Category: Medicine

Which country has had the best response to the coronavirus?

I pick the United Kingdom, even though their public health response has been generally poor.  Why? Their researchers have discovered the single-best mortality-reducing treatment, namely dexamethasone (the cheap steroid), and the Oxford vaccine is arguably the furthest along.  In a world where ideas are global public goods, research matters more than the quality of your testing regime!

And the very recent results on interferon beta — still unconfirmed I should add — come from…the UK.

At the very least, the UK is a clear first in per capita terms.  Here are the closing two paragraphs:

It is fine and even correct to lecture the British (and the Americans) for their poorly conceived messaging and public health measures. But it is interesting how few people lecture the Australians or the South Koreans for not having a better biomedical research establishment. It is yet another sign of how societies tend to undervalue innovation — which makes the U.K.’s contribution all the more important.

Critics of Brexit like to say that it will leave the U.K. as a small country of minor import. Maybe so. In the meantime, the Brits are on track to save the world.

Here is my full Bloomberg column on that topic.  And if you wish to go a wee bit Straussian on this one, isn’t it better if the poor performers on public health measures — if there are going to be some — are (sometimes) the countries with the best and most dynamic biomedical establishments?  Otherwise all the panic and resultant scurry amounts to nothing.  When Mexico has a poor public health response to Covid-19, the world doesn’t get that much back in return.  In this regard, I suspect that biomedical innovation in the United States is more sensitive to internal poor performance on Covid-19 than is the case for Oxford.

A highly speculative version of the immunological dark matter hypothesis

The COVID-19 pandemic is thought to began in Wuhan, China in December 2019. Mobility analysis identified East-Asia and Oceania countries to be highly-exposed to COVID-19 spread, consistent with the earliest spread occurring in these regions. However, here we show that while a strong positive correlation between case-numbers and exposure level could be seen early-on as expected, at later times the infection-level is found to be negatively correlated with exposure-level. Moreover, the infection level is positively correlated with the population size, which is puzzling since it has not reached the level necessary for population-size to affect infection-level through herd immunity. These issues are resolved if a low-virulence Corona-strain (LVS) began spreading earlier in China outside of Wuhan, and later globally, providing immunity from the later appearing high-virulence strain (HVS). Following its spread into Wuhan, cumulative mutations gave rise to the emergence of an HVS, known as SARS-CoV-2, starting the COVID-19 pandemic. We model the co-infection by an LVS and an HVS and show that it can explain the evolution of the COVID-19 pandemic and the non-trivial dependence on the exposure level to China and the population-size in each country. We find that the LVS began its spread a few months before the onset of the HVS and that its spread doubling-time is \sim1.59\pm0.17 times slower than the HVS. Although more slowly spreading, its earlier onset allowed the LVS to spread globally before the emergence of the HVS. In particular, in countries exposed earlier to the LVS and/or having smaller population-size, the LVS could achieve herd-immunity earlier, and quench the later-spread HVS at earlier stages. We find our two-parameter (the spread-rate and the initial onset time of the LVS) can accurately explain the current infection levels (R^2=0.74); p-value (p) of 5.2×10^-13). Furthermore, countries exposed early should have already achieved herd-immunity. We predict that in those countries cumulative infection levels could rise by no more than 2-3 times the current level through local-outbreaks, even in the absence of any containment measures. We suggest several tests and predictions to further verify the double-strain co-infection model and discuss the implications of identifying the LVS.

That is a new paper from Hagai and Ruth Perets, another link here, via Yaakov.

The Thai coronavirus paradox

Dr. Wiput Phoolcharoen, a public health expert at Chulalongkorn University in Bangkok who is researching an outbreak of the coronavirus in Pattani in southern Thailand, noted that more than 90 percent of those who tested positive there were asymptomatic, much higher than normal.

“What we are studying now is the immune system,” he said.

Dr. Wiput said Thais and other people from this part of Southeast Asia were more susceptible to certain serious cases of dengue fever, a mosquito-borne virus, than those from other continents.

