COVID, Policy: vaccine acceleration proposal, treatment accelration proposal

  • $1.3bn - $2bn for a 9% up to 40% chance to save 1.2 million US lives earlier

  • $700m, 9%+ chance save 200,000 UK lives 

  • Make a significant investment to scale up current vaccine trials

  • Chance mass vaccinations once safety data is passed

  • Chance mass antibody protections? Accelerate treatment trials.

  • Flatten the curves maths uncertain, vaccine and treatments good bets in any scenario.

  • Treatment/trial protocols should be set up now and accerelated after positive safety before full phase 3 trials

Please also see end disclaimer and draft open letter on this idea.

Is it not possible to have a vaccine into the field in 6 to 12 months, rather than 18 to 24 months?

I think it should be with some money ($1bn to $2bn), will power (some companies will have to work hard) and a change/boost from regulators (typically they’ve not allowed drugs on to the market until definitive efficacy is shown, though have in certain cases eg cancer, as they are risk averse) . I don’t even think incentives need to be changed much in this case, although a re-think here would help for the future.

My proposal:

-start mass scale up of leading vaccines now

-if safety trial is positive (April we might know but there should be some data already available)

-then proceed to vaccinate the 60m elderly in USA

If safety trial has passed this has in the range of a 20% to 40% chance of working (my estimate). Note, BIO suggests 24% success for a phase II vaccine and 16% for a phase I vaccine. 

Best case scenario: 1.2m+ lives saved

Base case scenario: no change, $1.2bn spent but manufacturing technology and other assets built 

There is no worse scenario if safety has passed except for tail events and resources used.  I guess small chance that somehow this messes up a future vaccine,, but seems unlikely.

Getting 60m vaccinations is tricky but they can also get the flu shot at the same time which should prevent flu deaths in any case. 

Details:

Moderna  has already submitted a vaccine candidate using its mRNA technology. It’s currently being tested in safety trials. There are several other vaccine candidates, (cf. Inovio, Sanofi, J&J, GSK) but the speed is too slow - and it might not need to be this slow.

There is time and money needed to scale up manufacturing in case of success.  This could be accelerated for $500m, if started now. That investment could be used to negotiate, say, a $15 price for the vaccine. CDC pays $18 for a flu vaccine. 

So ball park for US that would be a $1.4bn investment. 

While the UK has only 12m elderly, maybe it could go halves with the US.  Still the same calculation for UK is about $700m.

Note, CEPI (Coalition for Epidemic Preparedness Innovations) has suggested $2bn for for up to 3 candidates to go forward finally past phase 3 (starting with 8 or so in phase I). So, about $1bn for one drug seems doable, at speed. Now the mostly traditional system, will have a good probability of success but it will be slow. So I’m suggesting a $1bn, 6% chance bet on one or 2 candidates now, for a chance for a vaccine in 6 months - that’s 12 to 18 months before the likely CEPI process. (We also know with some recent fast success in cancers. cf. Roche, Merck PD-1s, Novartis’ Gleevec some of this is possible at speed)

I’m also suggesting we allow drugs once they pass safety (or have passed safety), to be allowed into the field (this would cover Regeneron’s possible treatment, it would cover Chloroquine, baricitnib and ruxolitinib - these have already passed safety in other indications; it would be resmedivir as well)

Source: Regeneron (Cowen Conference, March 3)

Source: Regeneron (Cowen Conference, March 3)

Also, note there might be antibody treatments - this would be Regeneron’s approach. It won’t have antibodies ready until summer, but once ready, after a short safety trial, it might be worth going to dose the elderly. So say doeses ready in August, safety trial Sep - get it ready now - and start dosing in October. This could be expensive but only in the order of $2bn to $8bn depending on price. Now, in October we won’t know efficacy, but if safety is basically clear, then again we have a 20 - 40% chance of success albeit at a higher cost (as antibodies are more expensive).

Vaccine probablity of success

Vaccines have a 6% percent of success once in pre-clinical trials (base line stat) and around 16% when in phase I.  Investors use a range of 1% to 16% chance of success typically for Phase I drugs.  Risk is often bucketed for (a) safety (b) efficacy and c) regulatory.

There are plus/minus reasons to vary the risk of a COVID vaccine.  Regulatory risk is lower than average. Reasonable people can argue for safety/efficacy risk. The mRNA technology is new, but we do have the virus genome. We know how to make flu vaccines very successfully, so it’s proabably a matter of time and investment rather than completely new invention/innovation needed.

In any event, this is a >0 success rate, and a ball park 9% is reasonable for a novel phase I vaccine.

Vaccine and treatment idea details

Manufacturing in advance.  This needs to start now as scale will be needed.

Trial for efficacy now. Ask for volunteer elderly, maybe healthcare worked and start the phase 2/3 test immediately in April/May. This is if you simply can’t push through vaccines when not yet tested.

If you scale up the money, you can run it on all 8 or so most viable vaccines, $8bn should be enough to take through an accelerated phase 2/3 + manufacturing if there is regulatory and company willing.

There are 80 or so drug treatment candidates identified by WHO. (see sources end)

We should start with drugs already approved and get them ready for trial in the field.

This would include chloroquine (already being used by China) and baricitinib (as identified by AI processes), China is running trials using ruxolitinib. These are treatments rather than preventative but still useful in curing patients and getting them out of ICU.

The practical maths of flattening the curve

The UK needs to keep ICU cases down to approx 1000 (range up to 2000).  This means peak diagnosed confirmed cases at 20,000. (Range 10K to 40k).  The measures required to do this in the UK given current doubling times are have quetionablt in feasibilty Some modelas have. UK reaching 20,000 cases between 21 to 90 days. And an ICU case may stay in ICU for 3 weeks+ depending on death or recovery.  So keeping capacity at the ICU level is going to hard. We may be able to produce cheap ventilation and free up capacity, but it might be tricky.

That’s why accelerating a vaccine and treatments are a good bet, as they might help get in before the peak or help people out of ICU.

Tough maths of elderly deaths

Let’s look at some other brutal maths. 1 year or 2 year infection rate estimates might range from 20% to 70% of the population. Swine flu had a 20% infection rate and 150K to 575K people died (CDC data). Swine flu also circulates every year now since 2009.

A 20% infection rate seems very plausible. The case fatality rate (this is for when you are assigned as a case and so doesn’t include non-symptom or mild cases that don’t get reporting) is very hard to know.

These are the brutal maths for the UK and Italy.

Italy has about 60m people and >22% are over 65 —> over 12m elderly.

If 20% are diagnosed —> 2.4m and at 4% CFR —> 96,000 deaths. It’s easy to see how this might range up to 200,000+ easily with double diagnosis/CFR.

In the UK, it’s about 18% of 67m —> this is also 12m elderly. The maths is the same, if 20% are diagnosed —> 2.4m and at 4% CFR —> 96,000 deaths.

Politics of this bet

In UK, US many conservative / Republican voters are elderly >65. There are more of these Rep voter >65 (and this reverses for under 30s).

So in particular for Trump and Johnson, this would be a political calculus to consider if they wish.

Alternatively, some have argued that losing “unproductive” >65s might make for a more productive economy with lower social cost burden. Eeek.

The Future:

Pandemics are very likely (over 90% chance) to occur (again) over the next 50 years and likely over 100 years+ time frames. This pandemic was predicted by pandemic experts.

This is because:

-humans are increasingly interconnected at speed

-the way we treat/breed animals is not changing any time soon

-wet markets and similar not likely to change soon (though I think in eg China there will be a crack down)

-current viruses/germs eg influenza, pneumonias have been around for 1000s years

-virus/germs will constantly mutate

-containment will slow, likely never stop, transmission

What to do about future pandemics

-cultural learnings eg greetings

-innovation

We can slow transmission and in small cases potentially even stop by a change in cultural norms. We know the behaviours - washing hands, hygiene, don’t shake hands, cough into elbow  - but compliance can be greatly improved. This is inexpensive. Still, it is unlikely to stop all future pandemics. It’s worth recommending more strongly. Sanitation has already given use huge gains here and can gives us further gains.

That leaves us with treating pandemics and vaccinating once pandemics start. This is a question of innovation.

Incentivising Innovation

The market arguably has inefficiencies with dealing with i) rare diseases and ii) developing world diseases and iii) diseases that have not occurred, but we can predict are likely to occur.

This is due to those markets being risky and/or commercially small and/or commercially small risk-adjusted (a market might be worth $2bn but at 1% chance of success, $20m risk-adjusted would be of small value).

