Why Experts Disagree on How to Manage COVID-19: Four Problem Conceptions, Not One
Disagreements on how to manage the COVID-19 outbreak can be traced back to four distinct ways of thinking about critical problems that have informed policy making for decades. Benjamin Cashore and Steven Bernstein argue that policy makers need to be more self-conscious and transparent about which problem conceptions guide their choices when millions of lives are at stake.
One of the most troubling trends for the billions of people affected by the spread of COVID-19 is that there remains widespread disagreement among experts about how to manage this outbreak. Some early advice, evident in the initial British response, emphasized “herd” approaches that targeted less vulnerable populations for infection to create societal immunity. Other advice focuses on “flattening the curve” to buy time for hospitals, technologies, and vaccines to adapt and develop. Following different advice led some countries, such as Singapore, to react proactively with purposeful measures, while others needed to play catch up following massive outbreaks.
Meanwhile US President Donald Trump initially announced that regardless of scientific evidence about the pandemic, the US economy needed to reopen by early April while Brazilian president Jair Bolsonaro continues to downplay the virus in favour of maintaining economic activity. And, almost all countries have changed their approach in response to new ideas from experts amidst uncertainty and evolving knowledge about the epidemiology of the disease. Given that decisions made right now have profound implications for whether, when, and how millions of lives might be saved, and that governments around the world have committed trillions of dollars in emergency funding, it is critical that society and policy makers also understand why such divergent policy advice is being followed.
One explanation, largely overlooked, is that experts carry hidden cognitive frames about how to conceive of the problem at hand. These frames, in turn, strongly influence policy prescriptions. Our work on the global climate and biodiversity crises is useful for uncovering these latent influences. Looking back at 25 years of well-intentioned policies that have nonetheless frequently left society and policy makers frustrated over the outcomes, we uncovered four different ways experts and policy makers conceive of real-world problems that we also see at play in the current COVID crisis.
Type 1 Commons conceptions emphasize a type of collective action problem typically seen in the irrational over-use of resources. In the environment and resource sustainability world – owing to lack of coordination, planning and difficulty excluding access – individuals rationally overharvest resources such as timber and fish to the point of system collapse. According to this school of thought, individuals reason that since their neighbours will overharvest anyway, they may as well do the same since unsustainable depletion will occur regardless of their own choices. This “tragedy of the commons” orientation, which dominates schools of resource and agricultural economics, leads experts to focus on developing policies and institutions that limit the extraction of any resource to the same level as they reproduce – ensuring long-term economic sustainability.
Much of the expert advice for managing COVID-19 dynamics is derived from viewing problems this way. For example, while many politicians exhort consumers to limit purchases of toilet paper, hand sanitizer and medical masks, individuals are still, quite rationally, purchasing them in large quantities believing their neighbours will do so anyway. This individually rational but collectively irrational behaviour has already contributed to critical shortages where these items are most needed, such as masks and sanitizer for frontline medical workers and hospitals, thus endangering everyone’s health. Experts following the commons problem conception would decry moral shaming in these cases as ineffective, and instead focus on enforcing strong rules and quotas, prosecution of those engaged in price gouging, and strong penalties for non-compliance.
One risk of this conception, however, is the tendency to assume only strong government control or privatizing the resource will work and to eschew more cooperative arrangements that pay more attention to why or how a resource may be best used to address the underlying health issue. For example, this conception has arguably led to competitive national and international behaviour such as the Trump administration’s order to prevent 3M from shipping N95 respirators to Canada or Latin America despite the humanitarian consequences and high risk of retaliation. Working under this conception highlights the challenge of finding innovative institutional arrangements when political authorities act as if they operate in an ungoverned global commons or where markets fail to distribute vital medical equipment where it is most needed. We are seeing such dilemmas even within countries where the need varies by region, as in the United States where many governors are pleading for such institutional innovations to distribute desperately needed supplies.
