Keywords

1 Prologue: Fermentation and Science

Early in the bleak month of July 2020, a team of researchers lightened the mood when they published “Association between consumption of fermented vegetables and Coronavirus 2019 (COVID-19) mortality at a country level in Europe” (Fonseca et al., 2020). The manuscript, a preprint, claimed to find that fermented food consumption predicted lower COVID-19 mortality.

There was much to criticize about this article. Even the title is wrong, given that its independent variables included fermented dairy as well as vegetable products. Country-level analysis obscured within-country heterogeneity. Its dependent variable was endogenous to the political system since COVID-19 mortality data is a function of testing availability and reporting policies. Its sparse controls entirely excluded politics and policy (there were stringent lockdowns in a number of central and eastern European countries with high consumption of fermented foods, but once those countries eased their non-pharmaceutical interventions, their second wave mortality in autumn was horrific) (Löblovà et al., 2021). Fermented food never gained much attention as an explanation for COVID-19 mortality, though the authors at least got their journal publication (Bousquet et al., 2021).

The reason to discuss this paper, one small flake in a blizzard of COVID-19 preprints, is that it is a memorable caution. It reminds us all just how wrong research can go when it crosses into new areas, and thereby gives us all a teachable moment: how can researchers avoid the kinds of traps that the fermented food researchers fell into? (de Leeuw, 2009) The outlandish hypothesis might seem easy enough to avoid, but before we dismiss it, consider the amount of political science scholarship on COVID-19 that pays too little attention to the fact that COVID-19 data are endogenous to the political outcomes they putatively measure. Before dismissing its lack of policy variables, consider the amount of public health scholarship that simply neglects well-established political variables, including social policy measures and elite cueing, in explanations of COVID-19 outcomes. And consider the risk that in something as complex as the pandemic, it could be possible that a powerful explanation of mortality might be an immunological pattern entirely outside the scope of social sciences (e.g., [Pretti et al., 2020], the plausibility of which I cannot judge, argues that the distribution of certain characteristics of immune systems explains differential mortality).

2 Introduction

The global pandemic that began in 2020 promised to teach us many things. One of the things it can help to teach us is about ways to do political science with public health. Put another way, how can we avoid political and public health equivalents of the fermented food hypothesis?

A political science with public health can work best if informed by a broad social-scientific understanding of both fields. This chapter, therefore, takes its inspiration from not just political science but also sociology and Science and Technology Studies, a field which focuses on the social construction of facts and their flow through society (a good introduction to the field can be found in [Vinck, 2010]). In particular, focusing on the small-p politics of knowledge and scientific enterprise complements political scientists’ preferred focus of the big-p politics of institutions, parties, and voters.

The chapter focuses on three issues that seem to be particular causes of disciplinary misunderstanding and potentially fruitful research. The first is the professional authority of public health, including the extent to which it has a clear domain of expertise that others in government and academia respect. How do we understand the political process by which public health policymakers or scholars try to establish an identified area of expertise which they dominate and which generalist policymakers respect? The second is the politics of data. Many political scientists discussing COVID-19 showed their poor preparation in epidemiology, which was not surprising or objectionable in itself. What was surprising was how frequently they failed to recognize that data are endogenous to the political process because the collection and coding of data of any kind are political decisions. The pandemic showed the potential value of viewing statistics as a dependent variable of the political process. Political scientists have given the politics of health data very little attention but could shed light on the topic by treating data as indicators of politics as well as whatever they are supposed to represent. The third is of the most contested concepts that can be found at the border of public health and political science: political will. “Political will” can seem to political scientists like a simple call for voluntarism without reference to incentives and constraints, but it might be that we can synthesize the practical public health search for a champion or advocate with the extensive political science research on the ways institutions locate and shape agency.

The chapter draws on our recent work on COVID-19 politics, in particular; that work is informed by a longer history of research on the politics of public health and communicable disease control (Greer, 2017a; Greer & Jarman, 2020; Greer & Kurzer, 2013; Greer & Mätzke, 2012) as well as new comparative research on the politics of the pandemic (Greer, Jarman, et al., 2020; Greer, King, et al., 2020; Greer et al., 2021).