Policy solutions that have (at least partially) worked have been  a) granting longer/extra intellectual protection for rare diseases and b) agreed forward purchasing contracts for developing world diseases.

(a) Has helped areas such as rare genetic diseases, and multiple sclerosis (and other classified rare diseases) in the developed world (mostly) and 

b) has helped in malaria and certain other developing world diseases (where commercial markets are smaller) - forward buying by the Gates Foundation amongst others.

Such mechanisms have mostly failed in I) developing new antibiotics against resistant strains, II) certain other developing world diseases,  III) pandemics.

One negative factor in this is state appropriation of (mostly) private innovation. Rich countries eg US have been guilty of this as much as poor countries. The US essentially disregarded protection (or threatened to break the patents) on anthrax treatments in seeking to stockpile such medications cheaply. [https://www.wsj.com/articles/SB1003966074330899280 ]

This causes a large disincentive to work on vital areas, if profit-seeking entities will lose out on their R&D development costs for such treatments.

I would propose (as others have done in various guises)

-partial speed up of regulatory response for areas of unmet medical need

-international “state capacity” in antiviral, antibiotic, mRNA, pandemic research

-forward purchase fund for pandemic vaccines and medications

Partial speed up of regulatory response for areas of unmet medical need

The gold standard in medical research are randomised controlled trials (RCTs). They are costly and slow, but typically generate the most robust results.

For low commercial value areas, RCTs (and previously trials needed before RCT) are too costly for entities to perform give the risk. 

But, mostly health regulators will need RCTs before approval of a drug to be able to know the risk/benefit of a medication vs standard of care.

This has led some thinkers (eg Peter Thiel) to argue that regulators need to change or relax standards to allow quicker and more innovation on to the market. The challenge is that this may let onto the market ineffective treatments that cost lives or damage the credibility of the system.

One compromise would be to let medications on to the market where - in a controlled fashion - when there is enough evidence of safety/efficacy but no RCT. A full approval would be contingent on  future RCTs being performed in a reasonable time frame else the drug would be with drawn from the market. The drug would also be withdrawn if the RCT fails.

If medications for areas of high unmet need - for instant pandemics or other diseases with limited treatment options - would be released this way, the net benefit would be positive.

Industry would pay for such a faster service, and this could cut drug development time in half.

International/national “state capacity”

Faster regulation alone would not help unless there were medications to test.  Given the long and uncertain cycles for viral pandemics, it’s beyond the risk tolerance for many private entities. There are further complications because mutations might mean the plan A vaccine proves to be relatively ineffective and has to be made again under plan B.

However, I believe this is an area where even libertarians or perhaps “state capacity” libertarians might concede a non-private institution or set of institutions might be useful.

Essentially, I would be arguing for a form of Health ARPA where a part of the HARPA is focused on pandemic anteviral research, and antibiotic research and possibly other areas of unmet medical need. This is a sibling idea to the NIH but more targeted at likely pandemics.

If such an organisation had capacity to response quickly to evolving pandemics, then it should be able to share royalties with any other parties needed to scale medications to commercialisation, if it needed private partners to help scale quickly.

There should be positive spillover (cf NIH) in the years when no pandemics occur.

Forward purchase fund for pandemic vaccines and medications

Now (A) We have an organisation that can respond quickly with a new medication, and (B) a regulatory process which can speed through medications for high unmet need (eg pandemic) but how will we pay and keep incentives especially if we need multi-stakeholders to develop the medication.

This is where a forward purchasing fund or contract comes  into play. This fund acts as a guarantee that a certain amount will be paid for the innovation in a swift manner. This is where CEPI already sits and comes in and the Gates Foundation (along with Mastercard and others) have made a sister CEPI for COVID specifically. I do note the US govt has approved funding quickly on COVID, but still better to have it already in place.

But, stronger and wider funding for CEPI (and I expect this will happen) would be a good development.

Conclusion

Given pandemics will re-occur, we should look to set up capacity to deal with pandemics, regulation that can be swift and responsive and a fund to guarantee a fair price for innovation and set incentives accordingly

Post Script: It turns out Bill Gates haas also written on this topic and he many similar ideas and sources (and talks more about infrastructure build) examples of certain pandemic preparation here. https://www.nejm.org/doi/full/10.1056/NEJMp2003762

Other Sources:

On some COVID maths https://www.thendobetter.com/investing/2020/3/13/covid-brutal-maths-and-counter-factuals

On political age split: https://www.people-press.org/2016/09/13/2-party-affiliation-among-voters-1992-2016/

Moderna in trials: https://investors.modernatx.com/news-releases/news-release-details/moderna-ships-mrna-vaccine-against-novel-coronavirus-mrna-1273

On the CEPI funding call https://cepi.net/news_cepi/2-billion-required-to-develop-a-vaccine-against-the-covid-19-virus-2/

On Regeneron’s approach: https://newsroom.regeneron.com/static-files/2b0c3227-defd-4b84-814a-8519c89e103f

ON WHO list of treatment candidates:

https://www.who.int/blueprint/priority-diseases/key-action/Table_of_therapeutics_Appendix_17022020.pdf?ua=1


Disclaimer and open letter:

Can you confirm the UK will be investing in COVID therapy research and will run trials this year, as according to the clinical trials database no trials are running?

Can you explain why, we should not significantly enhance UK treatment development protocols and potentially gain effective treatments or prophylactics this year, given certain biopharma companies are already testing treatments?

My thinking and letter  on this is below.

Dear Patrick Vallance + UK team,

A safe vaccine or treatment with up to 40% chance of efficacy (maybe more) could be ready within 12 months. You’ve stated a vaccine is highly unlikely this year. This might be true under a traditional timeline, but if we invested under novel protocols we might significantly beat this.

(We met when you were at GSK and I know you have detailed knowledge of the traditional pathways, but I’m asking that you think about evoking an accelerated pathway).

Moderna has a vaccine in phase I safety trials (running as of March 2020). (There are others too.)

Regeneron has an antibody based programme that will have treatment available for trials in late summer.

If these trails show safety - there could be reasonable evaluation by May for the Moderna vaccine  - then perhaps it is worth evaluating the risk of scaling up manufacturing and performing dosing in the elderly population? (Say, 20% - 40% chance of efficacy, this may be a good risk adjusted investment.) I think a £500m to £1bn investment could achieve this.

If this is not acceptable,  then at least running an accelerated phase I/II/III trial here in the UK? I feel sure you would find the necessary volunteers.

This way, we may be able to accelerate a successful vaccine by up to 12 months from historic timelines. Or the antibody treatment could be available early 2021 or in 2020 under compassionate use. Is this not worth a chance?

We have evidence that several drugs might be effective treatments:

remdesivir (trials in China)

The anti-Il-6, Tocilizumab  to treat cytokine release syndrome, a COVID-19 complication (China approved)

Chloroquine (China approved)

Baricitinib, Ruxolitinib (Rux is trialing in China already)

and many more.

Can you confirm the UK will be investing in this research and will run trials?

Now is the time to try fast and large scale innovation for a treatment and vaccine, and I feel sure that the UK could help lead the way here.

I wish you and your team every success.

Benjamin Yeoh

Notes and Sources:

Ben Yeoh is a healthcare investor with 18 years experience but is not a virologist or infectious disease expert. This is written in a personal capacity. This is an open letter to challenge traditional thinking based on biotech conversations that suggest accelerated timelines for treatments are possible. Ben believes government advisors should investigate this line of action. This is a personal view with no organisational endorsement. The view is made in good faith and should be investigated by those with expert knowledge. I suggest these ideas for public health reasons and there is no endorsement or not of any company mentioned for investment purposes.

On Moderna’s approach:

https://investors.modernatx.com/news-releases/news-release-details/moderna-ships-mrna-vaccine-against-novel-coronavirus-mrna-1273

On Regeneron’s approach: https://newsroom.regeneron.com/static-files/2b0c3227-defd-4b84-814a-8519c89e103f

See slide 22.

Identification of baricitinib (and ruxolitinib) as treatments:

https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30304-4/fulltext

WHO database of drug treatments referencing ruxolitinib already in trials:

https://www.who.int/blueprint/priority-diseases/key-action/Table_of_therapeutics_Appendix_17022020.pdf?ua=1

Details on Tocilizumab being approved in the 7th updated diagnosis and treatment plan for COVID-19 issued by China National Health Commission (NHC) on March 3, 2020 and the drug being in clinical trial.

https://www.gene.com/covid19

Speculative ways of thinking about treatment + vaccine: https://www.thendobetter.com/investing/2020/3/14/covid-policy-vaccine-acceleration-proposal

Further details:


Vaccine probability of success

Vaccines have a 6% percent of success once in pre-clinical trials (base line stat) and around 16% when in phase I.  Investors use a range of 1% to 16% chance of success typically for Phase I drugs. Risk is often bucketed for (a) safety (b) efficacy and c) regulatory.