Type 2 Optimization conceptions share Type 1’s goal of enhancing overall economic utility or what economists refer to as “social welfare”. However, they differ in that adherents are guided by a moral philosophy that evaluates solutions to any problem on whether they enhance economic welfare in society as a whole. The implicit normative position is that if solving one problem significantly worsens another, it is not economically rational to solve that problem. A common tool used to find optimal solutions is “cost-benefit” analysis, which turns every outcome into a single, comparative, economic value. When applied to an optimization problem conception, it frames solutions as if assigning the proper price to anything we value will allow the ”rational” assessment of trade-offs based on enhancing overall economic benefits. Policies would be designed based on willingness to pay for the benefit or to compensate those who take on greater risk for the benefit of the economy as a whole. This approach has led the US Environmental Protection Agency to value each statistical human life at about $9.47 million when calculating whether the economic costs of a particular environmental standard in dampening economic growth is “worth it” compared to the economic benefits that accrue from human lives saved owing to higher pollution standards.
This logic, prevalent among mainstream economists, not surprisingly also permeates President Trump’s Council of Economic Advisors (CEA). Casey Mulligan, a former CEA chief economist, captured this reasoning when he lamented, “We put a lot of weight on saving lives, but it’s not the only consideration. That’s why we don’t shut down the economy every flu season. They’re ignoring the costs of what they’re doing.”
For these reasons the debate among Type 2 managers during the Covid-19 crisis has been over how to value costs and benefits, i.e., how much is it optimally worth paying in financial stimulus, bailouts, aid or benefits for the economic losses caused by social distancing measures to achieve the benefit of reduced deaths from Covid-19. The substantive debate under this conception, to the chagrin of public health officials and epidemiologists, is not about how to adjudicate whether a “herd” or “flattening the curve” approach is best situated to save lives, rather it is about which of these approaches will be better or worse for the economy given the statistical numeric value of human life.
This problem conception accounts for the incongruity between Trump’s initial plan to relax restrictions and reopen the economy by Easter and statements by public health officials, including Dr. Anthony S. Fauci, director of the National Institute of Allergy and Infectious Diseases and member of the White House coronavirus task force, who said controlling the virus would require “at least” several additional weeks. It also explains Texas Lieutenant Governor Dan Patrick’s statement that despite being in the “high risk pool”, he, like “lots of grandparents out there” would choose his own death if it meant enhancing “[the economic future of] his children and grandchildren.”
Type 3 Compromise conceptions eschew cost-benefit analysis in favour of balance and compromise across different values. Substantively this occurs through “multi-goal” policy analysis in which various weighting exercises help governments understand and manage trade-offs that seek some type of balance among competing perspectives. Procedurally this conception underpins multi-stakeholder and dispute-resolution processes, and even the concept of “pluralism”, all of which aim to foster compromise among competing interests and goals. Adherents to a Type 3 conception tend to emerge from sociology, political science, the humanities and policy sciences because these disciplines focus not only on substantive outcomes, but also on the normative character and societal value of deliberative procedures that can enhance transparency, trust, and ultimately legitimacy. Type 3 approaches, adherents argue, often produce legitimate and effective decisions. However, strict adherence to compromise may undermine addressing particular types of problems, such as type 1 tragedies, which require more targeted efforts based on the nature of the problem at hand. For example, the Canadian province of Newfoundland engaged in Type 3 reasoning in which managers, facing uncertainty and pressure from a range of interests, set quotas higher than what biologists had recommended to address its Type 1 fisheries challenge. Resulting prescriptions led to the catastrophic decline of Newfoundland’s fisheries economy.
Type 3 conceptions have been applied to adjudicate the number of people allowed to congregate, what businesses and services are considered “essential” and should remain open, or how far to go in limiting civil liberties to enforce quarantine or social distancing policies. Operating under this conception, the wide variation in responses reflect attempts to balance various interests offering highly divergent ideas based on fundamentally different values.