“If our immune systems against dengue are so bad, why can’t our immune system against Covid be better?” he asked.

Here is more from the NYT, good to see coverage of this.  Finally we are getting somewhere.

Swedish update, and which places need to fear second waves?

Your recent question intrigued me. Do you have any new info/opinions on what’s happening in Sweden? Despite no mask wearing, continued indoor dining (at least judging from recent photos on instagram), their case AND death daily counts are plummeting (looks like an inverse exponential). This would also explain excess deaths returning to normal throughout US. Bizarrely, my cursory reading of Swedish newpapers online did not result in any recent articles discussing the dramatic decline in cases there!

One theory circulating is they achieved herd immunity on the math: 10x true seroprevalence (from CDC tests in US) * 2x true immunity (from Tcell things not measured by antibody tests that I don’t fully understand) * 0.75% reported case penetration * 2x for relatively low tests per capita rate = 30% true immunity (likely much higher in densest areas where spread would be much faster resulting in maybe >70% immunity in Stockholm). This puts them r0 < 1.

The nice thing about this hypothesis is that it’s easily falsifiable. If true immunity rates are 20x reported case load (dropping last 2x factor since test rate higher in US), then Florida should have just gotten to the 1.4% necessary to trigger similar immunity in dense cities and from now on, cases per day should follow an inverse exponential.

This would also explain why NYC has not seen a resurgence despite very similar reopening as SF and LA – they achieved dense herd immunity in May and thus the subsequent decline in reported cases was driven by herd immunity rather than more strict closures or mask compliance, reversing either of those factors now doesn’t reverse immunity. To be clear, I’m not disputing that distancing or mask wearing works – they do. But so does infecting everyone quickly. No value judgements on what’s the better policy decision here, just trying to make a predictive statement.

At least, one can hope!

That is my email from Mayank Gupta.  In my view, some version of this view is looking more true with each passing day.  We also are not seeing second waves in hard-hit northern Italy.  Still, many surprises remain and we should not leap to premature conclusions.

To be clear, I was and still am pro-lockdown (without regrets), pro-mask, pro-testing, and I believe Denmark followed a better path than did Sweden.  Long-term damage (rather than death) still may be a significant risk, and furthermore many parts of the world may be far more vulnerable than the United States.  Still, you need to put all of the moralizing and partisanship aside and ask what we are learning from the new data, and I think Mayank Gupta has put it (probabilistically) very well.  And see this related Atlantic piece, though I would have some quibbles with it.  And here is a bit more commentary on the new T-cell results.

In any case, always be prepared to revise!  I believe that within a month we will have a much better sense of these questions.

Addendum: You will note these hypotheses also significantly raise the probability of much earlier animal-to-human transmission, especially in Southeast Asia.  A very good baseline principle for reasoning is simply “Origins usually go back longer and earlier than what you first might think!”

Second addendum: If you go back to March, leading epidemiologist Michael Osterhalm argued: “We conservatively estimate that this could require 48 million hospitalizations, 96 million cases actually occurring, over 480,000 deaths that can occur over the next four to seven months with this situation.”  Covid-19 has been terrible, and the performance of the executive branch (and many governors) absymal, but do those look like good predictions right now?  (Hospitalizations for instance have yet to hit 250k.)  If not, why not?  How hard have you thought about this question?  (Added note: one correspondent suggests that Osterhalm misspoke and in fact meant 4.8 million hospitalizations — note that still would be off by quite a large margin, almost a factor of twenty.)

Our regulatory state is failing us, antibodies edition

It might be the next best thing to a coronavirus vaccine.

Scientists have devised a way to use the antibody-rich blood plasma of COVID-19 survivors for an upper-arm injection that they say could inoculate people against the virus for months.

Using technology that’s been proven effective in preventing other diseases such as hepatitis A, the injections would be administered to high-risk healthcare workers, nursing home patients, or even at public drive-through sites — potentially protecting millions of lives, the doctors and other experts say.

