do before approving a vaccine, allaying fear shouldn’t on the benefit side of the ledger. Greater investigation does have other benefits but I think that the costs of delay exceed the benefits at this time.

The FDA is very unlikely to find reasons not to approve a vaccine later in December. But if that is the case, they should approve now. Note that in August, before the efficacy results were in, I ran the numbers and I said that the case for early vaccination wasn’t strong for most people. Now that we have the efficacy results and months of safety data and a higher death rate, I think quick approval is obviously justified.

How badly has the FDA been lagging?

As a Johns Hopkins scientist who has conducted more than 100 clinical studies and reviewed thousands more from the scientific community at large, I can assure you that the agency’s review can be done within 24 to 48 hours without cutting any corners. They just need to work harder.

Contrary to popular belief, the FDA process is not hands-on—it does not interview vaccine trial patients or look under a microscope at the immune cells. It’s doing a statistical analysis and looking at data. For the vaccine trial, the data set is small and straightforward. If my research team, normally tasked with analyzing data on millions of patients, was asked to review the smaller Pfizer vaccine study of 43,000 patients, it would take about one hour.

The FDA also reviews manufacturing data from Pfizer on how they made the drug. But not only can that data be reviewed in a few hours, it should have been done months ago when it was available. While the FDA was waiting for Pfizer’s long-term vaccine results to come in, the agency should have anticipated this step and done it early.

The final step of the FDA review is to look at the outcomes of the study volunteers, including rates and severity of infection and side effects in the vaccine and placebo groups. Again, there is no plausible reason why this basic analysis cannot be done in 24 hours. The FDA and external scientists have a simple task: confirm or reject  the review already conducted by the trial’s independent data safety monitoring board before FDA submission.

That is from Marty Makary, who also details an ongoing history of FDA delays during the pandemic, starting with the very first Covid testing attempts from the University of Washington, which the FDA tried to nix, but continuing throughout.  And:

FDA insiders say the agency and its approximately 17,000 employees were dark for the four-day Thanksgiving holiday, including those working on the vaccine approval.

For those of us who lived through the 2008 financial crisis (agencies other than the Fed were not on the ball in response), or who have studied (and indeed practiced) the economics of bureaucracy for forty years, or who know the extensive literature on how the FDA operates, will not be surprised by a lack of urgency.  Or from the NYT:

Dr. Fauci said the politicization of the pandemic in his own country had led regulators to move a little more cautiously than the British, to avoid losing public support.

Sorry people, but I read that as “for political reasons we did not go more quickly.”

Here from Statnews journalists Matthew Herper and Nicholas Florko defend the FDA, going into considerable detail, do read it.  Here is one excerpt, in direct contradiction to some of the above:

The agency’s staff “were eating turkey sandwiches on Thanksgiving while reviewing documents,” Peter Marks, who heads the FDA center conducting the vaccine reviews, said on a Thursday webcast run by the Journal of the American Medical Association.

Additionally, members of an FDA advisory committee that will convene Thursday to review the data and issue its recommendations, have expressed no desire to meet sooner. STAT spoke to four members of the panel and all said the agency should not try to move any faster.

My view is this: if your agency is saying “usually we move five to ten times more slowly,” it is highly unlikely their current procedures are optimized for speed.  It is fast organizations that are good at moving fast, right Usain Bolt?

We’re now at the point where Covid-19 is the single leading cause of death in this nation.

Covid-19 as a Ramsey tax problem

So many commentators cite lives, hospitalizations, and so on, as measuring the costs of the pandemic, and I understand that those are the rules of engagement, and furthermore I know that welfare economics is not the only relevant normative approach.

Nonetheless let us try to apply welfare economics for just a moment.  In that framework what counts as a cost is deadweight loss (no sick pun intended, nor recursively).

Look at it as a public finance problem. The total deadweight loss stems from the size of the “pandemic taxes” or “risk mark-ups” being applied to various human activities, then magnified by elasticities of adjustment, and quite possibly further social externalities from the collapse of critical scale (e.g., it is not just that movie-going might be dangerous, you can no longer enjoy the movie with large crowds of people).

