What Can Political Science Learn from Public Health? Reflections on Epidemiology and Methodology

This is part of our special feature, Public Health in Europe.

Three lessons for political science and sociology from public health and epidemiology

The value of observational research

In 1991, sociologist David Freedman introduced a generation of social science methodologists to John Snow (no, not the King in the North; the one of the Broad Street pump). Freedman argued that Snow’s pioneering research uncovering the means of transmission of the 1848-9 cholera epidemic in London was a model for social science research because Snow leveraged in-depth case knowledge and qualitative evidence to make sense of the observed spatial variation in cholera cases. “The force of the argument results,” he claimed, “from the clarity of the prior reasoning, the bringing together of many different lines of evidence, and the amount of shoe leather Snow was willing to use to get the data” (Freedman 1991, 298). However, more recent works in political science methodology (see e.g. Dunning 2008; Beck 2010) have taken a different lesson from Snow’s research, and from “modern scientific epidemiology” in general (Beck 2010, 501 emphasis in the original). To these latter-day methodologists, what makes the kind of work that Snow did valuable is its ability to make clean causal inferences about the source of an outcome (disease) by exploiting natural, medical, or policy experiments and analyzing the results quantitatively. 

Many epidemiologists and scholars of public health who rely mainly on observational data would surely be amused to find their work portrayed as adhering to this inferential “gold standard.” However, the question for political science—a discipline polarized by methodological battles—is not what epidemiologists actually do, but rather, in the words of Beck (Beck 2010, 500), “Who gets to claim John Snow?” Put another way: what lesson will social scientists take from public health and epidemiology? That clean causal inference from experimental (or at least quasi-experimental) data is the holy grail for social science; or that deep contextual knowledge, generated by expenditure of shoe leather, is necessary for advancing scientific understanding of social causation? In public health and epidemiology, scientific progress has relied on a combination of shoe leather, observational, and experimental research. The lesson for political science seems obvious: not “either/or” but “both, and.”

The importance of understanding mechanisms

The struggle over John Snow in political science is not only about the value of observational versus experimentally-generated data, but is also linked to a broader debate concerning the relative importance of estimating causal effects versus identifying the mechanisms that connect causes and effects (see e.g. Falleti and Lynch 2009; Gerring 2010; Imai et al. 2011). While many in political science find that causal explanations are unsatisfying without understanding of the mechanisms the produce effects, the rationalist and individualist microfoundations underlying much of modern political science have nevertheless delayed research into many mechanisms other than utility maximization that might underlie causation. Here again, public health and epidemiology may have important lessons to offer.

For example, for political scientists, it is axiomatic that political and economic power affect politics and political outcomes, but we rarely ask precisely about how power “gets under the skin” of politics in the same way that public health scholars ask how socioeconomic status “gets under the skin” to produce health or illness. Some of the most striking regularities in the field of political behavior—for example, the observation that people with higher levels of education tend to vote at higher rates than those with less education—are accepted as self-evident without much investigation of why. Public health scholars have begun to go beyond documenting that health status is correlated with socioeconomic status, and have developed a set of theories regarding the mechanisms that link the two. Political scientists need to start doing the same for politics.

Similarly, political scientists, like epidemiologists, are interested in things like conflict, policy models, and participation in politics that have a tendency to spread. These topics are of interest to many political scientists in part because they spread. But most research remains focused on documenting the phenomenon of spreading: The literature on policy diffusion, for example, consists of hundreds of books and articles documenting the spread of policy ideas across jurisdictions, but a much smaller number that investigate empirically the vectors or mechanisms of diffusion (notable examples of the latter include Shipan and Volden 2008; Weyland 2005). Diffusion and other kinds of movement through networks are processes that are central to political life. If we want to understand how and why they happen, we would do well to examine the central transmission mechanisms that epidemiologists and public health scholars have identified, and begin to generate ideas about what their political analogs more fully.

Updating our thinking about causation

Greater attention to mechanisms of action and diffusion is not the only way in which political science’s approach to causation could benefit from greater attention to public health. Despite some advances in some sub-subfields of political science (e.g. historical institutionalist comparative politics and American political development), political scientists tend to prefer monocausal, parsimonious explanations that occur closely coupled in time. Much of political science remains, in other words, wedded to eighteenth-century models of causation (for an excellent discussion see Kurki 2008, 108:Introduction). Public health and epidemiology offer at least two useful alternative models for thinking about causation that have so far received little attention in political science. 

One is the idea of etiologic period—the length of time required for a cause of a later health state to create its effect. Epidemiologists recognize that the etiologic period can vary substantially, depending on the nature of the cause and the outcome. Peter Hall (2003) and Paul Pierson (2011) both argue that many phenomena that are of tremendous political import simply cannot be explained through parsimonious, variable-centered causal models focused on the court durée. But if we were, as a discipline, to consider only the moyenne or longue durée, we would be no better off. Thinking in terms of etiologic period is a more promising approach. As Jason Beckfield (2018, 21) points out, “the concept of etiologic periods problematizes the length of time required by the body politic to translate coalitional cause into institutional effect” and is hence helpful for understanding how complex processes of institutional change, for example, are comparable even when the ultimate outputs of these processes may take either very little or quite a long time to come about. 

