Results for “first doses” 105 found
No Learning Without Risk
Here’s something from a paper that I am working on. The context is why first doses first makes more sense the greater the uncertainty but the point made is larger. No indent.
An important feature of First Doses First (FDF) and other policies such as fractional dosing is that they are reversible. In other words, FDF contains an option to switch back to Second Doses First (SDF). Options increase in value with uncertainty (Dixit and Pindyck 1994). Thus, contrary to many people’s intuitions, the greater the uncertainty the greater the value of moving to First Doses First. Indeed, the value of the option can be so high that one might want to move to First Doses First even if it were worse in expectation. For example, if the expected efficacy of the first dose were just 45% then in expectation it would be worse than Second Doses First (95% efficacy) but if there were lots uncertainty around the 45% expected efficacy it might still be better to switch to First Doses First. If there was a 75% chance that the efficacy of the first dose was 30%, for example, and a 25% chance that it was 90% (.75*.3+.25*.90=45%) then under reversibility one would still want to switch to First Doses First to learn whether the true efficacy was 30% or 90%.*
Put differently shifting away from the default strategy to an alternative such as FDF or fractional dosing might be considered to be “risky”. But in this context, learning requires risk. When learning is desirable, it is also desirable to take on risk. Risk aversion can prevent learning and thus can be dangerous.
If FDF is worse in expectation than SDF then it would be optimal to switch to the most minimal form of FDF necessary to learn about the true efficacy rate. In other words, to run an experiment. If FDF is superior in expectation to SDF then it might also be better to run an experiment before switching but not necessarily. If FDF is superior in expectation to SDF then the cost of running the experiment is keeping the policy with lower expected value while the experiment is running. If these costs are high then switching immediately is better.
It would take at least 16 weeks, for example, to run an experiment on extending dosing from 3 weeks to 12 weeks (including, optimistically, just 1 week to setup the experiment). As of early January 2021, confirmed cases in the United States are increasing at the rate of 200,000 per day or 1,400,000 per week. Thus there could be 22,400,000 new confirmed cases in the time it takes to run the experiment. At a case fatality rate of 1.7% that means 380,800 new deaths. If First Doses First reduces the infection rate in expectation by 10% that would imply that running the experiment has an expected cost of 38,080 lives.
At these rates, more lives could be saved in expectation by switching to the policy with higher expected value and simultaneously running experiments. Randomized trials that explicitly test the impact of dosing timing, fractional dosing and different timings of additional doses on severe, symptomatic and asymptomatic infections, and also on transmission should be incorporated as part of roll-out plans (Kominers and Tabarrok 2020, Bach 2021). However, roll-out of modified plans should not wait until these trial results are known; instead, plans should be adjusted as new information emerges. Most notably the British moved to First Doses First and they approved the AstaZeneca vaccine on December 30, 2020 and the consequences of both of these decisions should be monitored very closely to help improve decisions in other countries.
*This assumes that one could learn the true efficacy rate quickly enough relative to the ongoing pandemic to benefit from the new information. One might respond that in principle SDF also contains an option to switch to FDF but this option is valueless since Second Doses First provides no opportunity to learn. Only under First Doses First do we learn valuable new information.
Be Prepared! Sars-COV-3
The federal government was unprepared for the pandemic, despite multiple, loud and clear warnings. State and local governments were unprepared for vaccines, despite multiple, loud and clear warnings. The Capitol Police were unprepared for rioters, despite multiple, loud and clear warnings.
The record isn’t good but as a Queen’s Scout I persist. We now have multiple, loud and clear warnings that new variants of the SARS-COV II virus are more transmissible and thus much more dangerous. But we can do something. As wrote in The New Strain and the Need for Speed
One of the big virtues of mRNA vaccines is that much like switching a bottling plant from Sprite to 7-Up we could tweak the formula and produce a new vaccine using exactly the same manufacturing plants. Moreover, Marks and Hahn at the FDA have said that the FDA would not require new clinical trials for safety and efficacy just smaller, shorter trials for immune response (similarly we don’t do new large-scale clinical trials for every iteration of the flu vaccine.) Thus, if we needed it, we could modify mRNA vaccines (not other types) for a new variant in say 8-12 weeks.
Thus, let’s start doing much more sequencing to discover new strains–and also think about potential new strains–and start phase I and phase II trials of new vaccines. Florian Krammer suggested an even more ambitious plan to do the same thing for all potential pandemic viruses:
From each of the identified virus families, which should certainly include the Paramyxoviridae, Orthomyxoviridae, and Coronaviridae families, a handful of representative strains with the highest pandemic potential should be selected for vaccine production. Up to 50–100 different viruses could be selected and this would broadly cover all phylogenies that may give rise to pandemic strains….It should be possible to choose candidates that are close to viruses that might emerge in the human population. The idea is that once viruses are selected, vaccines can be produced in different platforms and tested in phase 1 and phase 2 trials with some of the produced vaccine being stockpiled. This would likely cost 20–30 million US dollars per vaccine candidate resulting in a cost of 1–3 billion US dollars.
What I am suggesting is less ambitious–just do this for Sars-COV-3, 4, 5 and 6. But do it now!