Many of the biggest “risk pandemic taxes” have been put on in-door socializing, many church activities, offices, elevators, live NBA games, etc.  You know the story.

If you say that people are overreacting to Covid, in essence you are admitting that those elasticities are high, and probably you think the resulting social externalities are high too.  And thus you are saying and indeed emphasizing that the costs of the pandemic are high.

There is a positive statement — “those elasticities are high!” — bundled with a normative statement — “I don’t think those elasticities should be so high!”  Being a human, your attention may be drawn to the normative statement. But what welfare economics hears is the positive statement about high elasticities and thus high deadweight loss.

Now you might believe that “talking people down out of their high elasticities” is a good strategy.  Maybe.  Still I ask you to consider whether this is generally how you approach economic problems.  How about?: “Don’t leave NYC just because the taxes are going up!  It will wreck the city.”  Would your focus be on talking people out of leaving, or rather on keeping taxes down or raising residence benefits correspondingly?

The “overreaction” advocates try to signal “the costs of Covid aren’t that high,” but translated into econspeak it is actually “the costs of Covid are really high.”

Unless they believe a great, great deal in the efficacy and corrective power of moral education. (Does Bryan?)

On top of that, keep in mind that the better informed and better educated people tend to be playing it safer, so the moral education you would have to deploy here would be very strange indeed — “don’t listen to what the other educated sources are telling you, listen to meYou are overreacting!

That is not where I wish to put my money or my time.

As a side point, note that in the 1968/1957 pandemics elasticities of adjustment were way lower, because you couldn’t switch things to Zoom, Amazon, and so on.  So those pandemics were closer to being a “lump sum tax” on human life and thus they were cheaper, and had lower deadweight loss, probably in per capita terms as well.  From the framework on welfare economics, that is.  The value of human lives was lower then too.

We all know that welfare economics is an inadequate “all things considered” moral framework.  But still it brings us insights every now and then.

Toward a short history of Operation Warp Speed

Link here, do read the whole thread.  So which of you is going to write the definitive book on this?  That is a serious question.

Why we should be optimistic about various vaccines

I’ve been a long-time reader of your blog, and I have enjoyed your analyses of how the pandemic could play out in the US.

I saw that you gave some space to Arnold Kling’s pessimistic take on the vaccines. I’m a volunteer in the J&J Phase 3 vaccine trial, and my experience of the trial design makes me more optimistic about the vaccines than even the headline numbers in the so-far announced trials would suggest. I think the trial set-ups particularly for J&J have some biases that would lead to understated effectiveness results:

First, these trials are effectively unblinded. The placebos are saline solution in J&J, AstraZeneca, Pfizer and Moderna. Per the Phase 2 results for J&J, >60% of participants had significant side effects, with flu-like symptoms the most common; I believe other vaccine trials had similarly intense side effects. When I got a shot, I was nearly bedridden for 24 hours; it felt as if I had the flu, and the effect was far more pronounced than for any other vaccine I’ve had. If I got the placebo, I need a psychotherapist. Though I plan to remain generally responsible and not take too many incremental risks, given I’m only mostly sure I got a vaccine that is still unproven, I’m sure my assumption that I’ve been vaccinated will influence my behavior, and the behavior of anyone else who has had significant side effects from their injection too.

Second, upcoming trials are likely going to suffer from a “too much COVID effect” on an absolute basis, and relative to prior trials in particular. J&J counts any infection more than 14 days after injection toward its efficacy calculation. If full immunity takes longer (and my understanding is that antibodies build after infections for 3+ weeks in many cases), then there will be people out there getting infected before the vaccine has taken full effect. That wasn’t particularly likely to happen in the summer when there were fewer cases overall. This is particularly going to affect 1-shot vaccines, as other trials have their effectiveness measured only after the second dose (but I could still imagine this dynamic having some impact, if full immunity builds gradually after the second dose).

Anyway, hope this is of some interest. I found it encouraging to conclude that study bias could understate, not overstate, the effectiveness of vaccines.

That is from my email, identity of the author is redacted.

Bryan Caplan on the cost of Covid

Here is Bryan’s post, here is one bit:

Taking quality of life into account, how many life-years has the reaction to COVID destroyed?…

Upshot: The total cost of all COVID prevention has very likely exceeded the total benefit of all COVID prevention.