3 The Political Status of the Public Health Profession: On Top or on Tap?

Political science literature, to the limited extent that it engages with professionals, professionalism, and organized professions, tends to focus only on their operation as interest groups. But professionalism is one of the key tools used in modern society to “depoliticize” an area by taking it out of partisan politics, and thereby more fully institutionalizing it in some different arena of politics with its own distinctive behavior and sets of actors.

We can view professions, for the purposes of understanding public health politics, as groups of people engaged in an effort to institutionalize a domain of action and expertise as theirs to define. This domain is intellectual as well as practical and can also be certified by law, so while it is possible for non-lawyers to appear in court in many countries, the intellectual and social dominance of lawyers means such people will probably fare poorly, and it is normally illegal in most jurisdictions for non-surgeons to perform surgery.

Since the political science literature on professions in politics is so sparse, it is reasonable to borrow from the much better entrenched field of the sociology of the professions. Viewing public health as a profession, using literature from the sociology of the professions, might help us to understand some of the much-lamented challenges faced in improving the connection between political and public health thought.

It is axiomatic in sociological studies of the professions that they—and their individual members—tend to fall into hierarchical relationships. Equality between professions that have much to do with each other is rare and produces friction; law and medicine might be a good example. Professions and professionals’ typical relationship is summarized by the phrase “on top or on tap.”Footnote 1 On top means that the members of that profession decide what kind of situation they are in and what action and expertise is needed. On tap means that they are available to help. A doctor orders a test, a treatment, and a prescription; the technician does the test, the nurse does the treatment, and the pharmacist delivers the prescription. The doctor is on top and the others on tap. Being on top is about having the right to define the nature of the situation and the allocation of skills. This tendency to seek hierarchy, born of an entirely natural professional perspective and socialization, means that interprofessional work on a basis of equality is famously difficult (e.g., [Bridges et al., 2011]).

Andrew Abbott created a sophisticated and more formal version of this insight in his System of Professions (Abbott, 1994). In his model, professions are not so much characterized by formal institutions (education, certification, self-government) as by their ability to sustain a claim to expertise over a given domain of activity. Sustaining a claim requires a system of abstract thought, since abstraction is what allows professions and professionals to adapt and maintain their claim to expertise even as problems, context, and technology change. Over time they can expand the domain of their members, whether through entrenching professional activities in law, advising government, or incorporating fields of research previously occupied by others. They can also acquire dominance over policy areas not strictly related to their expertise. One salient example is the justifiably contested extent to which pregnancy and childbirth is a suitable area for medicalization (Wagner, 1997). Another is the way medical associations in many countries have leveraged their public credibility and professional power into influence over topics like payment systems that do not, strictly speaking, require a medical degree to understand (for two excellent US studies with general applicability[Laugesen, 2016; Patashnik et al., 2020]).

Professions and specialties or disciplines within them are constantly engaged in border wars, such as economists’ regular invasions of the domains of other social sciences. Border conflicts are thus endemic to the system of professions and between specialists within a profession (e.g., between medical specialists) (Rozier et al., 2020; Zetka, 2003). Successful professions (and specialties within them, e.g., medical specialties or academic disciplines) nonetheless have a core domain within which they are largely untouchable, with efforts to occupy that domain not ratified by legal, scholarly, or bureaucratic actors. Political scientists and economists both write about all sorts of topics, but in areas such as electoral behavior and political institutions, political scientists dominate while economists dominate macroeconomic discussions.

Some professions—which Glazer called the “minor professions”—are structurally subordinate (as with pharmacy or nursing) and frequently feminized, while leaders and practitioners of others, such as public health or education, are constantly engaged in disputes about the nature and scope of their professional authority (Glazer, 1974). The status of profession tails off into occupations, but it is noteworthy how many and how often organized occupations try to stake out a professional domain. Studies of all sorts of occupations regularly note their efforts to establish both the formal accoutrements of a profession (licensing, postgraduate degrees, accreditation) and a claim to both a domain of expertise and an abstract body of knowledge.