Hat tip: Daniel Bier.
Broken Record Addendum: We should make better use of our limited vaccine supply by moving to First Doses First and/or fractional dosing and approve the AstraZeneca vaccine immediately and spend billions to increase the rate of vaccinations and to speed new vaccines (such as those from J&J and Novavax) to market.
Wednesday assorted links
1. How to run a simple and fairly quick clinical trial on First Doses First. It is funny how you do not hear the critics suggest the merits of further investigation.
2. “American Chess Magazine Releases Their List of the Top 1 Shows of 2020.” You should not need to click on the link.
3. The redone Joshua Gans calculations (great praise to him for trying to put numbers on everything) now favor a policy of First Doses First. And another useful model supporting First Doses First. The silence on the other side of the debate is deafening.
4. Is peer-reviewed work increasingly boring?
5. Making policy for a low-trust world (so far the year’s best short essay).
6. Hail Palau, it might soon have all its people vaccinated.
The AstraZeneca Factory in Baltimore
Emergent BioSolutions has a factory in Baltimore that operates under an innovative long-term private-partnership agreement with BARDA. Essentially BARDA subsidized the factory in return for an option to use it in an emergency–Operation Warp Speed exercised that option and in June-July AstraZeneca signed a licensing agreement with Emergent for large-scale manufacturing of its vaccine.
According to the Baltimore Sun the AZ vaccine is already being made at the facility. I hope they are making millions of doses. I want the AZ vaccine approved in the United States immediately but if we won’t take it (yet) they can still export it to Britain and the many other countries which will approve the vaccine.
More generally, there are three vaccines in the near term pipeline. AstraZeneca, Johnson and Johnson and Novavax. If there is anything that we can do to speed these vaccines to people it would be worth billions. All of these vaccine manufacturers should be making and storing millions of doses now.
It’s important to understand that a policy like First Doses First works best when capacity is increasing rapidly so approving these additional vaccines is part of an integrated plan.
Here’s the factory in Baltimore. It’s capable of producing tens to hundreds of millions of vaccine doses a year. Isn’t it beautiful?
Addendum: One more thing. Stop telling me that the problem is vaccine distribution not supply. Guess what? I am thinking ahead.
Hail Britannia!
The British approved the Pfizer vaccine, they approved the AstraZeneca vaccine, they moved to first doses first and now they are allowing (not yet encouraging they are running a trial) mix and match. Under the present circumstances, the British focus on doing what it takes to save lives is smart, admirable, and impressive.
As I wrote on Dec. 10, in Herd Immunity is Herd Immunity:
Mix and matching has two potentially good properties. First, mix and matching could make the immune system response stronger than either vaccine alone because different vaccines stimulate the immune system in different ways. Second, it could help with distribution. It’s going to be easier to scale up the AZ vaccine than the mRNA vaccines, so if we can use both widely we can get more bang for our shot.
Addendum: The CDC is projecting 80,000 COVID deaths in the United States over the next three weeks.
The New Strain and the Need for Speed
I was going to write a long blog post on the new strain but Zeynep Tufekci has written an excellent piece for The Atlantic. I will quote from it and add a few points.
One of the big virtues of mRNA vaccines is that much like switching a bottling plant from Sprite to 7-Up we could tweak the formula and produce a new vaccine using exactly the same manufacturing plants. Moreover, Marks and Hahn at the FDA have said that the FDA would not require new clinical trials for safety and efficacy just smaller, shorter trials for immune response (similarly we don’t do new large-scale clinical trials for every iteration of the flu vaccine.) Thus, if we needed it, we could modify mRNA vaccines (not other types) for a new variant in say 8-12 weeks. As Zeynep notes, however, the vaccines are very likely to work well for the new variant. It’s nice to know, however, that we do have some flexibility.
The real worry is not that the vaccines won’t work but that we won’t get them into arms fast enough. We were already going too slow but in a race against the new more transmissible variant we are looking like tortoises.
A more transmissible variant of COVID-19 is a potential catastrophe in and of itself. If anything, given the stage in the pandemic we are at, a more transmissible variant is in some ways much more dangerous than a more severe variant. That’s because higher transmissibility subjects us to a more contagious virus spreading with exponential growth, whereas the risk from increased severity would have increased in a linear manner, affecting only those infected.
Here’s a key example from epidemiologist Adam Kucharski:
As an example, suppose current R=1.1, infection fatality risk is 0.8%, generation time is 6 days, and 10k people infected (plausible for many European cities recently). So we’d expect 10000 x 1.1^5 x 0.8% = 129 eventual new fatalities after a month of spread. What happens if fatality risk increases by 50%? By above, we’d expect 10000 x 1.1^5 x (0.8% x 1.5) = 193 new fatalities.
Now suppose transmissibility increases by 50%. By above, we’d expect 10000 x (1.1 x 1.5)^5 x 0.8% = 978 eventual new fatalities after a month of spread.
…the key message: an increase in something that grows exponentially (i.e. transmission) can have far more effect than the same proportional increase in something that just scales an outcome (i.e. severity).
