Lockdown was never right for Africa. Half the population is 19 or under, highlighted in this report; and known prior to COVID, of course. On the cost side of the balance sheet, other risks are massively dominant over that posed by COVID-19. Living conditions mean that suppression was never achievable in any case. Costs of lockdown were obviously going to be horrific, because recession means starvation in contexts of poverty. What a mess for those countries that did lock down. And those that didn’t seem to be doing fine, COVID-wise: e.g. Malawi, whose supreme court prevented the government from locking down.
Aside from all that, it’s clear that there’s a great deal of uncertainty about why some places get hit so much harder than others by COVID-19. Sweden is held up as being hit hard, and blamed; but that ignores the fact that many other European countries that did lock down were hit a lot harder. Why? I favour the following theory: we don’t know.
Epistemic humility in all matters relating to medicine is always appropriate.
If I guess the time, and get it right, do I know the time? No, says common sense, and nearly all theoretical and formal epistemology. If I guess that it will rain tomorrow, am I any better off? Presumably not. Yet we assess predictions almost entirely by whether they are right.
I do think Swedish predictive work was broadly accurate, compared to, for example, the models produced by Imperial College London. But more importantly, I think their stance was rational. They did what was right given the evidence. That isn’t the same as being right in the sense of landing on the truth. But there’s nothing either epistemically or morally significant about the latter. The former, however, is both. Sweden behaved more reasonably than any other country, or perhaps at least as reasonably as the most reasonable, given that there was room for reasonable disagreement.
The stance on Sweden is another version of the intellectual intolerance of the age. And it ignores the evidence. Sweden has done well: not perfectly, but no country has, that I can think of. Whether it comes out tops long-term is up in the air. But there is good reason to think it will – at least as good as the reasons to think it won’t.
Soon I’ll have an opinion piece out arguing several of these points. In particular, regulation is just the wrong idea in the first place: people need to be consulted. And that’s not a watery option, it’s the way to get effective solutions that are context-specific.
We wrote this letter a couple of months ago in response to an editorial in the Lancet suggesting that opposing lockdowns was neoliberal. I continue to be surprised by how the world hasn’t noticed that, in fact, extreme measures to combat COVID-19 shift the burden from the wealthy to the poor, who suffer more from the measures than from the disease. It’s a disease that primarily affects the old, and thus primarily the wealthy. This is true even if people who are of the same age fare worse if they are lower down the socioeconomic scale. That is unsurprising, extremely so; what is surprising, and what outweighs that effect massively, is that this disease is so much more dangerous for demographics that are dominated by the wealthy of the world. I still feel that has not been grasped in the global north. So, I’m very pleased to have this letter out. Maybe it will change the perspective just a little towards a more global one.
https://www.ecologi.st/post/covid/ Evidence from phone data that W Cape adherence to lockdown has been quite strict thus lack of adherence is less likely to be the cause of the spike there. Thanks to Monomiat Ebrahim for the share.
Wondering if this means it is more likely to be:
1. A demographic feature such as age
2. A latitude feature – around the equator, COVID-19 has generally been less prevalent
3. A climate feature
4. High concentrations of “starters” leading to a critical mass for an epidemic
…add your pet hypothesis here!
Check the entry on Pearl’s blog which includes a write-up provided by the organisers
Video of the event is available too
This was published in 31 May in the Sunday Independent (South Africa) but for some reason they have not made this available online. So:
- Here is an image of what was published (presumably fine to share because it was in print only) We were set up to lock down (The Sunday Independent)
- Below is the text I submitted. They did not run the final text past me and there are some irritating editorial bungles that make the published text less readable (and sometimes ungrammatical). So, the one below is probably a better read.
We were set up to lock down
There’s a standard line. South Africa’s decision to lockdown when we did was sensible. Little was known about COVID-19 and its potential impact here. Since then, the situation has changed. We know more about how the pandemic is likely to unfold and who the disease affects, and we have made preparations to deal with the likely impact. The economy continues to deteriorate each day we stay locked down, and with it, people’s livelihoods. It is now time to unlock; in fact, unlocking is overdue. Decisive steps should now be taken to restore the economy, education, health services, and other pillars of the nation to their “new normal” function.
This familiar story is wrong. The evidence available at the time we locked down supported doing something more moderate. Lockdown was not the right response for South Africa to the threat COVID-19 posed in South Africa. Its potential benefits for a population the majority of whom is under 27, and can expect to be dead by their mid-sixties, did not outweigh the certain costs to the one in four living in poverty, and the many more who would join them on losing their livelihoods. Besides, it was obvious that, for most of the population, lockdown was impossible, due to overcrowding, shared sanitation, and the necessity of travel to receive social grants.