There are plus/minus reasons to vary the risk of a COVID vaccine.  Regulatory risk is lower than average. Reasonable people can argue for safety/efficacy risk. The mRNA technology is new, but we do have the virus genome. We know how to make flu vaccines very successfully, so it’s probably a matter of time and investment rather than completely new invention/innovation needed.

In any event, this is a >0 success rate, and a ball park 9% is reasonable for a novel phase I vaccine.

Vaccine and treatment idea details

Manufacturing in advance.  This needs to start now as scale will be needed.

Trial for efficacy now. Ask for volunteer elderly, maybe healthcare worked and start the phase 2/3 test immediately in April/May. This is if you simply can’t push through vaccines when not yet tested.

If you scale up the money, you can run it on all 8 or so most viable vaccines, $8bn should be enough to take through an accelerated phase 2/3 + manufacturing if there is regulatory and company willing.

There are 80 or so drug treatment candidates identified by WHO. (see sources end)

We should start with drugs already approved and get them ready for trial in the field.

This would include chloroquine (already being used by China) and baricitinib (as identified by AI processes), China is running trials using ruxolitinib. These are treatments rather than preventative but still useful in curing patients and getting them out of ICU.

Costs

Moderna  has already submitted a vaccine candidate using its mRNA technology. It’s currently being tested in safety trials. There are several other vaccine candidates, (cf. Inovio, Sanofi, J&J, GSK) but the speed is too slow - and it might not need to be this slow.

There is time and money needed to scale up manufacturing in case of success.  This could be accelerated for $500m, if started now. That investment could be used to negotiate, say, a $15 price for the vaccine. USCDC pays $18 for a flu vaccine. 

While the UK has only 12m elderly, maybe it could go halves with the US.  Still an approx $1bn to $2bn investment per likely treatment candidate is viable and would potentially accelerate treatment into 2020.

Note, CEPI (Coalition for Epidemic Preparedness Innovations)  has suggested $2bn for for up to 3 candidates to go forward finally past phase 3 (starting with 8 or so in phase I). So, about $1bn for one drug seems doable, at speed. Now the mostly traditional system, will have a good probability of success but it will be slow. So I’m suggesting a $1bn, 6% chance bet on one or 2 candidates now, for a chance for a vaccine in 6 months - that’s 12 to 18 months before the likely CEPI process. (We also know with some recent fast success in cancers. cf. Roche, Merck PD-1s, Novartis’ Gleevec some of this is possible at speed)

I’m also suggesting we allow drugs once they pass safety (or have passed safety), to be allowed into the field (this would cover Regeneron’s possible treatment, it would cover Chloroquine, baricitnib and ruxolitinib - these have already passed safety in other indications; it would be resmedivir as well)

Also, note there might be antibody treatments - this would be Regeneron’s approach. It won’t have antibodies ready until summer, but once ready, after a short safety trial, it might be worth going to dose the elderly. So say doses ready in August, safety trial Sep - get it ready now - and start dosing in October.  This could be expensive but only in the order of $2bn to $8bn depending on price. Now, in October we won’t know efficacy, but if safety is basically clear, then again we have a 20 - 40% chance of success albeit at a higher cost (as antibodies are more expensive).

COVID, No impact seen on atmospheric CO2 in Q1 2020

  • -CO2 (and N2O?) long-term trends still rising

  • -short-term numbers lower, temporary positive health impacts

  • -why has China slowdown not improved atmospheric CO2 ?

  • Cultural change as potential a large impact driver

A few blogs and articles have noted evidence that short-term pollution levels  (as measured eg by PM2) in places like China have fallen. Some go on to argue that this may lead to health improvements.

However, this short term data is at odds with the long-term trends in the atmosphere, where there are no signs that CO2 have fallen significantly. This is CO2 from NOAA:

Source: NOAA, https://www.esrl.noaa.gov/gmd/ccgg/trends/gl_trend.html

Source: NOAA, https://www.esrl.noaa.gov/gmd/ccgg/trends/gl_trend.html

There has been essentially no impact in Q1 2020. Raw numbers in RH column here.

n2o_trend_all_gl.png

N20 and CH4 (methane) only have monthly figures so it will interesting to see if there will be an impact.

Here for N20 you can see the 20 year trend (left) . But below, you can see NASA recorded imagery of N2O over China (below).

Earth Observatory writes: “…The maps [below] show NO2 values across China from January 1-20, 2020 (before the quarantine) and February 10-25 (during the quarantine). The data were collected by the Tropospheric Monitoring Instrument (TROPOMI) on ESA’s Sentinel-5 satellite. A related sensor, the Ozone Monitoring Instrument (OMI) on NASA’s Aura satellite, has been making similar measurements.

According to NASA scientists, the reduction in NO2 pollution was first apparent near Wuhan, but eventually spread across the country.

“This is the first time I have seen such a dramatic drop-off over such a wide area for a specific event,” said Fei Liu, an air quality researcher at NASA’s Goddard Space Flight Center. Liu recalls seeing a drop in NO2 over several countries during the economic recession that began in 2008, but the decrease was gradual. Scientists also observed a significant reduction around Beijing during the 2008 Olympics, but the effect was mostly localized around that city, and pollution levels rose again once the Olympics ended. …” Link here.

Source: NASA, https://earthobservatory.nasa.gov/images/146362/airborne-nitrogen-dioxide-plummets-over-china

Source: NASA, https://earthobservatory.nasa.gov/images/146362/airborne-nitrogen-dioxide-plummets-over-china

Carbon brief wrote: “…Electricity demand and industrial output remain far below their usual levels across a range of indicators, many of which are at their lowest two-week average in several years. These include:

  • Coal consumption at power plants was down 36%

  • Operating rates for main steel products were down by more than 15%, while crude steel production was almost unchanged

  • Coal throughput at the largest coal port fell 29%

  • Coking plant utilization fell 23%

  • Satellite-based NO2 levels were 37% lower

  • Utilization of oil refining capacity was lowered by 34%

  • At their peak, flight cancellations were reducing global passenger aviation volumes by 10%, but the sector appears to be recovering, with global capacity down 5% on year in February as a whole.

All told, the measures to contain COVID have resulted in reductions of 15% to 40% in output across key industrial sectors. This is likely to have wiped out a quarter or more of the country’s CO2 emissions over the past four weeks, the period when activity would normally have resumed after the Chinese new-year holiday. Over the same period in 2019, China released around 800m tonnes of CO2 (MtCO2), meaning the virus could have cut global emissions by 200MtCO2 to date. The methodology is here: “The estimated CO2 reduction is based on fossil-fuel consumption data by sector and fuel for February 2019, and estimating year-on-year changes using sector activity indicators: daily coal consumption at power plants; coking plant; blast furnace and steel plant operating rates; and oil refinery operating rates. Residential fuel use is assumed to be unaffected. The estimate aligns with satellite-based NO2 levels, which point to the possibility of an even larger reduction.” Link here.

So, even the theoretical cut of 200MtCO2 over Q1 2020 had not been seen in the atmospheric ppm CO2 as a whole. Or it could be that the 3ppm increase seen from 1 Mar 2019 to 1 Mar 2020 is lower than might have been expected? This doesn’t seem to be the case as 3ppm is the high end of annual growth rate for the last 20 years.

I’d really like to know why? So I did some digging.

My observations would be:

The carbon cycle is complex. There are both slow and fast cycles, which interact with land and ocean sinks in a way which we understand in principle but not with exactness. So...”…Scientists can approach this problem in a number of different ways. They can use models of carbon sink behavior based on their best knowledge of the physics of ocean carbon absorption and the biosphere. They can also use records of changes in atmospheric carbon dioxide during glacial periods in the distant past to estimate the time it takes for perturbations to settle out.

carbon-sink.jpg
carbon-budget.jpg

Using a combination of various methods, researchers have estimated that about 50 percent of the net anthropogenic pulse would be absorbed in the first 50 years, and about 70 percent in the first 100 years. Absorption by sinks slows dramatically after that, with an additional 10 percent or so being removed after 300 years and the remaining 20 percent lasting tens if not hundreds of thousands of years before being removed….”

This suggests about 50% of the extra human-caused carbon dissipates after only 50 years. A 3 month pause is hardly a dent.

It also speaks to the way the “carbon balance” impacts over time. Land use + burning fossil fuels over the last 100 years has tilted the balance.

