COVID, why so many are mostly wrong, or only a little correct.
Summary: Vaccines are likely to give protection for at least c. 12 months and likely to reduce transmission rates, but vaccine hesitancy, mutation and maybe some amount of re-infection will mean that the virus stays with us permanently like influenza does. However like ‘flu we will find this disease manageable. We may also never know for sure why certain groups (eg men) suffer higher mortality.
The medium to long term speculative thoughts is that this crisis will spur more innovation and creativity across several domains.
This is because many may conclude it is human innovation that has saved us and will save us. Similar thinking may be applied to climate challenges (I expect Bill Gates will double down on this in his next book). I also think - while with much pain- the creative arts will also react with more creativity, although extremely crimped near term, as people will have to find new ways of reaching audiences/consumers.
This is a long form read over why so many people are fairly wrong (or only a little correct) about COVID and why the information seems so confusing. I will attempt to touch on:
Predicting vaccines
Immunity and immune memory
Cross-protection
Different strains
Different genetics
Super-spreaders
Cultural differences
Data reporting differences
Complexity models
Re-infection
Narrow vs broad thinking (fox vs hedgehog)
Ideology
Back in August 2020, I made the point estimate judgement of an 80% chance of a vaccine by the end of 2020. Significantly above some observers estimates (although a good number of healthcare investors were making similar judgments). I noted some of my thinking in my August blog.
What’s useful to note is why many expert observers were more pessimistic. I can summarise that those group were focused on past experiences, focused on the risks (which were clear) and anchored on previous examples. They were not willing to place faith in mRNA technology that had not produced commercial vaccine before even if much of the theory is well established.
Source: Google Finance
Stock market prices embody future expectations that people with money (not reputation or press articles) buy and sell at. It’s very difficult typically to be ahead of this collective wisdom of the crowd. Still with in a stock price reveals a signal that can be interpreted.
If you look at Moderna’s (one of the vaccine makers) stock price - which embody many factors including politics, interests rates, etc - there was much of a run up from March to early November before the positive pivotal data in November. There are still future unknown events to come eg launch and distribution, but looking back one can suggest that investors with money were not super surprised by early November as much had already been “priced in” over March to October.
Mostly investors do not bet directly on a question such as “will there be a COVID vaccine in 2020?” But indirectly on stocks or other assets and prices which lead to money win/loss outcomes. These investors were suggesting through the Moderna stock price signal that there was a decent expectation of some success here.
I won’t rehash all the many science and socio-political points that went into my August forecast but suffice to say there are a number of people who do make and essentially bet behind these predictions.
Cross-immunity, herd-immunity, re-infection, strains, genetics and why everyone is only a little bit right.
Mostly - with rare exceptions - media articles will take a single look at a narrow domain question and present evidence in favour of a certain answer. Sometimes coloured by an ideology. (Even studies tend to look at a narrow question).
For example, if by ideas, you strongly favour individual choices you may balk at the idea of government imposed lockdowns and so you are drawn to articles suggesting Sweden or a “herd immunity” process as a way of proceeding without lockdowns. The actual data from Sweden does not matter too much - especially when you can find media articles to support your inclination.
Another example is re-infection. There are cases of re-infection, but it seems from what we know re-infection is rare but it can and does make article headlines.
[A distant simplistic parallel that people might understand is that you can get chickenpox twice (or rather, shingles after chickenpox) but it is rare.]
Still depending if you have an idea already about what we should be doing then a case of re-infection or an article about it can be used to support that view.
So you can put all of these statements together which have a little bit of truth to them.
There are asymptomatic carriers of COVID.
You can gain (some amount of) cross-protection for some (unknown) amount of time by exposure to other coronaviruses including the common cold.
This level of protection will vary with strain, genetics, immune responses and memory - which in turn vary with factors such as age.
Different strains can act with different people’s genetics to cause varying levels of severity of disease.
Different people’s immune system will “remember” the virus differently (age, strain etc. variant)
All of this becomes confusing because we would like a simple answer of do I get cross-protection or not? Not the complex answer of it dependant strain, time and genetics (and perhaps environment) and will not be static.
And from some of these simple parameters that can change we can have events such as “super-spreaders” where one person or one event (eg a sports or a night club evening) seem to cause many infections. The interplay of all those infection factors can produce those results. Or not.
In that sense - a distant parallel is with weather forecasting. We can put together large trends to fairly accurate assess total infection cases in regions over a few weeks or days, but predictions at the single person or event level are much more uncertain.
Other factors which interplay are cultural differences and reporting data differences. Certainly, if you have ever travelled through Japan then the cultural differences in hygiene and also in the populations general adherence to rules from authority (also see China, Taiwan) are very different from England or the US.
As an aside, I do think the politics of mask wearing especially in the early days of the pandemic in Europe and the US were surprising to me - although not in hindsight. There was (and is) a strand of thought as to how so simple an intervention could have an impact. A walk through a poorer country or even a more mixed one like South Africa would not scorn “simple” interventions so heavily (access to proper toilets and hygiene make huge impacts). I do think - again with hindsight - it is surprising that more weight was not given to first principles - in that we knew the virus was carried in aerosol droplets (and like colds, flus) and so the physical methods of transmission could well be interrupted by barriers like masks.