I don’t agree with Bryan’s numbers, but the more important point is one of logic.  The higher the costs of reaction to Covid, the stronger the case for subsidizing vaccines, therapeutics, and other corrective measures.  Would you accept this Bryan?  You have numerous posts about risk overreaction, but not one (if I recall correctly) calling for such subsidies.  Furthermore we just did some of those subsidies, through Operation Warp Speed, and they worked and they will fix the relevant incentives and lead to a resumption of normal life.  So the “subsidies will prove counterproductive” argument doesn’t seem strong here.  The subsidies are the (much) quicker path back to what you desire.

A second question is whether moral suasion — “don’t overreact to Covid!” — is likely to prove effective.  As I’ve already linked to, risk explains mobility reductions far more than do lockdown policies.  Or consider Sweden, which had a relatively non-panicky Covid messaging, no matter what you think of their substantive policies.  Sweden didn’t do any better on the gdp front, and the country had pretty typical adverse mobility reactions.  (NB: These are the data that you don’t see the “overreaction” critics engage with — at all.  And there is more where this came from.)

How about Brazil? While they did some local lockdowns, they have a denialist president, a weak overall response, and a population used to a high degree of risk.  The country still saw a gdp plunge and lots of collateral damage.  You might ponder this graph, causality is tricky and the “at what margin” question is trickier yet, but it certainly does not support what Bryan is claiming about the relevant trade-offs.

I keep on hearing this point again and again, about overreaction.  What kinds of reaction are you expecting or viewing as feasible and attainable?  If overreacting is indeed a public bad, why think you can talk people down out of it?  How much do you think you can talk them out of it?  What if someone suggested that we try to talk people out of their irrational voting patterns, as analyzed by Bryan’s The Myth of the Rational Voter?  How sanguine would he be about that enterprise?  I believe he instead stressed changes in relative prices.

And this is the huge flaw behind so much of the discourse about the “costs of lockdowns” — they can cite the stupidity of closing the parks in March, yes, but they don’t and indeed can’t tell you how most of those costs were to be avoided, given how the public reacts to risk.

If we instead look to the relevant changes in relative prices, that means subsidies for vaccines and tests, most of all through advance market commitments, but not only.  And a full-scale commitment to implementing testing and masks and therapeutics.

The more you push home points about overreaction, the more you ought to favor these subsidies.  Libertarians out there, do you?  This chicken has come home to roost, so please fess up and give the right answer here.  Do you favor these subsidies, not just murmured into your closet at night but in plain black and white for the world to read?  Moral suasion against risk overreaction is a red herring, fine enough for cutting back on one part of the problem by maybe a few percentage points, but serving mainly to distract from the very real economic questions at hand and the need to admit that one’s libertarian ideology doesn’t fit around this problem as nicely as one might wish.

How good has media coverage of Covid-19 been?

We analyze the tone of COVID-19 related English-language news articles written since January 1, 2020. Ninety one percent of stories by U.S. major media outlets are negative in tone versus fifty four percent for non-U.S. major sources and sixty five percent for scientific journals. The negativity of the U.S. major media is notable even in areas with positive scientific developments including school re-openings and vaccine trials. Media negativity is unresponsive to changing trends in new COVID-19 cases or the political leanings of the audience. U.S. major media readers strongly prefer negative stories about COVID-19, and negative stories in general. Stories of increasing COVID-19 cases outnumber stories of decreasing cases by a factor of 5.5 even during periods when new cases are declining. Among U.S. major media outlets, stories discussing President Donald Trump and hydroxychloroquine are more numerous than all stories combined that cover companies and individual researchers working on COVID-19 vaccines.

Emphasis added by me.  That is the abstract of a new NBER working paper by Bruce Sacerdote, Ranjan Sehgal, and Molly Cook.

The case for geographically concentrated vaccine doses

Here goes:

A central yet neglected point is that vaccines should not be sent to each and every part of the U.S. Instead, it would be better to concentrate distribution in a small number of places where the vaccines can have a greater impact.