Framing public health as a profession—and political science as a field within an established profession, academia—helps to highlight some of the barriers to collaboration and thereby points out possible routes. In intellectual and academic terms, public health is an interdisciplinary enterprise. While epidemiology is largely native to public health, other fields found in public health schools, from economics to toxicology to medicine, are simultaneously institutionalized elsewhere. As Glazer notes, and Rojas neatly demonstrated decades later, leading scholars of the minor fields will frequently have their terminal degrees in some more prestigious field and frequently publish there (Glazer, 1974; Rojas, 2010). To some extent this is a useful division of labor. Higher-status disciplinary researchers such as political scientists develop theoretical and empirical tools for understanding politics, while researchers in public health develop tools for making and implementing public health policies. But in a system of hierarchical professions, the result is a fault line through public health education. The status and intellectual drive points to doing political science of public health even if the whole point of a School of Public Health, its students, and its funding is probably to do political science in public health. The resulting tensions are part of everyday life for people who work anywhere near the nexus of political science, or any social science, and public health. We can, however, give thanks that the weakly disciplinary nature of public health admits social scientists. Political scientists or any other non-medical field can have a much harder time in medical schools, where they are inevitably very subordinate (political science in medicine).

In formal and legal terms public health’s professional closure varies around the world but is usually low. In the UK, for example, at the core of public health is a medical subspecialty, one that is not especially well regarded, but a large part of the public health workforce, including people at the relatively significant level of Directors of Public Health, does not have medical training. Arguments about whether public health’s professional bodies should specify a particular kind of training are a long-standing and tiresome feature of England’s public health history. France has a similar story: the elite of the public health workforce are medical doctors, but public health doctors are so few as to leave much of the system staffed by non-doctors. In the US public health is not a medical field; a doctor can pursue a Master’s in Public Health (MPH) but that is no different from a doctor who pursues a degree in public policy or history. Lack of professional closure means that an MPH does not provide access to any particular kind of job or power in the way that a social work, law, or medical degree does. Most of the US public health workforce does not have any formal public health training, let alone an MPH (Leider et al., 2020).

The upshot is that public health has a very small domain and a huge area of ambition. Activities that were bundled with public health at the turn of the twentieth century, meanwhile, have often moved off into other professional domains such as social work, and low-status ones such as restaurant inspection, water quality inspection, and health education have in various places been cut away from formal public health agencies with no apparent loss to the status of public health. For example, in the UK, social work split off from the responsibilities of Medical Officers of Health and “environmental health” took over sanitarian work in local government in 1974 with no apparent damage to food safety or even the prestige of its academic public health. What we might, following Patrick Fafard, call the “public administration of public health” and its relationships to other areas of public health such as policymaking and academia merits more, comparative and historical as well as contemporary, research.

The synthesis that has been most widely proposed worldwide in recent years focuses on establishment of a central public health agency which can advise policymakers and selectively reinforce other parts of government (there is even an association to promote such “Public Health Institutes,” headquartered in Atlanta and supported by the Bill & Melinda Gates Foundation). This internationally advocated model, which has echoes in many traditions, is of an elite set of disease detectives trained in some combination of microbiology and epidemiology whose expertise is the control of communicable and perhaps the prevention of noncommunicable diseases (Binder et al., 2008; Frieden & Koplan, 2010; Myhre et al., 2020). A public health institute is loosely modeled on the US CDC and in country after country has “CDC” in its initials. It is a small body of highly trained people who can strengthen capacity (design surveillance systems), advise government, communicate, and do both science and field epidemiology when there is a crisis. It is akin to a fire department for public health—even if actually addressing a pandemic turns out to require something more like a bucket brigade, as Mätzke points out (Mätzke, 2012), with groups from police to doctors to the army involved in often improvised responses.

The problem for the professional and institutional project of public health is that the core of its domain since its modern foundation early in the twentieth century is the control of communicable diseases through non-pharmaceutical interventions such as masking or closures, and to some extent vaccination (Markel et al., 2007). Yet in a paradigmatic communicable disease outbreak that required NPIs, COVID-19, the striking thing we found in our cross-national study of 34 countries was the weakness of any claimed intellectual or formal monopoly of public health decision-making (Greer et al., 2021). Perhaps the fates of Public Health England (whose reorganization was brusquely announced in August 2020) or the US CDC (humbled by Donald Trumps’ political appointees and blamed for confusing guidance under Joseph Biden) are especially humiliating. In country after country, though, the formal public health apparatus turned out to have nothing approaching dominance of science and public advice on communicable disease control. Top scientific or medical advisors were frequently prominent, but it seems that in most cases they were not formally trained or employed in public health and were far from being seen to dominate the definition of relevant knowledge.