I argued that the FDA should have approved the Pfizer vaccine, on a revocable basis, as soon as the data on the safety and efficacy of its vaccine were made available around Nov. 20. But the FDA scheduled it’s meeting of experts for weeks later and didn’t approve until Dec. 11, even as thousands of people were dying daily. We could have been weeks ahead of where we are today. Now the epidemiologists are telling us that weeks are critical. As Zeynep notes holding back second doses looks like a clear mistake and the balance of the evidence also suggests we should move to first doses first:
All this means that the speed of the vaccine rollout is of enormous importance.
…Meanwhile, the United States was reportedly planning to hold back half the vaccine it has in freezers as a hedge against supply-chain issues, and some states may be slowed down by murky prioritization plans. Scott Gottlieb—the former FDA chief and a current board member of Pfizer—has argued that the U.S. should also go ahead with vaccinating as many people as possible right now and trust that the supply chain will be there for the booster. Researchers in Canada—where some provinces decided to vaccinate now as much as possible without holding half in reserve, and will administer the booster with future supplies—estimate that this type of front-loading can help “avert between 34 and 42 per cent more symptomatic coronavirus infections, compared with a strategy of keeping half the shipments in reserve.” (Note that this strategy, which is different from the one the United Kingdom just announced it will adopt in prioritizing the first dose, does not even necessarily involve explicitly changing booster timing protocols in order to maximize vaccination now; it just means not waiting to get shots into arms when the vaccines are currently available.) These were already important conversations to have, but given the threat posed by this new variant, they are even more urgent.
Perhaps most critically, the FDA should approve the AstraZeneca vaccine if not as part of Operation Warp Speed then on a right to try basis. We need every weapon in the arsenal. How many times must we learn not to play with exponential matches?
Addendum: See also this excellent Miles Kimball post, How Perfectionism Has Made the Pandemic Worse.
Wise Canadians
On December 12 I wrote:
We should vaccinate 6 million people with first dose NOW. It is deadly cautious to hold second dose in *reserve*. Supply chain will be ok and the exact timing of the second dose is not magical and likely not critical.
Modelling by a group at the University of Toronto confirmed.
Ashleigh Tuite, an epidemiologist at U of T’s Dalla Lana School of Public Health….said she and her colleagues projected that frontloading vaccine doses would avert between 34 and 42 per cent more symptomatic coronavirus infections, compared with a strategy of keeping half the shipments in reserve.
“It makes much more sense to just get as many people their first doses as soon as possible,” Dr. Tuite said.
…everyone should get the second dose on schedule, but if supply issues delay that injection by a week or two, it shouldn’t hamper how well the vaccines work.
According to Abigail Bimman at Global News, Ontario will now switch to getting as many first doses out as possible:
NEW: Ontario is changing its vaccine policy and no longer reserving second doses, but getting all of the initial 90k out the door- they expect to finish them in the “next several days” – Health Minister’s office tell @globalnew. Change due to confidence in supply chain.
It’s not all the way to first doses first but it’s a minimally risky, smart move. Indeed, Nova Scotia, Saskatchewan and British Columbia already have said that they won’t hold back first doses.
The United States should listen to the wise Canadians.
Double the Inoculated Population with One Dose
I’ve been arguing that we should delay the second dose (or at least not hold back first doses) in order to hit the virus hard and inoculate more people on the first dose. I wrote:
We should vaccinate 6 million people with first dose NOW. It is deadly cautious to hold second dose in *reserve*. Supply chain will be ok and the exact timing of the second dose is not magical and likely not critical. In the accidental low-dose, standard-dose regime for the AZ vaccine, people got the second dose 7 to 8 weeks after the first dose and that was the 90% efficacious regime. [A different vaccine obviously but ] Exact timing of the second-dose does not seem critical, although everyone should get a second dose.
Today epidemiologist Michael Mina and writer Zeynep Tufekci, who has been ahead of the curve on much of the discussion, make the case even more strongly in the NYTimes:
First, the science. While the vaccine trials were designed to evaluate a two-dose regimen, some immunity might be acquired before a second dose is administered. We know, for instance, that a Covid-19 infection appears to yield protection for at least six months. While infections are not vaccinations, and while we need more data on this, it’s plausible that the immunity gained from a vaccination may turn out to be even stronger than what comes from an infection. The reason we do a second — booster — vaccination is that these later doses help to solidify immune memory, in part by giving extra training to the cells that produce antibodies, a process called affinity maturation. But this process begins with the single dose, and the evidence collected between the time of the first and second doses in tens of thousands of people in the Phase 3 trials suggests that the level of affinity maturation may provide enough protection to meet the standards we have set for vaccine approval during this pandemic even without the second dose.
While we know that the single dose can protect against disease, we don’t yet know how long this immune protection will last, and at what level. However, there is no rule that says that vaccines must be boosted within weeks of each other. For measles, the booster dose is given years after the first dose. If the booster dose could be given six months or a year after the first dose, while maintaining high efficacy before the second dose, that would allow twice as many people to get vaccinated between now and later next year, accelerating herd immunity — greatly helping end the crisis phase of the pandemic in the United States.