The two scientists who spearheaded the proposal — an 83-year-old shingles researcher and his counterpart, an HIV gene therapy expert — have garnered widespread support from leading blood and immunology specialists, including those at the center of the nation’s COVID-19 plasma research.

But the idea exists only on paper. Federal officials have twice rejected requests to discuss the proposal, and pharmaceutical companies — even acknowledging the likely efficacy of the plan — have declined to design or manufacture the shots, according to a Times investigation. The lack of interest in launching development of immunity shots comes amid heightened scrutiny of the federal government’s sluggish pandemic response.

Here is more from the LA Times, substantive throughout, via Anecdotal.

Too many autistic adults are denied basic rights

That is the topic of my latest Bloomberg column, here is one excerpt:

Some of the very worst treatment of the vulnerable is hardly being discussed. There is an entire category of American adults being denied almost all of their basic legal rights: to hold a job, choose a residence, determine their health care, enter into contracts and even decide what to do with their own body. These are adults under legal guardianship — a court-imposed process, in Ohio as elsewhere, “by which a person is relieved of the right to make personal life decisions and another is appointed to make those decisions on that person’s behalf.”

Among the adults who have lost such rights, or live under the fear that they will, are those with autism. It is entirely possible that they will end up in guarded and segregated communities, often against their will.

Perhaps you think many of these individuals are unable to care for themselves and therefore their full rights cannot be respected. To whatever extent that may be true, it is not a reason for trampling on human rights. And even if you believe it is, you must concede that the legal system is prone to horrible misjudgments and mistakes.

After recent revelations about institutional racism, it is hard to believe that prejudices do not affect decisions about guardianship. The justice system is already heavily biased in favor of plea bargains, in effect favoring efficiency over constitutional rights. And even when there is no bias, there is the reality of simple error — which are common enough in hospitals, where the stakes are much higher.

Definitely recommended, do read the whole thing.  And don’t forget this:

When it comes to guardianship, is there any reason to be so sure that liberty-protecting institutions are in place? Especially since basic information is so hard to come by? As both a people and a polity, Americans do not always behave best “when no one is watching.”

Overall it is remarkable to me how little good information, or for that matter argumentation, is available on this topic.

A highly qualified reader emails me on heterogeneity

I won’t indent further, all the rest is from the reader:

“Some thoughts on your heterogeneity post. I agree this is still bafflingly under-discussed in “the discourse” & people are grasping onto policy arguments but ignoring the medical/bio aspects since ignorance of those is higher.

Nobody knows the answer right now, obviously, but I did want to call out two hypotheses that remain underrated:

1) Genetic variation

This means variation in the genetics of people (not the virus). We already know that (a) mutation in single genes can lead to extreme susceptibility to other infections, e.g Epstein–Barr (usually harmless but sometimes severe), tuberculosis; (b) mutation in many genes can cause disease susceptibility to vary — diabetes (WHO link), heart disease are two examples, which is why when you go to the doctor you are asked if you have a family history of these.

It is unlikely that COVID was type (a), but it’s quite likely that COVID is type (b). In other words, I expect that there are a certain set of genes which (if you have the “wrong” variants) pre-dispose you to have a severe case of COVID, another set of genes which (if you have the “wrong” variants) predispose you to have a mild case, and if you’re lucky enough to have the right variants of these you are most likely going to get a mild or asymptomatic case.

There has been some good preliminary work on this which was also under-discussed:

You will note that the majority of doctors/nurses who died of COVID in the UK were South Asian. This is quite striking. — Goldacre et al’s excellent paper also found this on a broader scale ( From a probability point of view, this alone should make one suspect a genetic component.

There is plenty of other anecdotal evidence to suggest that this hypothesis is likely as well (e.g. entire families all getting severe cases of the disease suggesting a genetic component), happy to elaborate more but you get the idea.