It is easier to mention the exceptions to this broad pattern of sidelining. In a few counties, such as South Korea (Park 2021) and Colombia (Acosta et al., 2021), politicians made a very clear decision to gain authority and credibility precisely by standing behind their communicable disease control agency leaders. In Sweden, politicians respected the deeply entrenched autonomy of that country’s agencies, in this case the state public health agency, and found themselves on an internationally unusual and much-debated course that might explain why Sweden had substantially higher excess mortality than its neighbours (Baldwin, 2021; Irwin, 2020). That was close to the whole list, though some subnational leaders did the same (e.g., British Columbia and Nova Scotia). In most countries, heads of government initially centralized power unto themselves, convening ad hoc committees for advice (Greer, et al., 2022; Jarman, et al., 2020; Greer, King, et al., 2020). In most places public health officials and researchers did not enjoy any kind of specialist monopoly or even dominance of a domain in the eyes of practitioners of other disciplines or heads of government, and were relegated to part of the answer and solution. Intellectually, legally, and organizationally, public health was sidelined by top politicians when they sought advice, frequently replaced by a mixture of more prestigious medical and scientific experts and administrative figures (Rozenblum, 2021).

We might expect this. Fox divides government into generalists and specialists (Fox, 2017). Generalists are the politicians, especially heads of government and executives, and their core staff, who typically cluster around the head of government and perhaps the finance ministry. They specialize in running the country—and in staying in office by winning elections. Good senior staff will usually support politicians in making policies that win elections. This means allocating time, energy, and money between priorities. Everybody else is a specialist, whether they work in public health or any other field. Establishing professional dominance over government activity is hard because it requires that generalist government cede its core power, which is the power to decide priorities between specialists. An independent central bank is a perfect example of a high level of formal autonomy for specialists (Adolph, 2013); the military is often an interesting case because of high esteem for its leaders and expertise combined with an urgent constitutional case for civilian, generalist, oversight of its activities. Professionalism is a way to buttress a claim to a putatively depoliticized area of domination—a claim that the profession, added to institutional frameworks, will produce consistent enough policy to justify a loss of generalist power and a displacement of politics into a distinctive professional realm. (Adolph shows that central bank appointments are highly political, but the politics look different because of the autonomy of central banking.) Put another way, it is a claim that the professions will do a good enough and predictable enough job to merit autonomy. It turns out that public health agencies did not manage to establish enough of a domain of professional expertise to persuade generalists to let them lead or even dominate advice and communications in most countries.

For developing a political science with public health, the suggestion is that we need a research agenda on how and why public health took the intellectual, professional, legal, and bureaucratic form it took in different countries—a comparative politics of public health (for an effort in the EU context, see [Greer & Jarman, 2020]). That would give us a sense of the value and likely outcome of, for example, the “health security” movement or the Gates-led push for Public Health Institutes, and a better understanding of the interplay of generalist government, public health researchers and practitioners, and other professions such as medicine, and thereby show what might work to strengthen public health as an actor or policy goal.

4 The Politics of Data

One of the most striking things about the interface between political science and public health in the 2020 pandemic was the extent to which it revealed the limits of empirical political science scholarship. Basic epidemiological data turned out to be not just new to political scientists but difficult to understand.

For example, test positivity should be easy to understand in the terms of political science: it is an indicator of a sampling problem. Test positivity reports the number of tests administered and reported that are positive. If it is above three or five percent, then it is likely that the test data is unreliable because testing is conditional on something else, such as a likely diagnosis. That might make the tests useful in clinical settings, but it means that the testing is not useful as a random sample that would give us population-level information. Test positivity was data about the test, not about the virus (Trump et al., 2020).

For a more serious problem, efforts to compare country outcomes were often hampered by using COVID-19 test data, whether it was case numbers, COVID-19 attributed mortality, or something similar. The problem is that data are endogenous to politics. Testing and surveillance systems of any kind are expensive, require resources and infrastructure, and can influence public behavior and political debate (Greer, 2017a). Not only do they require complex bureaucracies and data management systems, but they can also tread on the autonomy of individual doctors by inserting a public health rule on issues such as determining cause of death (e.g., if a patient with COVID-19 dies of a heart attack, attributing the death involves a decision that doctors might regard as part of their clinical decision space). Home testing gives individuals autonomy over data reporting and many public health systems might not even ask the public about at-home test results. The decisions to test, to gather data, and to report it are all political and therefore are dependent variables in themselves. Donald Trump certainly knew that.Footnote 2 Political scientists trying to understand COVID-19 ought to know it as well.