… we should begin immediate single-dose trials, recruiting volunteers from low-risk populations who are first in line for the vaccinations. For example, among health care workers protective equipment works, rates of infection among this group have fallen sharply and severe disease is much more rare.Younger essential workers without risk factors are less likely to be severely affected if they are exposed since this disease’s impact rises steeply with age. Just as tens of thousands of people volunteered for the earlier vaccine trials, many may well volunteer to test a placebo against a second dose, allowing us to quickly ascertain questions of durability and effectiveness of the single dose.
Two additional points. First, mix and match, as I argued earlier, may be beneficial:
…we could mix and match vaccines. The UK will run a trial on this question. Mix and matching has two potentially good properties. First, mix and matching could make the immune system response stronger than either vaccine alone because different vaccines stimulate the immune system in different ways. Second, it could help with distribution. It’s going to be easier to scale up the AZ vaccine than the mRNA vaccines, so if we can use both widely we can get more bang for our shot.
Second, an economics issue. If we want Pfizer and Moderna on board we need to pay them not just to run the clinical trials but to be happy with potentially selling half as many doses. Incentives matter.
Dose Optimization Trials Enable Fractional Dosing of Scarce Drugs
During the pandemic, when vaccines doses were scarce, I argued for fractional dosing to speed vaccination and maximize social benefits. But what dose? In my latest paper, just published in PNAS, with Phillip Boonstra and Garth Strohbehn, I look at optimal trial design when you want to quickly discover a fractional dose with good properties while not endangering patients in the trial.
[D]ose fractionation, rations the amount of a divisible scarce resource that is allocated to each individual recipient [3–6]. Fractionation is a utilitarian attempt to produce “the greatest good for the greatest number” by increasing the number of recipients who can gain access to a scarce resource by reducing the amount that each person receives, acknowledging that individuals who receive lower doses may be worse off than they would be had they received the “full” dose. If, for example, an effective intervention is so scarce that the vast majority of the population lacks access, then halving the dose in order to double the number of treated individuals can be socially valuable, provided the effectiveness of the treatment falls by less than half. For variable motivations, vaccine dose fractionation has previously been explored in diverse contexts, including Yellow Fever, tuberculosis, influenza, and, most recently, monkeypox [7–12]. Modeling studies strongly suggest that vaccine dose fractionation strategies, had they been implemented, would have meaningfully reduced COVID-19 infections and deaths [13], and perhaps limited the emergence of downstream SARS-CoV-2 variants [6].
…Confident employment of fractionation requires knowledge of a drug’s dose-response relationship [6, 13], but direct observation of both that relationship and MDSE, rather than pharmacokinetic modeling, appears necessary for regulatory and public health authorities to adopt fractionation [15, 16]. Oftentimes, however, early-phase trials of a drug develop only coarse and limited dose-response information, either intentionally or unintentionally. A speed-focused approach to drug development, which is common for at least two reasons, tends to preclude dose-response studies. The first reason is a strong financial incentive to be “first to market.” The majority of marketed cancer drugs, for example, have never been subjected to randomized, dose-ranging studies [17, 18]. The absence of dose optimization may raise patients’ risk. Further, in an industry sponsored study, there is a clear incentive to test the maximum tolerated dose (MTD) in order to observe a treatment effect, if one exists. The second reason, observed during the COVID-19 pandemic, is a focus on speed for public health. Due to ethical and logistical challenges, previously developed methods to estimate dose-response and MDSE have not routinely been pursued during COVID-19 [19]. The primary motivation of COVID-19 clinical trial infrastructure has been to identify any drug with any efficacy rather than maximize the benefits that can be generated from each individual drug [3, 18, 20, 21]. Conditional upon a therapy already having demonstrated efficacy, there is limited desire on the part of firms, funders, or participants to possibly be exposed to suboptimal dosages of an efficacious drug, even if the lower dose meaningfully reduced risk or extended benefits [16]. Taken together, then, post-marketing dose optimization is a commonly encountered, high-stakes problem–the best approach for which is unknown.
…With that motivation, we present in this manuscript the development an efficient trial design and treatment arm allocation strategy that quickly de-escalates the dose of a drug that is known to be efficacious to a dose that more efficiently expands societal benefits.
The basic idea is to begin near the known efficacious dose level and then deescalate dose levels but what is the best de-escalation strategy given that we want to quickly find an optimal dosage level but also don’t want to go so low that we endanger patients? Based on Bayesian trials under a variety of plausible conditions we conclude that the best strategy is Targeted Randomization (TR). At each stage, TR identifies the dose-level most likely to be optimal but randomizes the next subject(s) to either it or one of the two dose-levels immediately below it. The probability of randomization across three dose-levels explored in TR is proportional to the posterior probability that each is optimal. This strategy balances speed of optimization while reducing danger to patients.
Read the whole thing.
What is an Emergency? The Case for Rapid Malaria Vaccination
Compare two otherwise similar towns. In Town A there have always been 1000 deaths every month from disease X. In contrast, Town B has been free of disease X for as long as anyone can remember until very recently when disease X suddenly started to kill 1000 people per month. A vaccine for disease X is developed. Which town should receive expedited vaccinations?
