2020 has been the year that vague epidemiological theories that were mostly of interest to us nerds suddenly became mainstream. Herd immunity, which previously was mostly the purview of epidemiologists in mouldering public health departments, suddenly became worthy of mainstream discussion and endless debate. Infection fatality rates, which were previously restricted mostly to infectious diseases conferences, have suddenly become headline news around the world.
And most recently, we have the debate about cost and benefit. Cost-benefit analyses are a pivotal part of the epidemiological landscape, because as public health experts we are all too aware that there are limited resources to play around with when it comes to health interventions, something that has been even truer this year than ever before. It is a sad fact that restrictions to combat COVID-19 come with a cost, and that cost can be measured in human lives.
As Sir Austin Bradford Hill famously said, “Health statistics represent people with the tears wiped off”.
But the problem with cost-benefit analyses is that they are enormously complex. Take lockdowns, which have been derided by regulation opponents for months as the most costly mistake any government could make.
How do we evaluate whether that’s true?
The Tricky Truth
Well, firstly we can think about the costs. Immediately, this becomes a fraught question, because there is no simple answer to how much lockdowns have cost. We can look at how much the economy has dipped in various places around the world, but famously some places that enacted lockdowns have done relatively well economically and some places that have not locked down have suffered greatly. In fact, it is remarkably hard to address the costs associated with a lockdown, not just because every lockdown in every country has been different, but because the likely alternative — more widespread COVID-19 infection — is costly too.
So costs are hard. What about benefits? Well, even there it is amazingly difficult to come to a concrete answer. There is the obvious primary benefit in terms of reduced COVID-19 spread, and the potential to improve public health during a lower period of pandemic growth (i.e. ‘flattening the curve’), but there are also secondary benefits that are often ignored by regulation opponents. Influenza rates have fallen precipitously in places with COVID-19 restrictions, road death tolls are at historic lows, and many other regular issues have potentially been improved by government actions this year. While these are individually quite small points — in the grand scheme of the pandemic, a 15% reduction in the road toll is perhaps not as important as it might be otherwise — together they represent a potential benefit that any reasonable assessment would include. It’s also worth noting that, despite the efforts of some to minimize the pandemic, the benefits of preventing widespread infection from COVID-19 may be rather large, not just to public health but to the economy as well.
Indeed, a recent report from the International Monetary Fund found pretty much exactly this — while there are likely to be economic harms associated with locking down, there are also probably benefits. Moreover, much of the economic restriction in most places was probably down to voluntary restrictions on movement, with people restricting their movement as cases increased. According to the IMF, there is probably financial benefit to lockdowns if they are conducted early in the pandemic course because “letting infections grow uncontrolled can also have dire economic consequences”. In fact, the IMF depressingly notes that we are unlikely to see a rapid economic recovery from COVID-19 once restrictions ease because much of the financial impact is caused by the virus itself and not government regulations.
Which brings us to the point of all of this — cost-benefit evaluations are incredibly difficult. I imagine there will be arguments at health economics conferences for the next decades about which countries saved money through government action, and which would have been better off with a lighter touch. It will probably be years before we have a good idea of the exact ratio of cost and benefit that each policy entails, which is perhaps not surprising given how messy decision-making in this space can often be.
Letting infections grow uncontrolled can also have dire economic consequences
It’s also worth noting that, even when we talk about relatively specific measures like ‘lockdowns’, we are describing wildly different situations across the globe. In Sydney, Australia, where I live, the lockdown never included a stay-at-home order, and was generally much lighter than in many places in the world. After about 2 months of pretty heavy restrictions, we opened up again slowly and thus far have not experienced a large resurgence in cases (fingers very much crossed!). But we also had restrictions that other places did not — travel between Australian states has been strictly limited for most of the year, and getting into the country is all but impossible even for citizens.
Decision-Making Is Hard
Which brings us to the problem — when people decry government action as too expensive, they are often making the argument without much, or any, evidence, and usually don’t bother to define terms. Yes, some restrictions are probably, on balance, harmful, but which ones? Where? What could improve them? These are all important questions that are incredibly difficult to answer, but are usually misrepresented as some sort of easy yes/no choice.
There are of course already efforts to quantify the impact of various policies, but even then the evidence is mixed. If you read the IMF analysis, some restrictions such as stay-at-home orders may be of minimal benefit if the majority of workplaces and schools are already closed. Conversely, minimalist lockdowns that do not last very long appear to damage the economy with very little benefit to public health. It is likely that some restrictions in the past year have cost more than they benefited — equally, it is probable that many places did not enact restrictions that would have greatly improved their situations.
Like I said, this stuff is difficult. There’s a reason I became an epidemiologist rather than a health economist.
Ultimately, we must acknowledge that from a scientific standpoint it is really quite hard to know precisely the best way to go. Sometimes I am very glad that all I have to deal with is facts, because making political decisions based on conflicting viewpoints and the “best evidence” (which is often quite slim) is terrifying.
The only thing we can be fairly sure of, in these troubled times, is that those expressing absolute certainty about the economic benefits of lifting — or imposing — restrictions are probably wrong.