But, it’s a complex system. Image sources from YaleCimateConnections.

Turning back to the short term impacts in China.

Deaths from air pollution

We know air particles (eg measured by PM2.5) and N20 lead to poor health outcomes both in lung function —> death and via brain damage —> lower IQ.

But, a little bit like carbon in the atmosphere, some of this damage is long-term. It’s the accumulation of particulate debris in the lungs or damage via heavy metal poisoning in the brain that tips the human body over into health problems. A 3 month pause won’t significantly delay these mechanism of action on long-term health.

Now, it will delay some incidents of acute attacks eg asthma attacks, and where there is poor lung function from another cause eg emphysema, bronchitis, pneumonia.

For asthma, in the US around 3,500 people die a year even though 1 in 13 people suffer from asthma. So in China likely minimum is 4x or 14,000 asthma related deaths, or around 3,500 in Q1. True number likely to be be much higher given the health infrastructure and air quality challegens. It’s plausible that a large number of these would have been saved from the lower air pollution. In that, my calculation is in the same direction as Marshall Burke here (H/T Tyler Cowen). But, if air pollution returns - as it looks like doing - this would be a temporary effect.

There should be reductions from lower accidents as well, although there will be higher social and economic costs elsewhere.

Cultural Change as a positive

This brings me to my final two thoughts on this area and that’s cultural change and innovation investments. This could be harnessed in a very positive way. For instance, to the extent that hand washing becomes more ingrained into cultural practises and even our way of greetings may change (non-Asian at least) that should permenantly lower deaths/transmissions of infectious diseases like ‘flu.

While much of the climate challenge is systems based from land use, transport, power generation, industry, heating and the like - the power of the consumer and consumer preference has its role as well. Not only in behaviours such as walking and cycling but in more hidden areas like food waste.

Up to 35% of food is wasted in high income countries at the table and this could be changed with cultural and behaviour change. It’s notable that low income countries have much less food waste at the table (more in the supply).

China and places like Taiwan and Singapore have shown what strong state capacity can bring in critical areas. The environment and natural capital could be one place (along with innovation and health) where good state capacity (and to an extent culutural change) could have strong returns.

Innovation investments - Germany as of 13 March have announced in the order of EUR400 billion to 500 billion in funding to support businesses across the economic impact of COVID. It spent, in comparison, about $1.3bn in clean tech R and D last year. Now a 500x jump up in innovation spending is unlikely, but to the extent it might make governments re-think long-term resilience, this might be worth thinking on.


More on State Capacity here, and quality of govt over size of govt.

More on COVID thoughts, importance of bending the curve.

Here on Innovation Underspend.

COVID, brutal maths and counter-factuals

Thinking about what is said in the news, in your view is the seriousness of coronavirus generally exaggerated, generally correct, or is it generally underestimated? ( 5-9 March)

Source: Axios/Survey Money. Question wording: Thinking about what is said in the news, in your view is the seriousness of coronavirus generally exaggerated, generally correct, or is it generally underestimated?Survey dates: 3/5–3/9

Source: Axios/Survey Money. Question wording: Thinking about what is said in the news, in your view is the seriousness of coronavirus generally exaggerated, generally correct, or is it generally underestimated?

Survey dates: 3/5–3/9

I’m not an “expert” but 20 years investing in markets has taught me to be suspicious of practical behavioural insights as applied to complex systems (see Nassim Taleb for well articulated views here) and I don’t have viral pandemic modelling to hand - plus all the models have very wide uncertainty to them in the early days and are not time invariant. 

Still - here are some brutal maths, counterfactuals and ideas to consider:

-a considerable number of people currently believe COVID is no worse than flu.  About 1 in 3 people, I estimate. The survey above, taken around 5 March, suggests 44% of US think the risk is exaggerated.

If you look at UK data, 25% or 1 in 4 are doing nothing. Presumably these people think risk is low. Otherwise they would be doing something. 6 / 10 are improving hygiene, but that means 4 / 10 are not.

Source: YouGov, https://yougov.co.uk/topics/health/articles-reports/2020/03/13/most-britons-still-arent-scared-about-contacting-c

Source: YouGov, https://yougov.co.uk/topics/health/articles-reports/2020/03/13/most-britons-still-arent-scared-about-contacting-c

Trust in governments are low in Europe/US. This is true in the UK.

Source: Edelman Trust Survey (2019)

Source: Edelman Trust Survey (2019)

Items to consider about “herd immunity” and UK government advice, quarantines etc:

-We don’t know if people can acquire good immunity to COVID, we don’t have certainty about re-infection as yet (happy to be proved wrong here)

-We do know that “second waves” in pandemics can be worse than the first wave, but we don’t know about COVID

-We don’t know whether the UK public would listen to the UK government - a significant amount of people disbelieve the evidence on COVID

-We don’t how many people will catch COVID but show no symptoms

-We don’t know how long control measures would have to be in place, and whether when lifted, a second wave happens

-(At some point?) There is a trade-off being considered between economic growth (and its impact on social) and health outcomes

-We could assume that eventual infection rates are between 20% to 70%, with 50% infection rates very plausible. It is unknown whether social distancing will impact that number significantly.

-Is there transmission from immune people? Unknown. Maybe not.

-Can this method keep peak cases in the UK below 20,000 to 40,000, so that healthcare capacity in ICUs and ventilators is OK?

But a ‘flatten the curve’ argument (eg introduce strict social distancing policies) has 3 other points in favour:

-The delay might be enough time for a drug therapy treatment to be identified (my estimate is that we may know about efficacy for some antivirals by end April)

-We don’t know how hot weather will impact the virus. In the UK, a delay into summer or closer to summer might help

-A lower peak still helps with healthcare (ventilators and ICU beds)

Let’s look at some other brutal maths. 1 year or 2 year infection rate estimates might range from 20% to 70% of the population. Swine flu had a 20% infection rate and 150K to 575K people died (CDC data). Swine flu also circulates every year now since 2009.

A 20% infection rate seems very plausible. The case fatality rate (this is for when you are assigned as a case and so doesn’t include non-symptom or mild cases that don’t get reporting) is very hard to know.

As explained by Max Roser / World In Data , it’s not time invariant, it varies with country and many other factors.

Screenshot 2020-03-13 at 20.03.26.png

The case fatality rate is the share who died from the disease among individuals diagnosed with the disease. The CFR is calculated by dividing the total number of deaths from a disease by the number of confirmed cases. It is expressed as a percentage and used as a measure of disease severity. 

But, still a case fatality rate ranging between 0.1% and 0.5% would seem plausible, with a heavy impact to the elderly (3% to 8% CFR).

Coronavirus-CFR-by-age-in-China-1.png

These are the brutal maths for the UK and Italy.

Italy has about 60m people and >22% are over 65 —> over 12m elderly.

If 20% are diagnosed —> 2.4m and at 4% CFR —> 96,000 deaths. It’s easy to see how this might range up to 200,000+ easily with double diagnosis/CFR.

In the UK, it’s about 18% of 67m —> this is also 12m elderly. The maths is the same, if 20% are diagnosed —> 2.4m and at 4% CFR —> 96,000 deaths.

Let’s hope the CFR comes down but it’s going to be quite sobering.

Screenshot 2020-03-13 at 20.27.19.png

If you consider there are about 540K deaths in a year in England/Wales. This will be an excess of 15 to 20% of the annual base rate with a heavy elderly skew.

curve.jpeg

If the UK ends up with more or equal deaths to Italy given it was earlier on the curve (see above for number of cases) compared to Italy - I think the UK’s strategy may be considered a government mistake. But, if UK remains under 20K cases for an extended time, it may end up sealing another 4 years of this government.

COVID $1m+ in prizes

#COVID $1m+ in prize money for important: blogs, journalism, innovation, public policy and other COVID ideas. "The prizes on offer:

1. Best investigative journalism on coronavirus — 50k

2. Best blog or social media tracking/analysis of the virus — 100k

3. Best (justified) coronavirus policy writing — 50k

4. Best effort to find a good treatment rapidly — 500k, second prize 200k

5. Best innovation in social distancing — 100k

6. Most important innovation or improvement for India — 100k

What might be an example of a winning project? What if this attempt to build scalable respirators succeeded? That would be a natural winner. Or a social distancing innovation might be the roll out of more meals on wheels, little libraries, online worship, easier ways to work from home, and so on. The vision is to give to people whose work actually will be encouraged, not to give to Amazon (sorry Jeff!), no matter how many wonderful things they do. These are not prizes you apply for, they will be awarded by Emergent Ventures when a significant success is spotted." …. via Tyler Cowen, Marginal Revolution - Emergent Ventures.

