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Even before the omicron variant emerged, many European countries were discussing whether to reintroduce lockdowns. In the UK, there are debates about vaccinating schoolchildren and about who should get booster jabs. These policies are controversial because they involve trade-offs. Even if lockdowns save lives, they can harm people’s health in other ways. Even if vaccines save lives, they can have side-effects. How should we decide when medical interventions should go ahead?
Here’s one possible answer: we shouldn’t adopt interventions that we predict will do more medical harm than medical good. Of course, that answer leaves open questions about things like liberty or fairness, but it seems an obvious starting point: a lockdown that killed more people than it saved would be perverse.
However, things get complex when we ask how the “more good than harm” principle is interpreted and used in policymaking. This is because real-life cases typically involve trade-offs between very different sorts of outcomes, for different types and numbers of people.
Consider, for example, lockdowns. Their “benefits”—lives saved—are very different from their “costs”—say, to mental health. The benefits also tend to fall on older people and their costs on younger people. Finally, the benefits are more concentrated than the costs, in the sense that the number of people whose lives are saved is far smaller than the number of people whose mental health is harmed. So, do they do more good than harm?
Health economists have tools for addressing this kind of challenge, which have long proved popular with policymakers. These tools are complex, but, very roughly, they follow a two-step process.
First, all the different health outcomes are converted into a common scale, allowing us to compare, say, the “badness” of mental health problems against the “badness” of getting COVID. Second, all of the different expected benefits are added, all the different costs are added, and the two numbers are compared to see if the overall effect is positive.
These tools play an important role in decisions about drug funding, for example, by the National Institute for Health and Care Excellence (Nice) in the UK. Many argue that they ought to play a larger role in thinking about emergency measures such as lockdowns.
Decisions, decisions
Unfortunately, these tools are highly questionable. First, think about comparing very different sorts of health outcomes along a common scale. When doing this, we aren’t measuring some objective feature of reality, like how long a disease typically lasts, but making an ethical judgment about how bad it is to have a disease.
We soon run into a challenge about who is qualified to make these sorts of judgements. For example, do we ask doctors who are used to seeing the effects of certain diseases or patients who live with the disease?
This isn’t an idle question, because there are divergences between different perspectives, giving rise to the so-called disability paradox—that certain “disabilities” can seem to improve subjective wellbeing. In a study of 153 people with moderate to severe disabilities, 54% reported having an excellent or good quality of life. So, who’s the expert?
Second, the idea of simply adding up “costs” and “benefits” to do a giant comparison is also controversial because it can lead to counterintuitive conclusions. In principle, we might decide that letting a few people die is a price “worth paying” for ensuring that a (very large) number of people don’t suffer ingrown toenails.
Even worse, a focus on comparing aggregate outcomes can blind us to how costs and benefits are distributed. For example, we might recommend policies that help already relatively healthy groups, leaving marginalized or difficult-to-reach communities even further behind.
Does that mean that there is no way of deciding when the risks outweigh the benefits? Of course not. Some cases really are simple. And there are responses to the worries above.
What is important is to recognize that claims about the balance of harms and benefits don’t just express factual claims, they make ethical judgements. For example, about how bad it is to be ill or whether equality matters. And, although we can’t all be experts on epidemiology, we are all equally qualified—and, in a democracy, all obliged—to think through those questions ourselves.
Stephen John, The Conversation