Thus, COVID-19 data for the United States for most of the pandemic were unreliable, as we can see from test positivity that was often above 5% and frequently in the double digits. At-home testing, a very useful tool for managing risk, also reduced the usefulness of case counts in any jurisdiction where they were common. As a result, the scale and patterns of the US outbreak were at best hazily understood. Meanwhile, there was no consistent rule in most states, let alone the country, for attribution of deaths (Rocco et al., 2021). It would therefore be hazardous, for example, to use COVID-19 infections or COVID-19 attributed deaths as dependent variables for studies of policy effects or behavior.Footnote 3 Instead, the behavior of governments, statistical agencies, health care organizations, and individual doctors signing death certificates is the right dependent variable. Data from testing are a clue for that study, not an indicator of government success or failure. The question should be why the United States’ public health surveillance system, and its broader public health system, collapsed so dramatically, not what unreliable testing data says about the difference between two places in August or October. The further question might be: why didn’t more countries invest in better surveillance and data presentation during the pandemic?

The logical extension is that COVID-19 data are no exception to what we might call Trench’s Law, coined by Alan Trench in the context of comparative federalism: data are useful or comparable but not both (Greer, 2019). As a look at any existing data project, or a scan of the Science and Technology Literature will show, data are a political project and outcome. Data are expensive to gather, organize, and maintain. They require not just resources and money, but also a variety of forms of compliance, as simple as people agreeing to response to surveys or as complex as agreeing to code complex clinical procedures, lab findings, and patient outcomes. A national rule for coding deaths took discretion away from individual doctors, with costs and benefits in terms of data quality.

For a good outcome variable, instead, we can use excess mortality. Excess mortality is calculated by taking an average of mortality—the deaths on a given day or week over the last five or ten years—and comparing it to mortality on that day in 2020. The spike in mortality would likely be attributable to the pandemic. Excess mortality might understate COVID-19 deaths, in fact, because nonpharmaceutical interventions such as business closures might reduce other causes of death such as drunken driving and construction work. Mortality and natality data are among the statistics that states are most likely to collect consistently and competently because they are enormously useful for taxation, conscription, disbursements such as pensions or conditional cash transfers, and all manner of government databases from driving licenses to passport issuance. That many states do not reliably collect them is interesting, but they are more likely to be reliably collected than most other data.

Excess mortality data are not perfect. It is slow. In most countries a death report must travel up a long chain, from a doctor’s signature on a death certificate, through local government, figures such as coroners who might review deaths before reporting them, and then different levels of government that collect and collate death data. As a result, excess mortality is not widely reported in the popular media. It is a poor real-time guide to the progress of the pandemic or relevant policy. For a mixture of inevitable statistical and frustrating bureaucratic reasons, it will often lack detailed geographic or subgroup information. It also fails to reflect improving COVID-19 treatment and differential risks among infected people which meant that over the course of the pandemic the case fatality ratio and infection fatality ratios clearly changed. There is no fixed relationship between the number of people with the virus and the number of deaths. It is, however, probably the best statistic for political scientists to use in gauging the success or failure of pandemic response policies.

Beyond using excess mortality or other indicators to gauge the effects of government decisions, something that political scientists might wish to leave to epidemiologists, the problems with testing raise a series of important political science questions. Above all, what are the politics of surveillance? This is a topic on which remarkably little is known (Greer, 2017a). Why do governments collect the health data that they collect, what are the political forces for and against collection of such data, and how does data collection interact with practice? The effects of introducing electronic health records (EHRs), for example, are very well documented. They change practice in the service of managers and researchers who seek more information about clinical practice even if the results are unsatisfying to clinicians (Timmermans & Berg, 2003). An even better empirical issue is the collection, or non-collection, of information about racial and other disparities in COVID-19 infection and mortality. On one hand, the story of COVID-19 is in many ways a story of inequalities, but on the other hand it highlighted the politics of collecting data on inequality. The politics of racial data on every level are fraught. Not only do we have well-known cases such as what amounts to a ban on such data collection in France (Fredette, 2014), but on the individual level doctors’ decisions about when to mention race reflects deep and often racist structures (Balderston et al., 2021).