Details here.

COVID, resources, notes, thoughts on present and future

As of 7 March, my updated view (subject to wide change). COVID is worse than seasonal flu by 10x - 20x and Pandemic flu (Swine Flu) by 4x, but the worse case panic (eg Spanish flu, 1918 )is overstated because treatment is likely (60% chance IMO) coming in 6 months and there is decent chance (but not overwhelming) that hot weather will slow progression (although not completely halt). So reality lies between, “don’t panic, it’s flu” and “panic, it’s Spanish ‘flu pandemic”.

IMG_1401.png

Risk is around healthcare services being swamped by exponential growth of critical cases before treatment is approved. Medium-term (1-2 year), est of 50% infection rate is plausible. 6-12 months for treatment (80% chance, my view; remdesivir my top choice, baricitinib others possible). 24 month+ for vaccine (70% chance, timing a challenge).

IMG_1381.jpeg

The political fall out is unknown. The US has been unexpectedly poor. South Korea and Singapore have been (expected?) good. China after a (arguably) slow start has since performed strongly. UK response (as judged by testing seems OK but NHS beds already stretched over winter.

The second order economic impact also quite varied, base case is a 6 - 12 month slow down (50% recession chance) with recovery thereafter, but with downside risk from US particularly given impact to small business. Markets to remain volatile. (OECD downgraded World GDP from 2.9% to 2.5% on containment scenario, but would fall to 1.5% under a non-containment scenario).

Good single source data: World In Data

Useful Dashboard from @avatorl

Further round up below.

Present

-WHO report and collections of COVID resources

-Prediction markets

-My notes from healthcare conference 

-health/economics/social/market impacts

Future

-what to do about  future pandemics

-incentives for innovation and stores of knowledge

-dissuade state-appropriation, but increase state capacity

I thought I’d put my growing collection of COVID thoughts in one place. There is much expert information on the web so I would point you to that. I have studied healthcare investing for 20 years, but the still puts me in a distinctly amateur category. My major contribution here is to think about what to do about the medium to long term, as it looks highly like there will be recurring pandemics (as there have been before). But before getting to that have a look at a collection of papers sources to start.

Current Resources

On what to do this is WHO: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/advice-for-public. (Mostly you can find advice on this readily on the web)

This WHO report: Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19) is pretty much (as of early March) one of best details one stop information sources. 

“…In the face of a previously unknown virus, China has rolled out perhaps the most ambitious, agile and aggressive disease containment effort in history. The strategy that underpinned this containment effort was initially a national approach that promoted universal temperature monitoring, masking, and hand washing. However, as the outbreak evolved, and knowledge was gained, a science and risk-based approach was taken to tailor implementation. Specific containment measures were adjusted to the provincial, county and even community context, the capacity of the setting, and the nature of novel coronavirus transmission there.

…. China’s bold approach to contain the rapid spread of this new respiratory pathogen has changed the course of a rapidly escalating and deadly epidemic. A particularly compelling statistic is that on the first day of the advance team’s work there were 2478 newly confirmed cases of COVID-19 reported in China. Two weeks later, on the final day of this Mission, China reported 409 newly confirmed cases. This decline in COVID-19 cases across China is real…”

But

“…COVID-19 is spreading with astonishing speed; COVID-19 outbreaks in any setting have very serious consequences; and there is now strong evidence that non-pharmaceutical interventions can reduce and even interrupt transmission. Concerningly, global and national preparedness planning is often ambivalent about such interventions. However, to reduce COVID-19 illness and death, near-term readiness planning must embrace the large-scale implementation of high-quality, non-pharmaceutical public health measures. These measures must fully incorporate immediate case detection and isolation, rigorous close contact tracing and monitoring/quarantine, and direct population/community engagement.”

Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China. Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention (Feb 24)

Also very good overview of China situation. JAMA article: https://jamanetwork.com/journals/jama/fullarticle/2762130

There are many non-symptom carriers (see notes below from HC conf). But NEJM letter shows it by case study: https://www.nejm.org/doi/full/10.1056/NEJMc2001899

My own notes on COVID from a recent healthcare conference are here:

Notes on #COVID from Healthcare Conference (Boston). 

Prof. Suggests many (>50% ?) of ppl at conference likely already exposed. 

40 - 60% eventual exposure rate for US population plausible (and in his view likely but timing unknown). 

(Based on Washington State and several papers) seems many ppl show no/mild symptoms, many still have virus post-symptoms, unknown if still shed virus post symptoms/asymptomatic but likely. Many likely undetected so death rate still unclear. Info. v. Fluid. (Lots of papers suggest this, also suggestion two strains already in circulation, one more virulent)

Good news: Children seemingly not at higher risk of death. 

Bad news: Elderly, and already ill, at higher risk. 

Unknown but possible: 

-if summer/heat will kill off virus (to what extent, as it is heat sensitive; but it’s novel)

-if mutation and numbers make this another seasonal infection on going (hiigh uncertainty, but mosre seem to be leann this way)

US hosp. Could be overwhelmed (mixed views in room, decent votes for stretched, decent votes for very overwhelmed). 

Future cures/vaccines: Possible treatments in 2020 (not advice, but Gilead’s Remdesivir on treatment, Incyte/Lilly’s baricitinib; Moderna on speed of its novel vaccine) plus quite a few more.

Commercial vaccines not likely for 18-24 months+, but from 2022 vaccines possible + maybe routine. Treatment could be in 2020.

Large debates on exponential compounding (or not) and views on risk plus uncertain second order impacts on business, supply chains, remote working, politics etc. Plus observations that if we can manage for COVID can we manage for eg. Air pollution or other big killers.

Now for more quirky resources:

A daily newsletter summarising developments: https://cronyclecovid19.substack.com/

This GJ Open Prediction market on COVID. I am participating (and along with other questions). My Brier score current 0.7 vs crowd at 0.8 (so I’m 0.1 better - scale is 0 to 2), but some of the questions very hard!

Screenshot 2020-03-05 at 09.36.31.png

It really focuses the mind if you try and actively predict and record why you are predicting an item.  https://www.gjopen.com/challenges/43-coronavirus-outbreak

In that worth looking at Tyler Cowen’s column on exponential growth forecasting (and compounding) vs base rate effects.  https://www.bloomberg.com/opinion/articles/2020-03-03/how-fast-will-the-new-coronavirus-spread-two-sides-of-the-debate

And my own previous blog on how to forecast drug success rates.

Future

Very broadly there are a few interlinked impacts to think about.

  1. Public Health impacts

  2. Economic Impacts

  3. Social Impacts (cultural change, and interlink with economic)

  4. (Maybe less important but who knows) Financial market impacts

My sense is that people in the US thought the US system would have handled this better (especially the testing, which is behind). And while the population in China are upset and emotional, the WHO have come down positive on China’s handling, and looks like South Korea and Singapore also faring well. The end game looks like 50%+ of US (and world) eventual infection. Death rates are always difficult to put in context - as most people had no idea that season flu was such a big killer, and most completely underestimate the killer effects of eg. Air pollution.

Still - my *amateur* sense is that this is broadly in the 2009 swine Flu pandemic bucket. This was:

“…estimated that 11–21% of the then global population (of about 6.8 billion), or around 700–1400 million people contracted the illness -  About 150,000–575,000 fatalities..” see https://www.cdc.gov/flu/spotlights/pandemic-global-estimates.htm

So if COVID is going to hit about 50% - that’s about 4bn people (or 4x swine flu), with an unknown death rate.

If the range is 0.01% to 3% (worse case) that’s about 400,000 to 140m deaths.

IMG_1398.png

The Economist put it:

A broad guess is that 25-70% of the population of any infected country may catch the disease. China’s experience suggests that, of the cases that are detected, roughly 80% will be mild, 15% will need treatment in hospital and 5% will require intensive care.

So it’s in line.

Set against that is if drugs we have are effective and when (and there’s good reason to believe that we have some effective treatments which we are testing now) and longer term how quickly we can develop a vaccine.

There is also going to be much scrutiny about capacity in this area.

The above picture is why some are calling for much stricter/organised public health interventions. They argue that flattening the potential exponential growth and extending the time allows for treatments and less stress on health capacity.

Especially it is about 5% of cases in ICU eventually.

(2) China is showing signs of slowly starting a normalising process - from companies I speak to - but it looks like economic impacts from lost work and supply chains etc. will last longer than recent swine flu or SARS.  So 6 to 12 months+. A good portion of that doesn’t come back. (eg a shoe maker who makes a shoe a day, is going to lose all those shoe-days) but productivity levels should come back as it has done previously.