Contrary to what’s said, the evidence hasn’t changed. The relevant characteristics of COVID-19 were apparent by the end of March, when the decision to lock down was taken. Much of it is cited in an opinion piece published on the same day lockdown was announced, 23 March, a piece arguing that a one-size-fits-all approach could not be applied to achieving social distancing. The piece was written by a colleague and myself, unaware that that same day the country would move in exactly the opposite direction to the one we advised. We wrote several further pieces, and by 8 April I was sure that lockdown was wrong for Africa, including but not limited to South Africa, and published an opinion to that effect. The next day lockdown, was extended.
What has changed? Is it the evidence, or is it intellectual fashion?
It’s possible that those of us making anti-lockdown arguments two months ago are like stopped clocks that inevitably tell the right time when it comes. But the salient evidence was there all along. The dominance of age as a predictive (who knows whether causal, or how) risk factor for serious, critical and fatal COVID-19. One credible infection fatality estimate published in March based on data from China was 0.66%, with a marked age gradient. A credible systematic review concluding that school closures were not supported by evidence was published in early April. Perhaps the major uncertainty concerned HIV as a potential vulnerability of the South African population. But it was known early that treated HIV status was not correlated with COVID-19 risk, and in early April early results emerged that this might be true even for untreated HIV. Those same results are being relied on in current opinions, in some cases by people who dismissed them at the time.
If that’s correct, and many will deny it, then how could so many academics, politicians, analysts and commentators have got it wrong? And what stops them seeing it now?
Obviously there are social costs to admitting error, and perhaps psychological ones too. Certainly we’re better at spotting each other’s mistakes than our own. But I think there was something else in play, which continues to confuse us. We felt we were presented with two options, and chose one of them as a precaution. This was not the reality, but a product of the modelling approaches that informed policy and perception alike at the time, and that still play worryingly prominent roles in the policy approach.
These models had and have three misleading features.
First, they did not and do not estimate the health burden of COVID-19. This is because they model the effects of reduction in social contact without properly modelling the effects of the actual measures taken to achieve that reduction. A free decision to stay home is represented in the same way as being chained to the bed, or indeed being shot dead on the spot. These have different consequences for mortality, none of which show up in the models. Perhaps this doesn’t matter in the developed world, where economic downturn means poverty but not starvation. But it’s crucial in the developing world, where recession often means death.
Second, and relatedly, contextual differences were obliterated by the use of using a simple percentage scale to measure the reduction in social distancing. This meant that, for instance, a 60% reduction in social distancing was represented as the same thing in Geneva and Johannesburg. Whereas, of course, that is an outcome one takes by implementing policy decisions, which would usually be informed by the local context.
Third, the different scenarios modelled were then given different names, re-introducing a qualitative difference between them that was simply absent in the input. Qualitative differences were thus obliterated in the inputs – perfectly reasonably, from a modelling perspective – then introduced in the output. Where before we had (say) a 40% reduction in distancing, we have “mitigation”. And instead of (say) a 60% reduction, we have “suppression”. These began life as arbitrary points on a continuous scale, as the modellers would have been the first to admit. But with different names, they became treated as qualitatively different strategies. Moreover, the leading models at the time predicted hugely greater benefits from suppression compared to mitigation.
Thus, almost magically, the huge range of possible measures, varying between context depending on context and policy priorities, became transformed into a choice between lockdown and no-lockdown. Lockdown was exemplified already in China and Europe as a set of specific restrictions, and not as an abstract percentage reduction in social contact.
All context, all nuance, all qualitative factors were lost, washed out in a modelling exercise that was insensitive to contextual differences when formulating its inputs, and unwise in giving qualitatively different labels to its outputs.
Against this background, precautionary thinking naturally overtakes cost-benefit thinking. Proportionality gave way to precaution. The anti-COVID measure has a clear form: restricting on economic activities and confining people to their homes. It is so much more effective than any other measure that it presents us with a binary choice; other measures are pathetically ineffective by comparison, because in the process of de-quantifying the effectiveness of suppression over mitigation, regional differences have been lost. The choice is between action and inaction, and the cost of doing nothing appears huge: just look at the footage from Italy. Yes, it will be painful, but it’s better than the alternative.
But the precautionary approach was never necessary. There was always a range of possible actions, the costs of lockdown were always obvious, and the most significant determinants of the risk profile of the South African population were known.
Now, European countries have passed their peak, and we are again ignoring our own context. Our curve remains exactly the same as it was the day we went into lockdown (a straight line on a logarithmic scale, which is the relevant scale here – for both cases and deaths). Lockdown made no difference, if those graphs are to be believed; and it’s hard to know what other data to look at. The decision to unlock is, as Glenda Gray pointed out, not backed by any scientific case. Yet it’s the right one, not because the evidence changed, but because it was right all along. Lockdown was always wrong for Africa, including South Africa.