Why don’t we know the answer yet? We unfortunately don’t have a great answer yet for lack of sufficient data, i.e. you need a dataset that has patient clinical outcomes + sequenced genomes, for a significant number of patients; with this dataset, you could then correlate the presences of genes {a,b,c} with severe disease outcomes and draw some tentative conclusions. These are known as GWAS studies (genome wide association study) as you probably know.

The dataset needs to be global in order to be representative. No such dataset exists, because of the healthcare data-sharing problem.

2) Strain

It’s now mostly accepted that there are two “strains” of COVID, that the second arose in late January and contains a spike protein variant that wasn’t present in the original ancestral strain, and that this new strain (“D614G”) now represents ~97% of new isolates. The Sabeti lab (Harvard) paper from a couple of days ago is a good summary of the evidence. — note that in cell cultures it is 3-9x more infective than the ancestral strain. Unlikely to be that big of a difference in humans for various reasons, but still striking/interesting.

Almost nobody was talking about this for months, and only recently was there any mainstream coverage of this. You’ve already covered it, so I won’t belabor the point.

So could this explain Asia/hetereogeneities? We don’t know the answer, and indeed it is extremely hard to figure out the answer (because as you note each country had different policies, chance plays a role, there are simply too many factors overall).

I will, however, note that this the distribution of each strain by geography is very easy to look up, and the results are at least suggestive:

  • Visit Nextstrain (Trevor Bedford’s project)
  • Select the most significant variant locus on the spike protein (614)
  • This gives you a global map of the balance between the more infective variant (G) and the less infective one (D)
  • The “G” strain has grown and dominated global cases everywhere, suggesting that it really is more infective
  • A cursory look here suggests that East Asia mostly has the less infective strain (in blue) whereas rest of the world is dominated by the more infective strain:
  • image.png

– Compare Western Europe, dominated by the “yellow” (more infective) strain:


You can do a similar analysis of West Coast/East Coast in February/March on Nextstrain and you will find a similar scenario there (NYC had the G variant, Seattle/SF had the D).

Again, the point of this email is not that I (or anyone!) knows the answers at this point, but I do think the above two hypotheses are not being discussed enough, largely because nobody feels qualified to reason about them. So everyone talks about mask-wearing or lockdowns instead. The parable of the streetlight effect comes to mind.”

Sweden fact of the day

Cases in the Nordic country have declined sharply over the past few days and on Tuesday only 283 new cases were recorded.

That contrasts with a torrid month of June when daily numbers ran as high as 1,800, eclipsing rates across much of Europe, even as deaths and hospitalisations continued to decline from peaks in April.

At the same time:

…weekly numbers for tests have more than doubled since late May, putting the country in the same bracket as extensively testing nations such as Germany.

Here is the full article.  Who again has the best model of this?  Anyone?  How about no one?  Here is a NYT piece on Sweden, dated July 7, it doesn’t even mention any of this.

Here is the steadily declining Swedish death rate.  No need to point out that Denmark and Norway, with their early and swift responses, did much better yet.  I am interested in what is the best way to model why Sweden is not doing much worse.

Southeast Asia coronavirus update

Health officials praise Laos after coronavirus-free declaration (some new concerns here, so far nothing major)

Cambodia has zero reported deaths, broadly consistent with anecdotal evidence too.

Vietnam reports 14 new cases, all imported.  Broader record of zero deaths.

No new Covid cases in Thailand Tuesday.

Have you noticed that those four countries are right next to each other?  (Within southeast Asia, most cases are in the relatively distant Indonesia and Philippines.)

I genuinely do not understand why this heterogeneity is not discussed much, much more.

Those countries also have very different institutions and systems of government and state capacity.  Do you really think this is all because they are such policy geniuses?

Those countries have instituted some good policies, to be sure.  But so has Australia, where there is a major coronavirus resurgence.

Inquiring minds wish to know.  One hypothesis is that they have a less contagious strain, another is that they have accumulated T-cell immunities from previous coronaviruses.  Or perhaps both?  Or perhaps other factors are playing a role?