So large short term impact, but world recovers. This is essentially the Ray Dalio view (see end) but large uncertainty and caveats. This is mostly because of the intersection with social-politics eg inequality, wroker protection. If people are forced not to work, and they don’t have any safety net then this hits poor people and gig economy people potentially very hard. Lots more possible here to think about.

(3) More lasting could be social impacts. Will we find new ways of working and learning? That actually work for us. Will remote working start to show its worth. How will we think of events? 

How will US politics change ? China politics ? Singapore has seemingly strengthened its reputation. Healthcare could rise up the US political agenda and weak economies tend to be no good for incumbent politicians. Will this be bad for Trump?

Does China become restricter or does free speech become easier?

Could this be better for the environment? Air pollution?

Will we travel less for a time? Or even longer?

How successful will our open collaborations be? Will this spur future investment in more healthcare infrastructure and genomic technologies.

Will this cause a re-think of long global supply chains, and spur investment in local supply for food, energy, staples? Does this strengthen localism? Populism?

COVID is going to throw many of these social-political questions open. Especially the intersection with the poor and the healthcare questions in the US.

(4) Markets both debt and equity have displayed volatility as they deal with both emotion and evolving data.

To the extent that they impact funding for businesses (eg capital raising for innovation) and that bear markets are hard on the psyche then they may have an evolving role.

But mostly (from what I see) economists (eg Larry Summers, Jason Furman) have identified fiscal responses as most appropriate. See: https://www.washingtonpost.com/opinions/2020/03/03/how-economic-policymakers-can-respond-growing-economic-shock-coronavirus/

OK. On to my contribution here about the long term and innovation:

Future innovation

Pandemics are very likely (over 90% chance) to occur (again) over the next 50 years and likely over 100 years+ time frames. This pandemic was predicted by pandemic experts.

This is because:

-humans are increasingly interconnected at speed

-the way we treat/breed animals is not changing any time soon

-wet markets and similar not likely to change soon (though I think in eg China there will be a crack down)

-current viruses/germs eg influenza, pneumonias have been around for 1000s years

-virus/germs will constantly mutate

-containment will slow, likely never stop, transmission

I don’t have more room to explain these assumptions but will leave links at the end, but if you don’t accept this premise then you will under-rate what follows

What to do about future pandemics

-cultural learnings eg greetings

-innovation

We can slow transmission and in small cases potentially even stop by a change in cultural norms. We know the behaviours - washing hands, hygiene, don’t shake hands, cough into elbow  - but compliance can be greatly improved. This is inexpensive. Still, it is unlikely to stop all future pandemics. It’s worth recommending more strongly. Sanitation has already given use huge gains here and can gives us further gains.

That leaves us with treating pandemics and vaccinating once pandemics start. This is a question of innovation.

Incentivising Innovation

The market arguably has inefficiencies with dealing with i) rare diseases and ii) developing world diseases and iii) diseases that have not occurred, but we can predict are likely to occur.

This is due to those markets being risky and/or commercially small and/or commercially small risk-adjusted (a market might be worth $2bn but at 1% chance of success, $20m risk-adjusted would be of small value).

Policy solutions that have (at least partially) worked have been  a) granting longer/extra intellectual protection for rare diseases and b) agreed forward purchasing contracts for developing world diseases.

(a) Has helped areas such as rare genetic diseases, and multiple sclerosis (and other classified rare diseases) in the developed world (mostly) and 

b) has helped in malaria and certain other developing world diseases (where commercial markets are smaller) - forward buying by the Gates Foundation amongst others.

Such mechanisms have mostly failed in I) developing new antibiotics against resistant strains, II) certain other developing world diseases,  III) pandemics.

One negative factor in this is state appropriation of (mostly) private innovation. Rich countries eg US have been guilty of this as much as poor countries. The US essentially disregarded protection (or threatened to break the patents) on anthrax treatments in seeking to stockpile such medications cheaply. [https://www.wsj.com/articles/SB1003966074330899280 ]

This causes a large disincentive to work on vital areas, if profit-seeking entities will lose out on their R&D development costs for such treatments.

I would propose:

-partial speed up of regulatory response for areas of unmet medical need

-international “state capacity” in anteviral, antiobiotic, mRNA, pandemic research

-forward purchase fund for pandemic vaccines and medications

Partial speed up of regulatory response for areas of unmet medical need

The gold standard in medical research are randomised controlled trials (RCTs). They are costly and slow, but typically generate the most robust results.

For low commercial value areas, RCTs (and previously trials needed before RCT) are too costly for entities to perform give the risk. 

But, mostly health regulators will need RCTs before approval of a drug to be able to know the risk/benefit of a medication vs standard of care.

This has led some thinkers (eg Peter Thiel) to argue that regulators need to change or relax standards to allow quicker and more innovation on to the market. The challenge is that this may let onto the market ineffective treatments that cost lives or damage the credibility of the system.

One compromise would be to let medications on to the market where - in a controlled fashion - when there is enough evidence of safety/efficacy but no RCT. A full approval would be contingent on  future RCTs being performed in a reasonable time frame else the drug would be with drawn from the market. The drug would also be withdrawn if the RCT fails.

If medications for areas of high unmet need - for instant pandemics or other diseases with limited treatment options - would be released this way, the net benefit would be positive.

Industry would pay for such a faster service, and this could cut drug development time in half.

International/national “state capacity”

Faster regulation alone would not help unless there were medications to test.  Given the long and uncertain cycles for viral pandemics, it’s beyond the risk tolerance for many private entities. There are further complications because mutations might mean the plan A vaccine proves to be relatively ineffective and has to be made again under plan B.

However, I believe this is an area where even libertarians or perhaps “state capacity” libertarians might concede a non-private institution or set of institutions might be useful.

Essentially, I would be arguing for a form of Health ARPA where a part of the HARPA is focused on pandemic anteviral research, and antibiotic research and possibly other areas of unmet medical need. This is a sibling idea to the NIH but more targeted at likely pandemics.

If such an organisation had capacity to response quickly to evolving pandemics, then it should be able to share royalties with any other parties needed to scale medications to commercialisation, if it needed private partners to help scale quickly.

There should be positive spillover (cf NIH) in the years when no pandemics occur.

Forward purchase fund for pandemic vaccines and medications

Now (A) We have an organisation that can respond quickly with a new medication, and (B) a regulatory process which can speed through medications for high unmet need (eg pandemic) but how will we pay and keep incentives especially if we need multi-stakeholders to develop the medication.

This is where a forward purchasing fund or contract comes  into play. This fund acts as a guarantee that a certain amount will be paid for the innovation in a swift manner.

On the one hand this should give a guarantee to private or other players that the innovation won’t be appropriated for nothing. But, also given that it’s a guaranteed market, and the risk is lower, the price for the medication can be set in a more fair manner especially for poor countries (cf HIV).

This is similar to were the Global fund and GAVI already sit. I do note the US govt has approved funding quickly on COVID, but still better to have it already in place.

Conclusion

Given pandemics will re-occur, we should look to set up capacity to deal with pandemics, regulation that can be swift and responsive and a fund to guarantee a fair price for innovation and set incentives accordingly

Post Script: It turns out Bill Gates haas also written on this topic and he many similar ideas and sources (and talks more about infrastructure build) examples of certain pandemic preparation here. https://www.nejm.org/doi/full/10.1056/NEJMp2003762

On why Pandemics will (re)occur: https://www.worldbank.org/en/topic/pandemics#1

Ray Dalio on COVID

Where did UK science go?

Where did all the science go? Can ARPA bring it back.

-I suggest there will be no more big UK life science companies

-Network agglomeration effects are important

-An UK ARPA and its location should be placed carefully

-I suggest we need more innovation in institutions

 

Take $8.5 billion? No. Take $10 billion? No. Gilead, in 2017, bidding against itself, paid $11.9 billion to acquire Kite Pharmaceuticals.  I am sad because Kite may have developed into a $40bn, maybe $100bn, market capitalisation company over time, and now we will never know.

 

The same goes for the UK’s Shire. Takeda Pharmaceuticals completed its $59bn takeover in 2019.

 

Kite Pharmaceuticals is a small biopharmaceutical company focused on cancer therapies and CAR-T (chimeric antigen receptors T-Cell) technology. As of January 2017, Kite had a market capitalisation of $3bn and it had its IPO (initial public offering)  in 2014. Gilead had to raise its bid several times before Kite’s board succumbed. The boards and shareholders of smaller companies such as Kite and Shire are unlikely to be able to resist cashing out to dollar-rich, large drug makers. Gilead’s management indicated limited value was attributed to CAR-T success in solid tumors or Kite’s earlier stage technology.