Putting this all together what does this mean? In my view, vaccines are likely to give protection for at least c. 12 months and likely to reduce transmission rates, but vaccine hesitancy, mutation and maybe some amount of re-infection will mean that the virus stays with us permanently like influenza does. However like ‘flu we will find this disease manageable. We may also never know for sure why certain groups (eg men) suffer higher mortality.
The medium to long term speculative thoughts is that this crisis will spur more innovation and creativity across several domains.
This is because many will conclude it is human innovation that has saved us and will save us. Similar thinking may be applied to climate challenges (I expect Bill Gates will double down on this in his next book). I also think - while with much pain- the creative arts will also react with more creativity, although extremely crimped near term, as people will have to find new ways of reaching audiences/consumers.
Here are a mix of random thoughts and questions that I considered when thinking about COVID:
Where did SARS-CoV-2 come from?
Some uncertainty, but seems very likely that it came from animals (zoonotic, maybe bats) and crossed into humans. Evidence that is was present in China in November 2019 (as early as 17 Nov) and maybe earlier. Open question. We don’t know if the virus mutated in animals and then crossed to humans. Or crossed to humans and then mutated and crossed human-to—human.
Definitely seems NOT lab made (IMO).
https://www.nature.com/articles/s41591-020-0820-9
Why have certain regions (Taiwan, South Korea, Singapore, Hong Kong) handled the pandemic better than others (Italy, Spain, all of Europe, US….)?
…Same for sectors and businesses ?
The high-performers had:
-Very prepared systems
-Responsive public health authorities
-Responsive general public
-Responsive private companies (at the request of the public health authorities)
But, they had very prepared systems + public because:
-They had dealt with the trauma and cost of SARS-classic
The actions were/included:
-Early responses (masks, restrictions)
-High testing (fast deployment + development of tests)
-Strict isolate, contact, trace protocols
-Travel bans and similar
-Tracking of quarantined people
There is a 124 point list of what Taiwan did:
https://jamanetwork.com/journals/jama/fullarticle/2762689
…Same for sectors and businesses ?
Some sectors/businesses:
-had more awareness on what exponential growth can look like (tech), and/or,
-had more respect for the seriousness that China were taking (and put weight on that signal)
-more redundancy built into their supply chains (typically, as product considered critical, eg insulins, other must-have pharmaceuticals)
-more cash on balance sheets to deal with emergencies (typically these were maybe ear marked for litigation or other catastrophic events)
-ability to remote work
-business models that are resilient to COVID (eg. Video conference calls)
This has lead to:
(Parts of) Tech + Health + Utilities > most business
Big business > small business
Within countries / regions
Some regions influenced by:
-understanding of exponential growth (Tech community in San Francisco)
-population density
-culture
-strains
-maybe weather?
Open Question: Why are death rates different across European regions, Asia etc ? Also, knows as heterogeneity.
We don’t know.
We do know:
-Data is patchy
-Testing criteria are different
-Testing efficacy varies
-Older people, men, people with underlying diseases (eg heart problems) are more at risk
(But even here, there are regional differences with US rates of hospitalisation in the young much higher than in other regions).
-Different strains
-Different genetics
-Different cross protection
No one has a model that explains these intersecting factors.
One tentative suggestion is the difference in “viral load” or dosage of virus you get on first infection may explain part of this.
We do know viral load can have an impact with other viruses.
Open: Why are some people more susceptible than others?
This goes across many subgroups: Children, Men, but also differences in the young who do get impacted.
Open Question: Why are death rates so low in children? This pattern is consistent across regions even if rates vary. Explanations include:
Children’s immune system being more flexible and rapid
Adult immune system may over react due to priming with other coronaviruses
Adult immune system being slower
Other varieties of explanation…
See: Christakis https://twitter.com/NAChristakis/status/1243883141900763137
Open Question: Why are death rates higher in men? (also Co-morbidities)
We don’t know. Partial explanations that I have seen touted but with no evidence include:
-men being worse at hand washing/hygiene
-men being more likely to smoke or use vapes.
But, essentially whatever your underlying risk the virus seems to magnify it (eg age, male, underlying diseases)…
Open Question: How long will immunity last? (Likely ranges, we have looking to be quite a few months, I’d would hone in on at least a year)
Partly Open Question: How long does a person remain infectious? (We have some likely ranges)
Partly Open Question: How exactly is the virus spreading? (While we know it’s via viruses in droplets, we don’t really know if it’s surviving to infect people in open spaces as opposed to enclosed spaces. There’s tentative evidence that open spaces are safer (some outdoor mass events protests have not lead to super-spreading spikes but some internal ones have, also cf. different experiences in Italian cities, also Brazil) . Even if viruses can survive on cardboard in a lab how that works in the real world is unclear.)