In contrast, a Type 4 conception identifies those problems that for either Moral or Scientific reasons cannot be ameliorated by subjecting them to policy recommendations that emerge from Type 3 compromise or Type 2 optimization conceptions. The paradigmatic example is anti-slavery efforts. Adjudicating whether society should be against allowing humans to own other humans based on Type 2 optimality calculations, or compromise to permit some types of slavery, is considered abhorrent and absurd almost everywhere. Anti-slavery is considered a universal norm that cannot, by definition, be traded off against other values if it is to be achieved.
A second kind of Type 4 conception emerges from the scientific evidence about the problem at hand. Simply put, if scientific evidence is clear about what type of conservation efforts are needed to ensure addressing an irreversible problem like species viability or prevent catastrophic climate change, then policy makers only have two choices: they either undertake actions consistent with that scientific evidence or they acknowledge the problem cannot be solved.
Hence, the ability of governments and society to ameliorate Type 4 problems, owing to moral problems akin to slavery or scientific knowledge of ecological tragedies, requires their prioritization. Managers who conceive a problem in this way must therefore be careful not to inadvertently undertake policy options based on Type 3 or 2 rationales.
Disciplines that tend to treat problems as Type 4 include scientists who study ecological and biological catastrophes, as well as philosophers and social scientists who focus on how universally shared norms emerge and permeate societal attitudes. In the case of COVID-19, Type 4 thinking dominates among public health officials, perhaps most famously Dr. Fauci, who, despite personal risks, publicly confronted Trump’s initial Type 2 inspired pronouncements by providing scientific evidence about the disease and its spread. Type 4 thinking is increasingly evident in discourse and policy choices. For example, Ontario Canada’s Premier Doug Ford explained that “nothing is worth more than a life” while media commentators and New York Governor Andrew Cuomo criticized as absurd Type 2 inspired management decisions that propose to “sacrifice” the elderly to avoid economic collapse: “My mother is not expendable. And your mother is not expendable.”
Four Problem Conceptions Explaining Variations in COVID-19 Management
Our point is not that one conception is morally superior. It remains uncertain as to whether exclusively Type 4 management of COVID-19 will lead to undermining Type 2 economic welfare in the long run, or whether adoption by some governments of Type 3 compromise frames might explain why the virus has so quickly proliferated. At the same time, rendering explicit what are currently largely implicit cognitive frames at play should permit experts, public policy officials, and politicians to be more aware of, and transparent about, the competing philosophies governing their management choices. For instance, decisions to conceive of COVID-19 as a Type 4 problem means adjudicating lifting restrictions according to emerging science about whether herding, test and trace, isolation or some combination will save more lives. Yet, it is clear from the responses to date that those advocating for lifting restrictions earlier than later almost always emphasize Type 2 economic concerns over Type 4 epidemiology that prioritizes human lives qua human lives.
Governments owe it to citizens to make these moral philosophies and resulting calculi explicit since, with the exception of Type 4 conceptions, none of these approaches was developed with a pandemic in mind. Put bluntly, arbitrarily placing a dollar value on a statistical life owing to Type 2 thinking in the absence of Type 4 evidence risks many more people dying than otherwise would have occurred. Acting under a Type 4 conception will have different outcomes than a Type 2 orientation, even as scientific knowledge continues to evolve and experts debate the most effective strategies. Given the dominance of Type 1, 2 and 3 conceptions in public policy thinking in most countries, it is imperative to recognize their profound implications for how governments adjudicate policy choices that will affect how many lives will be saved and lost.
Benjamin Cashore, Li Ka Shing Professor in Public Management, Lee Kuan Yew, School of Public Policy, National University of Singapore. (sppbwc@nus.edu.sg) Steven Bernstein, Professor, Department of Political Science and Co-director of the Environmental Governance Lab at the Munk School of Global Affairs and Public Policy, University of Toronto. (steven.bernstein@utoronto.ca)
ACKNOWLEDGEMENTS: We thank for their comments on a previous version Danny Quah, Kanti Prasad Bajpai, Dan Hara, Alan Ernst ,Taha Hameduddin and Tim Gallagher
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