 

This trend is intriguing as it suggests that the new creation of large biopharmaceutical companies organically from small ones may seldom happen again. Certainly, it seems unlikely that the UK will create another  bio-pharmaceutical powerhouse such as GlaxoSmithKline or AstraZeneca. Shire was the last likely candidate and now it has gone to Takeda. The US might still establish a new one.

 

I posit the reasons are threefold: the UK has under-invested and continues to under-invest in science and innovation; the network and agglomeration effect where scientists creatively clash to form new ideas is diminished in the UK as a whole, and, as I described earlier, large, cash-rich global biopharma companies are now in the habit of acquiring their smaller peers before they grow large.

 

This has negative long-term implications for UK science and private wealth creation. Private company inventions often rely on publicly-funded research ideas as the initial spark. Development is costly, risky and seemingly not well suited to publicly funded enterprise.

 

I’ve heard investors speak of the Chomsky trade, after Noam Chomsky, which suggest if you want to know what’s worth investing in, look at what US federal research funding organisations, like DARPA or the National Institutes of Health (NIH), are investing in today, and then go long.  

DARPA—the Defense Advanced Research Projects Agency— was established in the late 1950s to accelerate development of U.S. satellite technology. Research at DARPA led to a number of breakthroughs, including GPS technology and the Internet. The inventions at Kite were based on ideas first formed by Dr Steven Rosenberg at the NIH. Kite fits the Chomsky trade.

Sir John Bell recognised this value in his Life Sciences: Industrial Strategy report for the UK government (August 2017, green paper). Bell proposed an Health Advanced Research Programme (HARP) which looks to be modelled on the US DARPA, and suggested ideas to reinforce the UK science value proposition. Bell sees the NHS as a source of value particularly in the data sets that it owns on behalf of UK patients.  Bell suggests a strategic goal for the NHS to engage in 50 collaborative projects with the life science industry over the next five years ranging from late-stage clinical trials to large-scale data analysis and evaluation of medical technology and diagnostics. 

 

I can think of at least three large technology companies who could use health population data analytics to transform the UK health service. The UK has a unique and valuable healthcare data asset because of everyone’s singular NHS number. The majority of the UK population already gives away its data, if only we could be persuaded to use our data as a force for good.

 

This will be relevant in any discussion of a UK DARPA equivalent for energy as well.

 

“Ben, none of my neuroscience colleagues want to work in the UK. Not even Cambridge University and the like. Funding is 50% lower, salaries are 50% lower, there are many interesting labs in the US or China. We will not come to the UK,” one of the world’s leading neuroscientists under 40 years old told me. There are several cutting-edge science labs in the UK but post-graduates and professors, if they have a choice, are joining US labs; or increasingly settling in China.  The US government risks this innovation too with possible cuts to the NIH.


Scientists (in a now closed Pfizer lab) in Sandwich, UK, discovered that experimental heart drug UK92480 had a specific side effect on male subjects - plenty of erections. Viagra was born. Serendipity came into play, much like it did in 1928 when Alexander Fleming discovered penicillin as a result of mould falling on his petri dish.  Black Swan author, Nassim Taleb, has advocated for the need for randomness in drug discovery. As Google scientists have noted, creative ideas happen around ‘focused serendipity’. A network effect from sharing and debating new scientific ideas tends to happen round hubs and those hubs are in short supply in the UK. 

 

Arguably, Cambridge, and the South East of the UK, has a hub. A Cambridge-Oxford-London (with the EU drug regulator, EMEA, formerly in London) triangle has possibilities. Brexit has ended the London location of EMEA and Cambridge is still nothing like the huge biopharmaceutical hubs of Boston or California in the US. Senior management at Genentech mentioned to me that there are over 250 biotechs currently in the south San Francisco area alone. Research networks are important intangible assets for a country.  The lack of UK hubs, combined with the paucity of leading scientists and fewer occasions for serendipity, discourages the discovery, nurture and growth of fledgling biopharmaceutical companies. In economist speak it’s all about the agglomeration effect (or lack of) of networks.

 

In this regard UK Brexit is unhelpful. For all Brexiteers’ talk of trade, isolation dampens creative networks. More damaging is the time and energy spent on figuring out Brexit and its aftermath that could otherwise be spent working out how best to support and nurture UK science. Hopefully Bell's proposal will not be lost in the Brexit noise. There is also the cost of UK institutions losing EU funding, which is likely to be substantial. If the UK government materially increased funding in science  (perhaps using Bells' HARP modelled on the USA’s DARPA) this would be an investment for long-term gain, with the value felt over generations (penicillin, for example, was a 1920s discovery which we continue to benefit from.) This could be investment worth borrowing for.

 

Turning to using Brexit as a force for good, the UK government seems to be contemplating a UK version of ARPA. The UK Policy Exchange has argued “ARPA should focus on developing advanced technology on a 10-15 year horizon.  Unlocking transformative technologies, rather than basic research or incremental near-to-market innovation, is where ARPA’s efforts should be centred and ARPA must embrace failure.” One can argue whether these are easy words and how implementation of a culture that can learn from failure or understand how transformational research happens (it often relies on basic research and can also rely on combining inventions across fields in novel ways). Still, one aspect missing from this vision is any argument over place and agglomeration (the word agglomeration does not appear in the report). To this end, I would rely on the work of Tom Forth, Stian Westlake (co-author of Capitalism without Capital) and others to suggest that the geographic placement of ARPA to catalyse stronger innovation agglomeration effects is vital. ARPA will be too small in itself to catalyse a whole network, if it is placed far away from current networks (see also the Office for National Statistics’ move to Newport, far away from hubs), but if it is placed in the London triangle, an opportunity will be missed to strengthen networks outside of the South East. Losing much of the AstraZeneca science in the north of England over the last few years was a national calamity in this regard. 

 

I argue that an UK ARPA or,  even better, both an energy focused ARPA-E and a health based HARPA, would be powerful long-term investments for the UK to make. Politically, it would meet aims of “State Capacity Libertarians” and also innovation elements of “Green New Deal”. A focus on innovation and experimenting with novel research is to be recommended. Its geographic placement in order to benefit from and catalyse agglomeration effects should not be underestimated.

 

I further argue we must be much more experimental in types of institution, forms of institution and how institutions might spur innovation. Reading Colin Mayer’s Prosperity, and exploring economic historians’ work it seems we used to have more forms of institution, corporate bodies and people trying to achieve innovation through various organisations. Today we seem more ossified. Sure, we have ideas on charter cities and the like but shouldn’t there be more competing big ideas? Maybe there are and I am missing them. Still, I argue there should be many, many more.

 

Psychologists, such as Daniel Kahneman, show humans are often poor at making good long-term investment decisions. I am not confident the UK will invest sufficiently. There’s always still hope from serendipity. 

Follow Benjamin Yeoh, @benyeohben

His microgrants programme (£1k for positive impact) is open www.thendobetter.com/grants

 

References:

Policy Exchange: https://policyexchange.org.uk/wp-content/uploads/Visions-of-Arpa.pdf

@stianwestlake

@thomasforth

On State Capacity Libertarianism, see @tylercowen 

On Prosperity, Colin Mayer - blog here. Microsoft CEO recently noted this has reformed his view of business in capitalism and society.

Quality of Government matters more than size of government for human development, education and life expectancy

“...It’s not the size of the wave but the motion of the ocean…”

  • Quality of government (QGOV) seems more important than size of government (SGOV) for a variety of domains

  • QGOV is more important for peace, for human development, for health and for education 

  • This exploratory work extends the work of Ed Dolan (Niskanen Centre) and comes with many caveats due to interactions.

  • Outliers such as Singapore and Ireland may be worth closer examination for what is working well in smaller governments 

  • QGOV may have increasing importance at higher levels of development 

  • This may provide exploratory evidence that “state capacity” in certain domains eg innovation, health and education - might be important. This adds to the debate on “state capacity libertarianism” and in terms of current UK policy may inform on whether investing in an “ARPA organisation” or other areas of state capacity is a positive return on investment.

Background 

Economist Tyler Cowen posited a notion of State Capacity Libertarianism. Cowen subsequently linked to a blog referencing the work of Ed Dolan.

The work (2017) developed two scores - QGOV for quality of government and SGOV for size of government.  Dolan analysed two measures of freedom and prosperity the Legatum Prosperity Index and the Cato Human Freedom Index and concluded - with several caveats due to interactions and unknown causality- that QGOV was more important than SGOV. See his work for definitions of SGOV and QGOV.