A second useful model of causation that has not been applied in political science is that of “fundamental causation” (Link and Phelan 1995). Link and Phelan argue that the unequal distribution of power and resources in society is so tightly interconnected with health, and through so many different mechanisms, that even if one causal pathway is interrupted (for example, when a health-promoting technology such as sanitation becomes widely available to all rather than reserved for the wealthy) the fundamental cause will act through a different mechanism to create a similar outcome (e.g. substituting socioeconomic inequalities in deaths from delayed cancer screenings for socioeconomic inequalities in deaths from cholera). Fundamental causation can occur only when both the cause and the effect are “multiply realizable” (Lutfey and Freese 2005; Ward 2007)—that is, when both cause and effect are complex phenomena (like “socioeconomic inequality” and “health”) that have multiple internal dimensions that may be operationalized and measured in different ways. As Gary Goertz (2012) notes, many (if not most) of the concepts that we use in political science ought to be thought of as having this structure. Given this, the idea of fundamental causation could be a useful tool in the arsenal of political scientists seeking more adequate explanations for complex social phenomena.    

Two lessons for public health and epidemiology from political science

Institutions matter

The actors and the structures with which epidemiologists and public health scholars are most intimately familiar—patients, communities, health and social care providers, health ministries, health policies and health systems, health ministries—are multi-faceted, complex, and prone to behaving in ways that are not always well-predicted by either scholarly theories or norms of governance. Very few researchers would make the error of assuming that all health ministries will behave in the same way when confronted with an infectious disease epidemic. However, public health and social epidemiology scholars sometimes forget that the same is true when they branch out into less familiar terrain. Insights from historical institutionalism could help public health scholars better understand how political entities affect health by highlighting the ways in which institutional structures can affect their preferences and behaviors. 

First, the internal structure and coalitions underlying complex political entities can result in the same “kind” of entity behaving differently or having different effects. For example, political parties bearing the same label may have quite different goals and methods, and welfare states from the same “world” of welfare (Esping-Andersen 1990) may generate quite different outcomes for different groups in society. This implies that key findings in public health about the effect of party type or welfare regime type on health outcomes that the party in government or the welfare regime type in a country are correlated with health outcomes should be interpreted with great caution, especially if the results are generating primarily using aggregate-level cross-national statistical comparisons that are unable to account for the internal dynamics of these organizations (see e.g. Navarro et al. 2003; Mackenbach 2014). Katherine Smith’s work examining how the structure of health policy-making institutions shapes the take-up into policy of ideas about health equity is an example of how public health scholarship can use insights about the structure of institutions to generate more useful understanding about their effects on health policy and on health (Smith 2013a).

A failure to understand the internal institutional structure of entities is related to a second difficulty with some work in public health: it treats entities like “social democracy” or “neoliberalism” as unitary, natural types when they are actually aggregates. Figuring out why these aggregates are correlated with health requires unpacking them to understand the coalitions and compromises that created them, and the multiple actors and structures that comprise them. Moreover, a core insight of historical institutionalism is that characteristics of institutions do not only affect the way that those institutions work, but can also shape the preferences and behavior of otherwise similar individuals whose lives are touched by those institutions.  nstitutions matter for politics because they aggregate and shape interests in different ways. Again, health scholars know this. Public health interventions are often aimed at changing the characteristics of families, neighborhoods, and communities because we know that these institutions shape the health behaviors of the people who live in them. But the shape of institutions also matters for the politics of health. For example, Isabel Perera’s work shows that the internal structure of unions representing public and private sector health and social care workers has a profound effect on the process of deinstitutionalization of mental health care (Perera 2018).

Ideas and ideologies work in mysterious but still analyzable ways

Public health scholars and epidemiologists have noted that processes denoted by abstract ideas like stigma, habitus, or relative deprivation might affect health, and at this point the disciplines have articulated a set of mechanisms that operate at levels from the cellular to the societal to explain these links. Still missing from many of these accounts, however, is a strong statement of how we ought to understand the etiologic role of ideas and ideology as distinct from resources and power relations. Katherine Smith’s work again provides a notable exception (see e.g. Smith et al. 2010; Smith 2013b); but even much of the finest work on the impact of political ideologies (e.g. social democracy or neoliberalism) on health could benefit from more careful thought about how ideas attain motive force in society. Political science is not far ahead in this regard, but recent interventions—for example the articles collected in the excellent special issue on ideas in public policy in the Journal of European Public Policy (2016, 23:3)—provide guidelines that might be useful.