I do not understand why the world is not obsessed with this question.  And should you be happy if you have, in the past, traveled to these countries as a tourist?

Alcohol is again the culprit

It is “crystal clear” drunk people can’t – or won’t – socially distance, a police chief has warned after scenes showed huge crowds packed into Soho in central London.

John Apter, chair of the Police Federation, said he witnessed “naked men, happy drunks, angry drunks, fights and more angry drunks” while on shift in Southampton – and there were similar scenes across the rest of England.

Chris Whitty, England’s chief medical officer, had warned reopening pubs was a “high risk” for spreading coronavirus ahead of the easing of lockdown restrictions which also saw restaurants, cinemas, hairdressers and museums open their doors on what was dubbed “Super Saturday”.

Here is the article (no further reason to click), via Matt Yglesias.

Combining life insurance and health insurance

Why not internalize the relevant externalities by bringing the two together?:

We estimate the benefit of life-extending medical treatments to life insurance companies. Our main insight is that life insurance companies have a direct benefit from such treatments because they lower the insurer’s liabilities by pushing the death benefit further into the future and raising future premium income. We apply this insight to immunotherapy, treatments associated with durable gains in survival rates for a growing number of cancer patients. We estimate that the life insurance sector’s aggregate benefit from FDA-approved immunotherapies is $9.8 billion a year. Such life-extending treatments are often prohibitively expensive for patients and governments alike. Exploiting this value creation, we explore various ways life insurers could improve stress-free access to treatment. We discuss potential barriers to integration and the long-run implications for the industrial organization of life and health insurance markets, as well as the broader implications for medical innovation and long-term care insurance markets.

That is from a recent article by Ralph S J Koijen and Stijn Van Nieuwerburgh in the May 2020 QJE.  Here are ungated versions of the same paper.  And here is Robin’s related idea from 1994.

New evidence that amino acid mutations matter for contagiousness

It seems the virus mutated in Europe and became significantly more contagious (though not more dangerous per unit dose):

The Spike D614G amino acid change is caused by an A-to-G nucleotide mutation at position 23,403 in the Wuhan reference strain; it was the only site identified in our first Spike variation analysis in early March that met our threshold criterion. At that time, the G614 form was rare globally, but gaining prominence in Europe, and GISAID was also tracking the clade carrying the D614G substitution, designating it the “G clade”. The D614G change is almost always accompanied by three other mutations: a C-to-T mutation in the 5’ UTR (position 241 relative to the Wuhan reference sequence), a silent C-to-T mutation at position 3,037; and a C-to-T mutation at position 14,408 that results in an amino acid change in RNA-dependent RNA polymerase (RdRp P323L). The haplotype comprising these 4 genetically linked mutations is now the globally dominant form. Prior to March 1, it was found in 10% of 997 global sequences; between March 1- March 31, it represented 67% of 14,951 sequences; and between April 1- May 18 (the last data point available in our May 29th sample) it represented 78% of 12,194 sequences. The transition from D614 to G614 was occurred asynchronously in different regions throughout the world, beginning in Europe, followed by North America and Oceania, then Asia (Figs. 1-3, S2-S3).

That is from a new paper in Cell by B. Korber, via Eric Topol.  You will note there is another recent paper suggesting the east and west coasts of the United States have faced different mutations and thus different levels of contagiousness, but that seems less well established.

The authors do not mention Taiwan, but if I understand their chronology correctly, it would seem that Taiwan has not significant been hit by the most contagious version of the virus.

In any case, I will repeat my general point: moralizing about the virus is premature.  And of course the main result presented in this new paper is subject to revision, further scrutiny, and possible reversal.

Addendum: Here is NYT coverage.

Why American lockdown exceptionalism?

That is the topic of my latest Bloomberg column, and here is part of the explanation:

The danger lies in the potential for ratchet effects. If hardly anyone is eating out or going to bars, you might be able to endure the deprivation. But once others have started doing something, you will probably feel compelled to join them, even at greater risk to your life.