Data and metrics shape perceptions of reality and all kinds of practice by making some things tangible and apparently manipulable—“what’s measured is what’s managed,” as the dictum goes. In other words, what is measured is what is going to be managed. Once the measurement is good enough for managers, then it will be used even if, or because, it distorts reality and norms as perceived on the ground. This is why so many EHRs around the world are effectively billing systems that are hard to use for public health, research, or quality improvement. Those who can muster the monetary and organizational effort to impose EHRs are usually those interested above all in budgets. Likewise, part of the appeal of syndromic surveillance (such as testing wastewater for COVID or monitoring internet searches) is that it requires less bureaucratic investment because it draws on data that is easily collected (wastewater sampling) or already exists for another purpose (internet searches) (Fearnley, 2008a, 2008b; Ziemann, 2015).

Public health and medical researchers and leaders will often naturalize these data, partly through familiarity and partly because data shape theories and concepts (consider GDP, or unemployment, data full of value judgments, politics, and bureaucratic oddities which have nonetheless shaped the whole field of academic economics). It is also because of the determinedly apolitical style and culture of public health research. Pointing out the extent to which public health data is politically constructed is not part of the conventional public health style of apolitical expertise. For decades, historians and activists have documented and fought over surveillance (Fairchild, 2015; Fairchild & Bayer, 2015; Fairchild et al., 2007). The HIV pandemic, naturally, created enormous political contests about testing and privacy, with different jurisdictions creating very divergent testing and privacy regimes (Baldwin, 2005; Berridge, 1996). The public health literature nonetheless presents antiseptic and apolitical “good practice” as if surveillance systems were not in the middle of a hurricane of privacy, practice, legal, and coercive issues (Lee et al., 2010).

In short, a great many political scientists in 2020 and 2021 were floating empirical studies based on grievously flawed data. It might be frustrating that COVID-19 data are endogenous to politics—but we should really embrace that. Rather than competing with observational epidemiology to identify the effects of policies, it might be useful to look at how governments and others gathered and processed the data they had. The picture of the world that policymakers and researchers used throughout the pandemic was one shaped by expensive, flawed, and political data collection and management systems. The fact that so few countries meaningfully improved surveillance over a long pandemic is a political science puzzle. Data are a valuable object of political study in itself; rather than bemoaning data problems or pushing on regardless of data problems, we might study them. The data problem is the puzzle, and one that political scientists, with colleagues in sociology and STS, might explain.

Part of the contribution of political science with public health could be precisely in explaining why and how decisions about surveillance are inherently political. A political science with public health would share the overall goal of good surveillance data but would help model the proverbial hurricane of issues and tease out that issues and help identify which are real issues (e.g., privacy) and which are more in the order of pretexts for inaction or avoiding politically difficult issues (Patrick Fafard, personal communication, 2021).

5 Political Will and the Politics of Agency

“Political will” might be the phrase that most neatly marks the division between public health and political science researchers. To most public health researchers, it is crucial to making policy, and much of the practical education in politics that can be had in public health is geared toward finding and creating it. To most political scientists, it is wormwood. It seems to be a voluntaristic concept that ignores politicians’ incentives and actual ability to act.

One way to approach this debate is to point out that some of the problem is terminological. Is it really that contrary to political science findings to point out that policies are more likely to be adopted and implemented when they have entrepreneurs and politicians willing to promote them? To simply call for political will, outside of an analysis of what is possible and desirable from the perspective of working politicians, is indeed quixotic. But is that what is really happening when public health practitioners are being taught advocacy and policy skills? Is it really fair to imply that advocacy classes for public health practitioners aren’t discussing political incentives and constraints when they tutor students about ways to identify interested politicians and tailor the case to their situation? Kingdon’s multiple streams analysis might be taught too often and unreflectively, and with too much attention to the policy entrepreneurs, but it is still a good theory (Greer, 2015; Kingdon, 2003). There is good applied political science in public health, and concepts like political will might often just be teaching tools. The problem that arises with simplifying teaching tools, of course, is that they might persist in people’s heads—an analogy might be the simple and easily refutable models taught in introductory economics which no working economist would endorse but which pollute analysis of economies.