From a utilitarian perspective, both towns present equally compelling cases for immediate vaccination (1). Vaccination will avert 1,000 deaths per month in either location. The ethical imperative is thus to act swiftly in both instances. Lives are lives. However, given human psychology and societal norms, Town B is more likely to be perceived as facing an “emergency,” whereas Town A’s situation may be erroneously dismissed as less dire because deaths are the status quo.
A case in point. The WHO just approved a malaria vaccine for use in children, the R21/Matrix-M vaccine. Great! There are still some 247 million malaria cases globally every year causing 619,000 deaths including 476 thousand deaths of children under the age of 5. That’s not 1000 deaths a month but more than 1000 deaths of children every day. The WHO, however, is planning on rolling out the vaccine next year.
Adrian Hill, one of the key scientists behind the vaccine is dismayed by the lack of urgency:
“Why would you allow children to die instead of distributing the vaccine? There’s no sensible answer to that — of course you wouldn’t,” Hill told the Financial Times. The SII said it “already” had capacity to produce 100mn doses annually.
…“There’s plenty of vaccine, let’s get it out there this year. We’ve done our best to answer huge amounts of questions, none of which a mother with a child at risk of malaria would be interested in.”
Hill is correct: the case for urgency is strong. More than a thousand children are dying daily and the Serum Institute already has 20 million doses on ice and is capable of producing 100 million doses a year. Why not treat this as an emergency?! Implicitly, however, people think that the case for urgency in Africa is weak because “what will another few months matter?” The benefits of vaccination in Africa are treated as small because they are measured relative to the total deaths that have already occurred. In contrast, vaccination for say COVID in the developed world (Town B) ended the emergency and restored normality thus saving a large percent of the deaths that might have occurred. But the percentages are irrelevant. This is a base rate fallacy, albeit the opposite of the one usually considered. Lives are lives, irrespective of the historical context.
Hill, director of the university’s Jenner Institute, compared the timeframe with the swift rollout of the first Covid vaccines, which were distributed “within weeks” of approval.
“We’d like to see the same importance given to the malaria vaccine for children in Africa. We don’t want them sitting in a fridge in India,” he said. “We don’t think this would be fair to rural African countries if they were not provided with the same rapidity of review and supply.”
The term “emergency” inherently embodies the conundrum I highlight. Emergency is defined as an unexpected set of events or the resulting state that calls for immediate action. When formulating a response to an emergency, however, the focus should not be on whether the events were unexpected but on the resulting state. The resulting state is what is important. The resulting state is the end that legitimizes the means. The unexpected draws our attention–our emotional systems, like our visual systems, alert on change and movement–but what matters is not what draws our attention but the situational reality.
Lives are lives and we should act with all justifiable speed to save lives. The WHO should accelerate malaria vaccination for children in Africa.
(1) You might argue that in Town B the 1000 deaths are more unusual and thus more disruptive but you might also argue that Town A has undergone the deaths for so much longer that the case for speed as matter of justice is even greater. These are quibbles.
The Story of VaccinateCA
The excellent Patrick McKenzie tells the story of VaccineCA, the ragtag group of volunteers that quickly became Google’s and then the US Government’s best source on where to find vaccines during the pandemic.
Wait. The US Government was giving out the vaccines. How could they not know where the vaccines were? It’s complicated. Operation Warp Speed delivered the vaccines to the pharmacy programs and to the states but after that they dissappeared into a morass of incompatible systems.
[L]et’s oversimplify: Vials were allocated by the federal government to states, which allocated them to counties, which allocated them to healthcare providers and community groups. The allocators of vials within each supply chain had sharply limited ability to see true systemic supply levels. The recipients of the vials in many cases had limited organizational ability to communicate to potential patients that they actually had them available.
Patients then asked the federal government, states, counties, healthcare providers and community groups, ‘Do you have the vaccine?’ And in most cases the only answer available to the person who picked up the phone was ‘I don’t have it. I don’t know if we have it. Plausibly someone has it. Maybe you should call someone else.’ Technologists will see the analogy to a distributed denial of service incident, and as if the overwhelming demand was not enough of a problem, the rerouting of calls between institutions amplified the burden on the healthcare system. Vaccine seekers were routinely making dozens of calls.
This caused a standing wave of inquiries to hit all levels of US healthcare infrastructure in the early months of the vaccination effort. Very few of those inquiries went well for any party. It is widely believed, and was widely believed at the time, that this was primarily because supply was lacking, but it was often the case that supply was frequently not being used as quickly as it was produced because demand could not find it.
It turned out that the best way to get visibility into this mess was not to trace the vaccines but to call the endpoints on the phone and then create a database that people could access which is what VaccinateCA did but in addition to finding the doses they had to deal with the issue of who was allowed access.
A key consideration for us, from the first day of the effort, was recording not just which pharmacist had vials but who they thought they could provide care to. This was dependent on prevailing regulations in their state and county, interpretations of those regulations by the pharmacy chain, and (frequently!) ad hoc decision-making by individual medical providers. Individual providers routinely made decisions that the relevant policy makers did not agree comported with their understanding of the rules.