Idea 

I was intrigued if this work extended to other areas that I am interested in both personally and professionally. (I help allocate $13bn in pension fund and other investments in global equities with an interest in healthcare). 

I chose to look at: 

  • -Peace

  • -Human Development 

  • -Life Expectancy (as broad measure for health)

  • -Education 

As measured by other organisations.

Methods 

I hand inputted data on:

  • SGOV, QGOV, 

  • Human Development Index (UN HDI)

  • Education Index (EDI, as component of HDI)

  • Life expectancy Index (as component of HDI)

  • Peace index (as calculated by non-profit Vision of Humanity)

(Sources at end, errors possible)

I ran scatter plots and Pearson correlations. I tagged for World Bank classifications of income, and by geographic region.

Results 

QGOV vs Peace

QGOV vs Peace.png

Correlation = (-) 0.71 | R2 = 0.5

Higher quality of government had a 0.7 correlation with the Peace Index (where lower score = more peace)

An interactive version of this data, where you can also view by income level (use drop down box) and geography (click circle legend labels) is below. The trend holds for all levels of income.

SGOV vs Peace

Correlation =  0.32 | R2 = 0.1

Size of government had a weaker 0.3 correlation with the Peace Index (where lower score = more peace)

SGOV vs Peace Index.png

The overall correlation is weaker and also suggestive that large governments correlate slightly with the peace index.

An interactive version of this data, where you can also view by income level (use drop down box) and geography (click circle legend labels) is below. Different income levels change the trend line, upper middle level countries inverting - suggesting smaller govts here are better for peace but only weakly.

Geography also changes the trend, with Latin America countries suggesting smaller very weakly trending. It’s weak enough maybe to be considered almost no trend though.

My overall takeaway is that the trend is weak vs QGOV but it is intriguing that income levels change the pattern as do geography.

Peace comment 

As often there are intersections on what components might go into peace. Experts may disagree as to the validity of this index for peace however the methodology is clear and it has some support. 

I find it interesting as it is another lens to judge human “progress” on and therefore what types of government might best foster progress.

QGOV vs HDI, Human Development Index

Correlation =  0.75 | R2 = 0.57

Quality of government has a 0.75 correlation with the Human Develpment Index where larger HDI = more developed.  

QGOV vs Human Development Index.png

It looks to me that the slope is stronger in more developed nations. Gently sloping until about 0.75 on HDI, and then steeper.

An interactive version of this data, where you can also view by income level (use drop down box) and geography (click circle legend labels) is below. You can observe this as the slope is stronger for the richer nations (and a measure of GNP is included within the HDI) but it is the same direcction for all incomes, slightly weak for middle.

SGOV and HDI

Correlation =  -0.53 | R2 = 0.28

Size of government has a -0.5 correlation with the Human Develpment Index (where larger HDI = more developed) suggesting larger governments are moderately better than small governments with some notable outliers such as Singapore, South Korea and to some extent Ireland, and Switerland.

SGOV vs HDI.png

An interactive version of this data, where you can also view by income level (use drop down box) and geography (click circle legend labels) is below.

The trends are weaker split by income level, with there almost no trend in high income and upper-middle income.

I now present the components for life expectancy and education (that go into the HDI seperately).

QGOV vs EDI

QGOV vs Education Index.png
SGOV vs Education Index.png
QGOV vs. Life exp (1).png
SGOV vs. Life exp.png

Comments on EDI, Life expectancy; observations and arguments for state capacity.

Given the weighting in the HDI that life expectancy has, it is unsurprising that QGOV also correlates better than SGOV for life expectancy. 

While there are social and cultural determinants of health of which government would only be a component, I argue that it is still noteworthy that it is not size but quality of government here that seems to count.

Again given the weighting in the HDI for Education, it is again unsurprising that QGOV correlates better than SGOV.

Of note, Chile and Kazakhstan appear on education and to some extent life expectancy as higher perfomer small government countries to join Singapore and Ireland, Switerland.

I chose to examine education and health because in many countries there is on going debate as to the structure and capacity that governments should play in health and education markets. 

This line of argument would suggest where countries do wish their governments to be involved then quality of that government or perhaps “state capacity” could be an important factor. 

This is noteworthy in the UK where there is wide support for a National Health service across the political divide and also for state funded education providing the majority of the populations education. 

Two other tentative observations. It is worth dwelling on where small governments seem to be doing well. I would note Singapore and South Korea and perhaps to an extent Ireland and Switerland. Those countries would be good examples of small, high quality goverments. 

My own theory here is also the importance of social and cultural determinants of health and education. 

For instance, it is unknown what the compliance rate for medications are in various countries. A higher drug medication compliance of cost effective genetic medications in Singapore (arguable driven by a social factor of listening to your doctor properly?!) or of the positive/negative health outcomes of effective elderly social care across countries are mostly unknown. 

A second observation is the seemingly stronger slope in the high HDI nations. There may be many explanations for this and all the caveats expressed by Dolan also apply but it might be an intriguing provocation that quality of government becomes even more important in extending the progress of already highly developed countries. 

Caveat

As Dolan notes there is considerable interation between SGOV and QGOV as larger governments have a tendency to be of better quality, but Dolan runs multiple regressions here:

“…simple correlations like this need to be interpreted with caution, as there are complex intercorrelations among multiple variables. In this case, we have a correlation of -0.42 between SGOV and QGov, that is, a tendency for larger governments to have a higher index of quality. We also have a correlation of 0.74 between QGOV and the log of GDP per capita (richer countries have higher-quality governments) and -0.48 between SGOV and the log of GDP per capita (richer countries have relatively larger governments).

Dolan can run multiple regressions which I do not have the capcity for, but Dolan concludes:

We can use multiple regression to untangle these interactions, using HFI* as the independent variable and using QGOV, SGOV, and the log of GDP per capita as the dependent variables. When we do so, we get a strongly statistically significant positive coefficient on QGOV and no statistically significant relationship at the 0.01 confidence level for the other two variables. The overall correlation is 0.79, essentially the same as for the two-variable relationship shown in the left-hand scatter plot above…”

I suspect multiple regressions would confirm similar and hope a profesional academic might look into this

Conclusion

I tentatively extend the work of Dolan on the size of government and quality of government to look at four further broad indices of 1) peace, 2)  human development, 3) education and 4) life expectancy. 

In all four cases, quality of government seems to be a more important factor than the size of government. This would be tentative evidence for theories that emphasise the importance of quality - perhaps state capacity - over the size of the state, where societies favour a state role in any given area. 






Notes and Caveats 

Data sheet link available on request. It’s not very tidy but all in good faith. Image below. I may have made errors in the data, as it’s my late night pet -project.

Do read the Ed Dolan Caveats in his blog but repeated here.

“...As in any statistical study, we should be cautious about drawing conclusions about causation. There is nothing in these results to suggest that making a country’s government bigger will automatically make it better. At the same time, it is hard to deny that there is a strong tendency in the cross-country data for larger governments to be better governments, when by “better,” we mean better able to protect property rights, better able to offer impartial civil and criminal justice, and less open to corrupt influences.

Readers are also encouraged to think about the country-by-country data reported in the chart and table above. There is a lot of variety in the world. Too strong a focus either on statistical regularities or on selected outliers can draw us too strongly toward conclusions that, in reality, admit of many exceptions.

For example, the small-government city states of Singapore [is]  rightly admired for [its] prosperity and economic freedoms. However, it gives one pause to note how many small-government countries enjoy neither. Chad, Bangladesh, and the Democratic Republic of Congo  are just the outliers among a whole cluster of countries in that category.

Similarly, a look at individual countries shows that our statistical indicators of “big” and “small,” or of “good” and “bad,” do not always line up with what we mean by these terms in other contexts. For example, many people in the West would readily name Russia and China as countries with governments that are conspicuously both big and bad. Yet, although Russia and China do fall into the southwest quadrant of our chart, they do so only barely. Statistically speaking, neither country is an outlier on either variable…]

Ed Dolan’s two part blog on SGOV and QGOV. 

Peace Index can be found here: http://visionofhumanity.org/indexes/global-peace-index/

Human Development Index and components (both the education and life expectancy - I use 2018 data - ) can be seen here: http://hdr.undp.org/en/data

World Bank Classificatinos are from 2016 (as the 2018 xls wasnt’ working when I compiled the data). The Visuals are H/T Flourish Studios and Google Sheets.

Tyler Cowen on State Capacity Libertarianism 

The Table of data I used is below.