“At the end of all this, let’s try to remember that the geniuses who told us not to worry about coronavirus are the same geniuses telling us not to worry about climate change.” –Jimmy Kimmel
In the last few days, much has been said comparing the scientific consensus on anthropogenic climate change with the growing consensus of public health officials about how to respond to Covid-19. As philosophers of science, we think this comparison is inapt and dangerous. And while appealing to science is an understandable response to politically motivated downplaying of the threat posed by Covid-19, what is needed is more critical discussion of public health policy.
At present, there are very few controlled studies or peer-reviewed articles about Covid-19. The findings that are published in scientific journals end up being ubished as letters or brief reports, and this means the published material on the coronavirus has not received a full and thorough review. What is more, there’s been little time for scrutiny between public health experts from overlapping fields like virology, epidemiology, medical genetics, sociology, medical ethics and health economics, but this scrutiny is required to verify scientific findings and develop robust policy. All of this means there has been no independent audit of the Covid-19 “evidence” circulating in public discussion.
By contrast, human-induced climate change is a hypothesis that is 100 years old, and it has been carefully studied, criticised, audited and looked at by a host of different disciplines. And even if one of the disciplines involved in climate science were unreliable, this would likely be uncovered by a nearby discipline. As Michael Polanyi noted back in 1962, scientific disciplines are not hermetically sealed and a flawed line of inquiry would be apparent, even to an attentive layperson, because nearby disciplines would expose its shortcomings.
Given the disparate level of scientific scrutiny applied to climate change and Covid-19, it is misleading to compare the industry-financed and bad-faith questioning of climate science, to questioning the rapid response of scientists using limited models of the coronavirus and drawing on data that is at best incomplete. And while there is a growing policy consensus about how to respond to Covid-19, consensus is only a good guide to credibility and reliability if the relevant group of scientists is an appropriately structured and communicative community. Unfortunately, there is currently no well-ordered scientific community studying Covid-19 and its impact, so the emerging consensus could be the result of any number of all-too-human biases.
This emerging consensus without a rigorous scientific scrutiny is problematic from both a scientific and political point of view. On the scientific side, since the coronavirus is new, scientists should have some reasonable ground for disagreement among themselves about its nature and what policies should be used to combat it. In fact, an independent survey of expert forecasts suggests that there is huge variance and uncertainty in expert predictions, generally. So, the absence of scientific disagreement over Covid-19 would be highly surprising, implying informal coordination, not the ordinary give and take in the marketplace of scientific ideas.
Science, after all, does not reach reliable results because scientists have uncovered some magical method for finding the truth on the first pass. Science reaches reliable results because scientific claims are usually subjected to intense scrutiny – a stress testing of the concepts, data, and methods over an extended period of time – by members of rival research programs. Most scientific claims are flawed. But the process of mutual criticism eventually weeds out these flawed claims, leaving behind a much more reliable body of knowledge than could possibly be produced on the first pass.
Consider, for example, the premature scientific judgment of Dr Robert Koch, who “discovered the microbial causes of anthrax (1876), tuberculosis (1882), and cholera (1883)”. When he announced he had a “remedy for tuberculosis”, it made headlines everywhere. Since tuberculosis was then untreatable and a leading cause of death and illness, this was welcomed with enormous relief and enthusiasm. Alas, it was shown that talk of a remedy was decidedly premature when the clinical data was actually studied by independent experts.
Similarly, in climate science, when new data appears – surprising developments in the rate of ice-sheet melt, or big changes in the range of values of equilibrium climate sensitivity coming from global climate models – the scientific community erupts with internal debate and takes years to sort out the meaning of the anomalies. However, incredibly surprising developments are occurring with the spread of Covid-19 as we write – the low death rates in Germany, Japan, and Korea; the high rate of symptom-free test-positive subjects in Iceland and in a small Italian village where everyone was tested. And sorting out such matters will require time and care.
As it is, the available data for the coronavirus is very confusing or even contradictory, and unraveling the numbers to make sense of what is going on is very difficult. The availability of tests varies massively from place to place. Moreover, tests in some places are taking three to five days to come back, so the current numbers of positive results reflect the situation in hospitals three to five days ago. Meanwhile, deaths are reported in real time, and the discrepancy between test reporting and death rates means the so-called case fatality rates are unreliable. Yet this unreliable data is being plugged into simple models with massive policy implications, including the shuttering of entire economies and the loss of livelihoods to millions of people in multiple countries around the word.
On the political side, shutting down entire economies and shuttering people into their homes will have profound consequences. Public health research points to a strong correlation between a good economy and good health. So, if there is a major Covid-19 induced recession, there is likely to be an increase of domestic violence, suicide, drug addiction, poor neo-natal care, and so on. Needless to say, weighing these costs against the benefits of saving lives by shutting down the economy is not a simple or value-free exercise.
Given the profound economic, social and political impact of the coronavirus, people are entitled to know how the costs and benefits of different policies are being weighed. However, the way experts and governments are assessing the risks is not being communicated to the rest of us. As the response to a recent study that shifted UK policy makes clear, transparency in public health policy is important because it makes political decisions accountable to stakeholders and citizens. What is more, transparency is a means to prevent the negative effects that follow group-think and the growth of conspiracy theories. And in a case like Covid-19 where many experts are part of a government team, transparency is needed to ensure that political considerations do not shape the experts’ views.
With that said, we understand that policy-makers and their scientific advisors have to make time-sensitive and difficult decisions in light of uncertainty. Nevertheless, they could do a much better job explaining their key modeling commitments. How many lives do they expect to save? How long do they expect economies to be shut down? What negative consequences do they expect, in terms of lives and welfare, from these policy interventions? And what is the likely impact of the huge economic rescue packages being implemented all over the world?
At present, government responses involve hastily thought through social experiments that draw on public policies that are ill understood and that may have grave consequences even when they work out as roughly intended. At the very least, government policies in response to the spread of Covid-19 will have severe effects on the economy. The impact of society-wide lockdowns on social well-being are not well understood. And since the coronavirus is new, we don’t know what will happen once governments lift controls absent a vaccine.
So, at this point it is worth asking whether we are prepared to continue these measures for the 18 months we are told it will take to find a vaccine. Ultimately, what is needed is more and not less critical discussion of the science and politics behind our response to the coronavirus. “Trust the science” is a better slogan when the science, like climate science, is mature, multi-disciplinary, and has been subjected to intense scrutiny.
Put otherwise, the self-described geniuses who tell us not to worry about climate science have been debunked over and over again. And while we clearly do need to worry about Covid-19, we also should worry about hastily constructed responses that could do more harm than good – for in a pandemic, all of us have to live with the consequences of each other’s decisions.
Eric Schliesser is a Professor of Political Science at the University of Amsterdam and Eric Winsberg is a Professor of Philosophy at the University of South Florida.
This article is part of the Agora series, a collaboration between the New Statesman and Aaron James Wendland, Professor of Philosophy at the Higher School of Economics. He tweets @ajwendland.