VaccinateCA saw the policy sausage made in real time in California while keeping an eye on it nationwide. It continues to give me nightmares.
California, not to mince words, prioritized the appearance of equity over saving lives, over and over and over again, as part of an explicitly documented strategy, at all levels of the government. You can read the sanitized version of the rationale, by putative medical ethics experts, in numerous official documents. The less sanitized version came out frequently in meetings.
This was the official strategy.
The unofficial strategy, the result the system actually obtained, was that early access to the vaccine was preferentially awarded based on proximity to power and to the professional-managerial class.
… The essential workers list heavily informed the vaccination prioritization schedule. Lobbyists used it as procedural leverage to prioritize their clients for vaccines. The veterinary lobby was unusually candid, in writing, about how it achieved maximum priority (1A) for veterinarians due to them being ‘healthcare workers’.
Teachers’ unions worked tirelessly and landed teachers a 1B. They were ahead of 1C, which included (among others) non-elderly people for whom preexisting severe disability meant that ‘a covid-19 infection is likely to result in severe life-threatening illness or death’. The public rationale was that teachers were at elevated risk of exposure through their occupation. Schools were, of course, mostly closed at the time, and teachers were Zooming along with the rest of the professional-managerial class, but teachers’ unions have power and so 1B it was. Young, healthy teachers quarantining at home were offered the vaccine before people who doctors thought would probably die if they caught Covid.
Now repeat this exercise up and down the social structure and economy of the United States.
…Healthcare providers were fired for administering doses that were destined to expire uselessly. The public health sector devoted substantial attention to the problem of vaccinating too many people during a pandemic. Administration of the formal spoils system became farcically complicated and frequently outcompeted administration of the vaccine as a goal.
The process of registering for the vaccine inherited the complexity of the negotiation over the prioritization, and so vulnerable people were asked to parse rules that routinely befuddled healthy professional software engineers and healthcare administrators – the state of New York subjected senior citizens to a ‘51 step online questionnaire that include[d] uploading multiple attachments’!
That isn’t hyperbole! New York meant to do that! On purpose!
Lives were sacrificed by the thousands and tens of thousands for political reasons. Many more were lost because institutions failed to execute with the competence and vigor the United States is abundantly capable of.
…The State of California instituted a policy of redlining in the provision of medical care in a pandemic to thunderous applause from its activist class and medical ethics experts….Residency restrictions were pervasively enforced at the county level and frequently finer-grained than that. A pop-up clinic, for example, might have been restricted to residents of a single zip code or small group of zip codes.
All people are equal in the eyes of the law in California, but some people are . . . let’s politely say ‘administratively disfavored’.
The theory was, and you could write down this part of it, disfavored potential patients might use social advantages like better access to information and transportation to present themselves for treatment at locations that had doses allocated for favored potential patients. This part of the theory was extremely well-founded. Many people were willing to drive the length and breadth of California for their dose and did so.
What many wanted to do, and this is the part that they couldn’t write down, is deny healthcare to disfavored patients. Since healthcare providers are public accommodations in the state of California, they are legally forbidden from discriminating on the basis of characteristics that some people wanted to discriminate on. So that was laundered through residency restrictions.
Many more items of interest. I didn’t know this incredibly fact about the Biden adminsitratins Vaccines.gov for example:
Pharmacies through the FRPP had roughly half of the doses; states and counties had roughly the other half (sometimes administered at pharmacies, because clearly this isn’t complicated enough yet). You would hope that state and county doses were findable on Vaccines.gov. It was going to be the centerpiece of the Biden administration’s effort to fix the vaccine finding problem and take credit for doing so.
…Since the optics would be terrible if America appeared to serve some states much better than others on the official website that everyone would assume must show all the doses, no state doses, not even from states that would opt in, would be shown on it, at least not at the moment of maximum publicity. Got that?
A good point about America.
We also benefited from another major strength of America: You cannot get arrested, jailed, or shot for publishing true facts, even if those facts happen to embarrass people in positions of power. Many funders wanted us to expand the model to a particular nation. In early talks with contacts there in civil society, it was explained repeatedly and at length that a local team that embarrassed the government’s vaccination rollout would be arrested and beaten by people carrying guns. This made it ethically challenging to take charitable donations and try to recruit that team.
Many more points of interest about the process of running a medical startup during a pandemic. Read the whole thing.
What Operation Warp Speed Did, Didn’t and Can’t Do
Operation Warp Speed was a tremendous success and one that I was pleased to support from the beginning. Many people, however, are concluding from the success of OWS that big Federal funding can solve many other problems at the same speed and scale and that is incorrect.
First, it’s important to understand that OWS did not create any scientific innovations or discoveries. The innovative mRNA vaccines are rightly lauded but all of the key scientific ideas behind mRNA as a delivery mechanism long predate Operation Warp Speed. The scientific advances were the result of many decades of work, some of it supported by university and government funding and also a significant fraction by large private investments in firms such as Moderna and BioNTech. It was BioNTech recall that hired Katalin Karikó (and many other mRNA researchers) when she couldn’t get university or government funding. Since OWS created no new scientific breakthroughs there isn’t much to learn from OWS about the efficacy of large scale programs for that purpose.