A more productive way to think about the problem might be in terms of the politics of agency. How is the ability to have political will distributed? Structurally, who has agency and how are they selected? Whose political will matter and why? This is a way to approach and synthesize an enormous volume of political science, especially the study of formal and informal institutions.

Thus, for example, presidentialism creates a distinctive politics of agency. A presidentialist system has, in Linz’s definition, “an executive with considerable constitutional powers—generally including full control of the composition of the cabinet and administration—is directly elected by the people for a fixed term and is independent of parliamentary votes of confidence. [The president] is not only the holder of executive power but also the symbolic head of state and can be removed between elections only by the drastic step of impeachment. In practice…presidential systems may be more or less dependent on the cooperation of the legislature; the balance between executive and legislative power in such systems can thus vary considerably.” Linz continued that “two things about presidential government stand out. The first is the president’s strong claim to democratic, even plebiscitarian, legitimacy; the second is [the president’s] fixed term in office” (Linz, 1990, pp. 52–53).

Linz’s interest was in democratic stability, and of all the thousands of publications his insight inspired, most are likewise about regime stability and transitions rather than public policy (though public policy and domestic politics researchers are quite aware of the impact of presidents on public policy, e.g., [Skowronek, 1982]). Subsequent scholarship has qualified Linz’s point by emphasizing the extent to which party systems and electoral rules change presidential powers, accountability, and incentives (Elgie, 2005; Mainwaring & Shugart, 1997). But Linz’s point has power for understanding who mattered in COVID-19 response. The analysis above suggests that presidents as diverse as Jair Bolsonaro, Emmanuel Macron, Joe Biden, and Donald Trump would wield tremendous power during the emergency of the pandemic. They would have concentrated agency with limited accountability and use it for better or for worse—whether to act, to not act, or to shift credit and blame.

Presidents in presidentialist systems have not been the only leaders whose leadership counted in the pandemic. We can rescue another hoary and much-debated concept: majoritarianism (Lijphart, 1984, 1999). Without endorsing all of Lijphart’s coding decisions and his particular construction of the index, we can define majoritarianism in politics as a high score on two axes: the ease with which a single party can take control of government; and its ability to act once it has. Thus, for example, presidentialist France is very majoritarian. Emmanuel Macron’s career demonstrates it. Consider the ease with which Macron could constitute a political party almost out of thin air, take the presidency and legislature a short time later, and make nearly unilateral decisions for the country. But other, especially Westminster political systems, are also highly majoritarian. A plurality of voters empowered Conservative governments to not just govern but take the UK out of the EU on very hard terms in Brexit. It is reasonable to argue that the Canadian prime minister is the most powerful executive in the west, constrained only by negotiations with provincial premiers who are equally dominant in their provinces.

Majoritarianism would mean, then, that agency lies in the central executive. The agency given to Boris Johnson, Scott Morrison, and Justin Trudeau meant that, like their presidential colleagues, their leadership and behavior were extremely important because they could be elected on a thin majority and make major changes.

This is not to say that majoritarian systems did better or worse in excess mortality during the crisis, though a number of the most flamboyantly questionable COVID-19 responses were majoritarian leaders—Jair Bolsonaro, Boris Johnson, Andrej Babiš, Narendra Modi, or Donald Trump. For each of them, there were in parallel (or “also”) strongly empowered leaders who did not become known worldwide for ineffective responses—Justin Trudeau and Scott Morrison were highly empowered individual leaders who did not make strikingly bad policy, while a number of consensus democracies such as Sweden produced strikingly high excess mortality.

Federalism also redistributes agency by creating powerful elected general governments with constitutional status. They can create coordination problems and veto points, as much literature laments, but they can also create resilience by creating a second line of governments which can supplant a negligent or destructive federal government (as happened during the pandemic in Brazil, India, and the United States).

For our purposes, it simply means that the leaders of state or regional governments matter. This can be further divided by following Elazar’s distinction between self-rule and shared rule in federalism (Elazar, 1987; Hooghe et al., 2010) (Greer et al., 2015). In federations with a high level of regional self-rule (autonomy), such as Brazil and the United States, they have spheres in which they can take their own actions, complicating and perhaps diversifying responses. High levels of shared rule, such as in Germany, create more consensual democracies since regional or state governments can shape the federal government’s action.