Consider that in the 1920s, the chance of catching a disease or infection from dining out was pretty high, but people still went out. Accepting that level of risk was simply considered to be part of life, because everyone saw that everyone else was doing it. In similar fashion, members of an infantry brigade are usually willing to charge an enemy position so long as they can be assured that all their comrades are, too.

So if you are wondering why the U.S. has become so tolerant of Covid-19 risk, one reason is simply that it has the most pro-consumption norms of any major Western nation. The pursuit of socially influenced high consumption levels is far more common in America than in, say, Kosovo, a country with a relatively good anti-Covid safety record.

And one implication is this:

So telling Americans that they are stupid and excessively sociable is likely only to make the problem worse.

Better in fact is everyone thinks no one else is going out very much.

SARS-CoV-2 T-cell epitopes define heterologous and COVID-19-induced T-cell recognition

The SARS-CoV-2 pandemic calls for the rapid development of diagnostic, preventive, and therapeutic approaches. CD4+ and CD8+ T cell-mediated immunity is central for control of and protection from viral infections[1-3]. A prerequisite to characterize T-cell immunity, but also for the development of vaccines and immunotherapies, is the identification of the exact viral T-cell epitopes presented on human leukocyte antigens (HLA)[2-8]. This is the first work identifying and characterizing SARS-CoV-2-specific and cross-reactive HLA class I and HLA-DR T-cell epitopes in SARS-CoV-2 convalescents (n = 180) as well as unexposed individuals (n = 185) and confirming their relevance for immunity and COVID-19 disease course. SARS-CoV-2-specific T-cell epitopes enabled detection of post-infectious T-cell immunity, even in seronegative convalescents. Cross-reactive SARS-CoV-2 T-cell epitopes revealed preexisting T-cell responses in 81% of unexposed individuals, and validation of similarity to common cold human coronaviruses provided a functional basis for postulated heterologous immunity[9] in SARS-CoV-2 infection[10,11]. Intensity of T-cell responses and recognition rate of T-cell epitopes was significantly higher in the convalescent donors compared to unexposed individuals, suggesting that not only expansion, but also diversity spread of SARS-CoV-2 T-cell responses occur upon active infection. Whereas anti-SARS-CoV-2 antibody levels were associated with severity of symptoms in our SARS-CoV-2 donors, intensity of T-cell responses did not negatively affect COVID-19 severity. Rather, diversity of SARS-CoV-2 T-cell responses was increased in case of mild symptoms of COVID-19, providing evidence that development of immunity requires recognition of multiple SARS-CoV-2 epitopes. Together, the specific and cross-reactive SARS-CoV-2 T-cell epitopes identified in this work enable the identification of heterologous and post-infectious T-cell immunity and facilitate the development of diagnostic, preventive, and therapeutic measures for COVID-19.

Here is the full piece, by Annika Nelde,, via Jackson Stone.  Or from the paper, here is a simpler bit:

At present, determination of immunity to SARS-CoV-2 relies on the detection of SARS-CoV-2 antibody responses. However, despite the high sensitivity reported for several assays there  is still a substantial percentage of patients with negative or borderline antibody responses and thus unclear immunity status after SARS-CoV-2 infection34. Our SARS-CoV-2-specific T- cell epitopes, which are not recognized by T cells of unexposed donors, allowed for detection of specific T-cell responses even in donors without antibody responses, thereby providing evidence for T-cell immunity upon infection.

Big (and good news) if true.

UK fact of the day

#COVID19 mortality in UK hospital patients has been falling steadily from >6% in March to ~1% now, with similar trends elsewhere. The reasons behind this pattern remain unclear, but #COVID19 Infection Fatality Rates will likely have to be revised downward.

That is from Francis Balloux.  And again here is the source link.  And please do not conclude the virus is becoming less dangerous, that is not a necessary implication of the above!  Alternative explanations are given at the latter link.  Most broadly, I will say it again: if your model does not have long-run elasticities as much greater than short-run elasticities, it is likely to be off in some significant ways.