The looming relaxation of coronavirus lockdown measures is exposing the public to the messy basis of scientific fact-building.
The coronavirus pandemic continues to sweep around the globe. Cases and deaths are still rising in some countries (Russia, Brazil), while others (China, South Korea, Germany, New Zealand, Austria) appear to be over the worst and are beginning the relaxation of lockdown measures.
In certain countries, which have either been hit harder or are having problems getting on top of the pandemic – almost invariably due to being slow to react in the first place – there is a much tougher decision to make. They might be over the worst, but they also might not be out of danger, and yet the economic pain is considerable: so when, and how, to reopen the economy?
This dilemma is, regrettably, exemplified by the USA. The country was slow to react to the pandemic, chose not to implement WHO recommendations, and has a lower quality of societal healthcare than many other countries at a similar level of development despite spending the most on a per capita basis. When Alan Bennett wrote in his play Habeas Corpus that “The air is black with the wings of chickens coming home to roost” he could well have been describing the perfect storm that’s currently hitting the US healthcare system.
The economic pain currently felt by US citizens, coupled to a threadbare safety net compared to that offered in Europe, is creating an enormous pressure on the workforce. As of April 30th, over 10% of the population are listed as unemployed, and a decade of economic gains has been erased in a matter of weeks. It is partly this pain that’s manifested in protests against the lockdown in the US – whether from the unemployed, the politically partisan, or Elon Musk – and the mixed messages from the White House in particular are adding to a confused and conflicted picture.
So why the uncertainty? Why isn’t there a clear protocol for when and how to ease or release lockdown measures? Why this paradox of a rational agoraphobia, when people are unsure or afraid to open the door and leave the house? In part it’s because managing the coronavirus pandemic has revealed the messy business of fact-building in science.
The public tend to think of scientists as dealing with facts, which is why scientists are generally viewed as trustworthy and reliable. But facts become slippery things when you’re at the cutting edge of human knowledge. Experimental results are subject to interpretation, assessment by different means, different labs, and so on. It is the accumulated weight of evidence – based on different assays, carried out by many different people, in many different labs, in many different countries all around the globe over an extended period of time – that ultimately lets us state facts such as “the information for making protein is encoded in DNA” and so on.
It’s this very slipperiness that is often exploited by anti-science movements (creationism being a prime example) to portray scientific consensus-making as unfocused, equivocal, and weak. Because there is no higher authority to which scientific knowledge defers and draws its conclusions, the best that science can ever say is “This is as much as we know right now. Anything more is speculation”. As Richard Dawkins has noted, scientific knowledge acquisition is about cranes (building from the ground upwards) rather than sky-hooks (starting from the heavens and working down). It is this very plurality, and the plodding and methodical nature of it, that makes scientific fact-building so powerful, but like all consensus measures, it’s slower than a decision made by decree.
Like no other phenomenon in living memory, the coronavirus pandemic has revealed to the public this messy business of establishing scientific facts. How many people are infected? How many are asymptomatic? How soon does someone become infectious? Can people be reinfected? What distance is safe for interpersonal contact? Are masks protective? And on and on and on. There is no firm answer to any of these questions yet. Evidence is being accumulated, and the consensus is clearer for some questions than others, but science takes time. That’s the whole point.
And that’s what makes the decisions to relax lockdown measures so fiddly. They have to be based on the science, but are requiring a speed of scientific consensus-building that simply doesn’t exist. You take the best available data, draw your conclusions, and take the plunge. Essentially, every decision on relaxing lockdown is going to be an experiment conducted in real time, but with potentially ghastly consequences if it’s bungled. That’s a horrendous predicament for both scientists (who parse the data and provide the interpretations) and politicians (who make the decisions) to be in.
Currently the economic and scientific worlds are colliding. Obviously we can’t stay in lockdown forever – this is economic suicide. But if we reopen too soon or too quickly, then we’re endangering and maybe even dooming the very people whose care is the first duty of any government. It’s an exquisitely difficult and unwelcome balancing act, and one that bears more than a passing resemblance to chemotherapy.
Cancer chemotherapy means deliberately poisoning the body and hoping that the cancer cells (which replicate quickly) are snuffed out faster than the healthy cells (which replicate slowly). At a societal level, we’re engaged in the same thing – we’re in lockdown to kill off virus transmission and prevent our healthcare systems from being overwhelmed, but we’re doing so by incurring an economic cost. And the economic cost is epic, epochal.
We’ll never know the alternative either. Like evolution, there’s no way of rewinding the tape and repeating the process a different way. We’ll never know exactly how many people would have died if we did nothing, or did something earlier or later – we’ll only know how many people did die or became unemployed because of what we did do. And what we did do, what we will do, at some point, is tell them to open the door and venture back out into the world.
Politicians and the public at large are being treated to the most intimate and the most definitive kind of dilemma that stalks every scientist for every day of their professional lives. What do I know, how do I know it, and how sure am I that I have the right answer?