Second, it’s important to understand that we got lucky. OWS made smart bets and the portfolio paid off but it could have failed. Indeed, some OWS bets did fail including the Sanofi and Glaxo-Smith-Klein vaccine and the at-best modest success of Novavax. Many other vaccines which we didn’t invest in but could have invested in also failed. To be clear, my work with Kremer et al. showed that these bets and more were worth taking but one should not underestimate the probability of failure even when lots of money is spent.
So what did Operation Warp Speed do? There were four key parts to the plan 1) an advance market commitment to buy lots of doses of approved vaccines–this was important because in past pandemics vaccines had entered development and then the disease had disappeared leaving the firms holding the bag with little to show for their investment 2) the lifting of FDA regulations to allow for accelerated clinical trials, for example, phase 3 trials could start before phase 2 trials were fully complete 3) government investment in large clinical trials–clinical trials are the most expensive part of the development process and by funding the trials generously, the trials could be made large which meant that they could be quick 4) government investment in capacity, building factories not just for the vaccines but also for the needles, vials and so forth, even before any of the vaccines were approved–thus capacity was ready to go. All of these steps shaved months, even years, off the deployment timeline.
The key factor about each of these parts of the plan was that we were mostly dealing with known quantities that the government scaled. It’s known how to run clinical trials, it’s known how to produce vials and needles. The mRNA factories were more difficult but scaling problems are more easily solved with investment than are invention problems. It’s also known how to lift government regulations and speed the bureaucracy. That is, no one doubts that lifting regulations and speeding bureaucracy is within our production possibilities frontier.
It also cannot be underestimated that OWS funded people who were already extremely motivated. The Pfizer and Moderna staff put in near super-human effort–many of them felt this was the key moment of their life and they stepped up to their moment. OWS threw gasoline on fire–don’t expect the same in a more normal situation.
Another factor that people forget is that with vaccines we had a very unusual situation where the entire economy was dependent on a single sector–a macroeconomic O-ring. As a result, the social returns to producing vaccines were easily a hundred times (or more) greater than any potential vaccine profits. Thus, by accelerating vaccine production, OWS could generate tremendous returns. Most of the time, markets internalize externalities imperfectly but reasonably well which means that even if you accelerate something good the total returns aren’t so astronomical that you can’t overspend or spend poorly. Governments can spend too much as well as too little so most of the time you have to factor in the waste of overspending even when the spending is valuable–that problem didn’t really apply to OWS.
So summarizing what do we need for another OWS? 1) Known science–scaling not discovering, 2) Lifting of regulations 3) Big externalities, 4) Pre-existing motivation. Putting aside an Armageddon like scenario in which we have to stop an asteroid, one possibility is insulating the electrical grid to protect North America from a Carrington event, a geomagnetic storm caused by solar eruptions. (Here is a good Kurzgesagt video.) Does protecting the grid meet our conditions? 1) Protecting the electrical grid is a known problem whose solution does not require new science 2) protecting the grid requires lifting and harmonizing regulations as the grid is national/inter-national but the regulations are often local, 3) The social returns to power far exceed the revenues from power so there are big externalities. Indeed, companies could have protected the grid already (and have done so to some extent) but they are under-incentivized. (The grid is aging so insulating the gird could also have many side benefits.) 4) Pre-existing motivation. Not much. Can’t have everything.
I think it’s also notable that big pandemics and solar storms seem to occur about once in every one hundred years–just often enough to be dangerous and yet not so often that we are well prepared.
Thus, while I think that enthusiasm for an “OWS for X” is overblown, there are cases–protecting the grid is only one possibility–where smart investments could pay big returns but they must be chosen carefully in light of all the required conditions for success.
Who is protected against Omicron?
The vaccine made by Sinovac Biotech Ltd., one of the most widely used in the world, doesn’t provide sufficient antibodies in two doses to neutralize the omicron variant and boosters will likely be needed to improve protection, initial lab findings showed.
While the first two studies to be released on the Chinese shot and omicron diverged on how much the vaccine’s immune response is degraded, they both indicated the standard two-dose course would not be enough, raising uncertainty over a shot relied on by millions of people in China and the developing world to protect against Covid-19.
Among a group of 25 people vaccinated with two Coronavac doses, none showed sufficient antibodies in their blood serum to neutralize the omicron variant, said a statement from a team of researchers at the University of Hong Kong released late Tuesday night.
Here is more from Bloomberg.
An update on the mask debate
I am long since tired of this debate, and I see that a lot of people are not joining it in the best of faith. I can pass along a few updates, namely this study, with some critical commentary attached. And here is more on the Bangladeshi mask RCT. With more data transparency, it does not seem to be holding up very well.
That said, I am not sure that either calculation really matters. Any good assessment of mask efficacy has to be radically intertemporal in nature, and I mean for the entirety of the pandemic. “Not getting infected” now may well raise your chance of getting infected later on, and that spans for longer than any feasibly designed RCT. And have you heard about the new “Nu” variant? It may turn out not to matter, but it does remind us that the pandemic is not over yet.