Leadership clearly mattered during the COVID-19 pandemic, but it did not matter consistently because leaders do not matter consistently. More consensual democracies, even Westminster -descended ones with coalitions (e.g., Ireland, New Zealand), have leaders subject to more constraints who must aggregate interests within complex coalitions. The importance of leadership is a dependent variable of formal and informal rules. Thus, the behavior of some leaders mattered more than others. The hazard of leadership literature, like the hazard of writing about political will, is that it concentrates on the leader (in many cases because the target audience is would-be leaders). Both can perhaps be recovered by examining the circumstances under which political will and leadership matter, thereby creating a possible middle ground between political science theories, which tend to infer action from structure, and leadership theories, which tend to pay too much attention to the leaders at the expense of their circumstances.

One of the more successful political concepts in public health is that of the “decision space,” which demarcates what governments can do in light of all their different constraints (Bossert, 1998; Greer, 2017b; Koivusalo, 2015). Its value is in its ability to synthesize political science findings into an immediately valuable concept that tells us what is possible, what the problems are, and what might be improved. The politics of agency might be a similarly useful concept. It is a tool for synthesizing vast amounts of political science, most of it developed for different purposes (e.g., understanding democratic stability and regime transitions) for identifying who can do what in different political systems and how that might change.

6 Conclusion

As the editors’ introduction to this volume made clear, political science and public health scholarship can stand in different relationships to each other, with more or less productive results. A failure to connect clearly impairs both (Carpenter, 2012; de Leeuw, 2016; Fafard & Cassola, 2020; Gagnon et al., 2017; Gore & Parker, 2019). Part of the solution can lie in greater use of insights from STS and sociology about the ways that small-p politics and the construction and contestation of knowledge work and shape the priors of people focused on the big-p politics political scientists study.

This chapter set out to use the COVID-19 pandemic experience to think about three issues that might help in developing a public health with political science: the nature of public health’s intellectual and professional status; the politics of public health data; and the nature of leadership and political will. In each case, the hope was to at least reduce misunderstanding, and to perhaps identify a productive research direction.

Public health, even among the “lesser professions,” has an unusually small core domain (much of it low status and variable from country to country, e.g., restaurant inspection or health care for the indigent) combined with a tendency to intellectual imperialism. A field with an often-narrow set of bureaucratic responsibilities and political role has an intellectual superstructure of great ambition. The core of its domain, furthermore, is communicable disease control. In the pandemic, generalist policymakers showed little respect for public health claims to a monopoly in even that domain. In country after country, they sidelined or subordinated public health agencies and researchers, listening instead to ad hoc groups which often had limited public health representation.

Data preoccupy both political science and public health researchers, but this often means a focus on trying to work with imperfect data or bemoaning imperfections in available data. I suggest that what we need is research in political science, with public health, on the politics of data. Analyses of how data are generated and used have done much to illuminate the politics of different policy areas. Understanding the politics of data and surveillance might improve data as well as our understanding of politics and public administration.

Finally, political analysis within public health has a tendency that political scientists find frustrating to urge political will, as if finding a legislative champion is all one needs. I argue that a search for a champion, a leader, or for that matter a policy entrepreneur is a very rational advocacy strategy. Further, the COVID-19 pandemic reminds us that leadership matters in a way that sits badly with political science’s structuralist tendencies. Much political science, particularly institutionalist research, can be read as study of the allocation of agency. Rather than thinking that political will or leadership is a property of the person, we might better think of it as a use of agency, which is unevenly distributed within and between political systems, and regard the distribution of agency as part of the explanation of when leadership mattered and what happened during the pandemic.

I opened this chapter with reference to a particularly unfortunate piece of health research. It is a cautionary tale; in that it reminds us just how badly wrong research can go. The risk of interdisciplinary inquiry is that political scientists and public health researchers will, through lack of knowledge of each other’s achievements, do something similar—reinvent the wheel, at best, or end up with the intellectual equivalent of fermented foods. The hope is that we can avoid these problems by not just good scholarship and exchange, but by attention to the conditions under which the different disciplines operate and interact.