Say, for the purposes of argument, that you had 20,000 vaccine doses to distribute. There are about 20,000 cities and towns in America. Would you send one dose to each location? That might sound fair, but such a distribution would limit the overall effect. Many of those 20,000 recipients would be safer, but your plan would not meaningfully reduce community transmission in any of those places, nor would it allow any public events to restart or schools to reopen.

Alternatively, say you chose one town or well-defined area and distributed all 20,000 doses there. Not only would you protect 20,000 people with the vaccine, but the surrounding area would be much safer, too. Children could go to school, for instance, knowing that most of the other people in the building had been vaccinated. Shopping and dining would boom as well.

Here is one qualifier, but in fact it pushes one further along the road to geographic concentration:

Over time, mobility, migration and mixing would undo some of the initial benefits of the geographically concentrated dose of vaccines. That’s why the second round of vaccine distribution should go exactly to those people who are most likely to mix with the first targeted area. This plan reaps two benefits: protecting the people in the newly chosen second area, and limiting the ability of those people to disrupt the benefits already gained in the first area.

In other words, if the first doses went (to choose a random example) to Wilmington, Delaware, the next batch of doses should go to the suburbs of Wilmington. In economics language [behind this link is a highly useful Michael Kremer paper], one can say that Covid-19 infections (and protections) have externalities, and there are increasing returns to those externalities. That implies a geographically concentrated approach to vaccine distribution, whether at the federal or state level.

Here is another qualifier:

…there will be practical limits on a fully concentrated geographic distribution of vaccines. Too many vaccines sent to too few places will result in long waits and trouble with storage. Nonetheless, at the margin the U.S. should still consider a more geographically concentrated distribution than what it is likely to do.

Do you think that travel restrictions have stopped the spread of the coronavirus? (Doesn’t mean you have to favor them, all things considered.)  Probably yes.  If so, you probably ought to favor a geographically concentrated initial distribution of the vaccine as well — can you see why it is the same logic?  Just imagine it spreading out like stones on a Go board.

Of course we are not likely to do any of this.  Here is my full Bloomberg column.

The pandemic is indeed a big deal

In our estimation, and with standard preference parameters, the value of the ability to end the pandemic is worth 5-15% of total wealth. This value rises substantially when there is uncertainty about the frequency and duration of pandemics. Agents place almost as much value on the ability to resolve the uncertainty as they do on the value of the cure itself.

That is from a new NBER working paper by Viral V. Acharya, Timothy Johnson, Suresh Sundaresan, and Steven Zheng.  Their analysis also shows that preventing or limiting future pandemics may be a bigger deal yet.

Rapid Antigen Tests in Europe

Image‘If rapid antigen tests are so good how come other countries aren’t using them’? is a question I get asked a lot. In fact, India authorized these tests months ago. Slovakia tested most of their population using antigen tests. Germany is using them to protect nursing home residents. Lufthansa is trialing rapid antigen tests on special flights. Rapid antigen tests are now beginning to be available more widely in Europe. Here from a twitter thread is a picture of what they look like, it’s just a paper strip inside. You swab your nose (no need for deep cleaning), swirl the swab in a tube with some liquid and then squeeze a few drops of the liquid onto the end of the tester. Results in 15 minutes. They cost about $8 a test.

Why are these tests important? The CDC now says that asymptomatic or pre-symptomatic people account for a majority of infections. Do you get it? How many people without symptoms will get a COVID PCR test, which can be time consuming and expensive? (And how many PCR tests can we run in a timely fashion if people without symptoms get many more tests?) Not that many. But many people without symptoms would get a $8 or less, at-home, 15 minute test. And if some of those people discover that they are infectious and self-isolate for a few days we can drive infection rates down.

We should have had an Operation Warp Speed for tests. We still need funding for a mass rollout and, of course, the FDA needs to approve these tests! (Here is Michael Mina in Time fulminating at the FDA holdup.)

By the way, more than 2800 Americans have died of COVID since Pfizer requested an Emergency Use Authorization for their vaccine. The FDA meets Dec. 10.

Addendum: Here’s me explaining why Frequent, Fast, and Cheap is Better than Sensitive and the difference between infected and infectious.