As a simple first approximation, think of the real value of masks as “a) how many infections are delayed for how long, plus improvements in treatment in the meantime, plus b) how many infections are avoided altogether.” Even a well-designed RCT is going to focus on a version of b), but only for a limited period of time. The extant studies don’t at all consider “plus improvements in treatment in the meantime,” or when some of those protected by masks for say a year or two might nonetheless later catch Covid later yet. So those RCTs, no matter what their results, are grabbing only one leg of the elephant.
To make matters more complicated yet, a “very small” efficacy for masks might (yes, might) translate into a much larger final effect, due to effective R (sometimes) being greater than 1. So finding a very small effect for masks doesn’t mean masks are only slightly effective. As the pandemic is ending, you might (again might) have had one less “pandemic cycle” than if you hadn’t tried masks at all. You can think of masks as a kind of lottery ticket on “one big gain,” paying off only when the timing is such that the masks have helped you choke off another Covid wave. Again, the RCT is not capable of estimating that probability or the magnitude of its effect.
Yet another part of my mental model of masks has evolved to be the following. You have two sets of countries, countries that manage Covid well and countries that don’t, argue all you want who goes into which bin but that isn’t the point right now.
Now consider the countries that don’t manage Covid well. They might wish to stretch out their epidemics over time, so that better treatments arrive, subject to economic constraints of course. But the countries that manage Covid well probably want the poorly-managed countries to reach herd immunity sooner rather than later, if only to lower the ongoing risk of transmission from a poorly-managed country to a well-managed country. And to lower the risk of those countries birthing new variants, just as southern Africa now seems to have birthed the Nu variant.
So we have two major points of view, represented by multiple countries, one wanting quicker resolution for the poorly managed countries but the other wanting slower resolution. Does any study of masks take those variables into account? No. Nor is it easy to see how it could.
To be clear, I am not arguing masks don’t work, nor am I making any claims about how much masks may or may not protect you individually, or the people you interact with. I am claiming that at the aggregate social level we are quite far from knowing how well masks work.
I say it is third doses we should be doubling down on, not masks. To be clear, I am fine with wearing masks myself, I am used to it, and I dislike it but I don’t hate it. On this issue, I am not one of those people translating his or her own snowflake-ism into some kind of biased policy view.
But the emerging science on third doses is much stronger, and most countries have been dropping the ball on that one.
The Covid pandemic is not taking the very best of turns
This was emailed to me, but I am not doing a double indent…in any case I fear the person might be right…
“The prevailing sentiment is that the COVID pandemic is close to over. The vaccines are of course miraculous but we are not currently on a good trajectory.
- It is increasingly clear that two shots plus a booster of our current vaccines are the least one needs to have effective medium-term protection. Almost nowhere (least of all the US) is on track to reach this kind of coverage. The messaging in the US remains mistaken, where the CDC to this day recommends boosters only for those aged 50 and older. More broadly, the institutional confusion around boosters shows that the adults are not yet in charge.
- Even though Delta arose in the spring, we are still vaccinating (and boosting) people with the original Wuhan strain. This is insane, and probably meaningfully less effective, and yet nobody is up in arms about it.
- Severe outbreaks are manifestly possible even in exceptionally vaccinated populations, especially when booster uptake is low. See: Singapore, Gibraltar, Ireland. One should assume that almost every part of the US will see significant waves before COVID “ends”, whatever that turns out to mean. Note that just 60% of the US population is vaccinated today with two doses.
- There is early suggestive evidence from Israel that boosters may wane.
- Waning aside, it’s clear that breakthrough infections in boosted individuals are not uncommon. While the vast majority of those infections are not severe, this does mean that there will still be plenty of mutagenesis.
- It’s unclear that longitudinal cross-immunity is strong. Getting COVID is not enough to confer long-term protection. We probably can’t just “get this over with”, even if we are willing to tolerate a large number of one-time deaths.
- The currently-breaking news about the South African Nu strain shows that arguments about how the spike protein is running out of mutation search space are almost certainly wrong.
- While the fog of war is thick right now, the early data on Nu suggests that it may be a big deal. Even if it’s not, however, it has been obvious since we got the vaccines that vaccine escape is a concern. You can debate whether the probability of a vaccine escaping variant is 20% or 80%, but in any case we need effective contingency plans in place. If we fail to respond effectively to Nu, that will be a considerably greater institutional failure than anything that happened at the outset of the pandemic. We’ve had almost two years since the first COVID case and one year from the vaccine approvals to prepare. So I ask: what is the plan for the vaccine-escaping variant?
On current trends, it looks like we will probably need one of two things to effectively end the pandemic: (1) very effective COVID therapeutics (paxlovid, molnupiravir, and fluvoxamine all being candidates but my guess is that none is a silver bullet) or (2) pan-coronavirus vaccines (with broader protection than what is currently available).
It isn’t over yet.
P.S. Has any U.S. health body recommended the clinical use of fluvoxamine (an already-approved drug), or has the FDA given any guidance as to when it might approve paxlovid? If not, can they outline their reasoning? 1,600 Americans died of COVID on Nov 24.”