My forthcoming book, Regimes of Inequality: The Political Economy of Health and Wealth provides an example of how a rather subtle change in ideas—a reframing of the problem of inequality from the maldistribution of material wealth to a problem of unequal health—changed the capacity of governments to act in ways that would improve population health and reduce inequalities (Lynch 2020). The key mechanism linking ideas to health in this case was a shift in the Overton window around inequality that made it harder for politicians and policy-makers to act on the immediate drivers of health inequality, and instead focused attention on a range of policy solutions that were complex, difficult to implement, and that proved uniformly disappointing. Identifying other mechanisms that link ideas, ideologies, and health could provide both political science and health-focused fields with more tools for understanding the relationship between politics and health. It would also open up more opportunities for collaboration between political scientists and scholars of public health and epidemiology.

Julia Lynch


Beck, Nathaniel. 2010. “Causal Process ‘Observation’: Oxymoron or (Fine) Old Wine.” Political Analysis 18 (4): 499–505.

Beckfield, Jason. 2018. Political Sociology and the People’s Health. Oxford University Press.

Cammett, Melani, Julia Lynch, and Gavril Bilev. 2015. “The Influence of Private Health Care Financing on Citizen Trust in Government.” Perspectives on Politics 13 (4): 938–57. https://doi.org/10.1017/S1537592715002248.

Dunning, Thad. 2008. “Improving Causal Inference: Strengths and Limitations of Natural Experiments.” Political Research Quarterly 61 (2): 282–293.

Esping-Andersen, Gøsta. 1990. The Three Worlds of Welfare Capitalism. Princeton, NJ: Princeton University Press.

Falleti, Tulia G., and Julia F. Lynch. 2009. “Context and Causal Mechanisms in Political Analysis.” Comparative Political Studies 42 (9): 1143–1166.

Freedman, David A. 1991. “Statistical Models and Shoe Leather.” Sociological Methodology 21: 291–313. https://doi.org/10.2307/270939.

Gerring, John. 2010. “Causal Mechanisms: Yes, But….” Comparative Political Studies 43 (11): 1499–1526.

Goertz, Gary. 2012. Social Science Concepts: A User’s Guide. Princeton University Press.

Hall, Peter A. 2003. “Aligning Ontology and Methodology in Comparative Research.” Comparative Historical Analysis in the Social Sciences 374.

Imai, Kosuke, Luke Keele, Dustin Tingley, and Teppei Yamamoto. 2011. “Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies.” American Political Science Review 105 (4): 765–789.

Kurki, Milja. 2008. Causation in International Relations: Reclaiming Causal Analysis. Vol. 108. New York: Cambridge University Press.

Link, Bruce, and Jo Phelan. 1995. “Social Conditions As Fundamental Causes of Disease.” Journal of Health and Social Behavior 35: 80–94.

Lutfey, Karen, and Jeremy Freese. 2005. “Toward Some Fundamentals of Fundamental Causality: Socioeconomic Status and Health in the Routine Clinic Visit for Diabetes.” American Journal of Sociology 110 (5): 1326–72. https://doi.org/10.1086/428914.

Lynch, Julia F. 2020. Regimes of Inequality: The Political Economy of Health and Wealth. New York: Cambridge University Press.

Mackenbach, J. P. 2014. “Political Determinants of Health.” The European Journal of Public Health 24 (1): 2–2. https://doi.org/10.1093/eurpub/ckt183.

Navarro, Vicente, Carme Borrell, Joan Benach, Carles Muntaner, Agueda Quiroga, Maica Rodríguez-Sanz, Nuria Vergés, Jordi Gumá, and M. Isabel Pasarin. 2003. “The Importance of the Political and the Social in Explaining Mortality Differentials among the Countries of the OECD, 1950–1998.” International Journal of Health Services 33 (3): 419–494.

Perera, Isabel M. 2018. “States of Mind: A Comparative and Historical Study on the Political Economy of Mental Health.” PhD thesis, Philadelphia, PA: University of Pennsylvania. https://repository.upenn.edu/dissertations/AAI10978250.

Pierson, Paul. 2011. Politics in Time: History, Institutions, and Social Analysis. Princeton University Press.

Shipan, Charles R., and Craig Volden. 2008. “The Mechanisms of Policy Diffusion.” American Journal of Political Science 52 (4): 840–57. https://doi.org/10.1111/j.1540-5907.2008.00346.x.

Smith, Katherine E. 2013a. Beyond Evidence-Based Policy in Public Health. London: Palgrave Macmillan.

———. 2013b. “Institutional Filters: The Translation and Re-Circulation of Ideas about Health Inequalities within Policy.” Policy and Politics 41 (1): 81–100.

Smith, Katherine E., Gary Fooks, Jeff Collin, Heide Weishaar, Sema Mandal, and Anna B. Gilmore. 2010. “‘Working the System’—British American Tobacco’s Influence on the European Union Treaty and Its Implications for Policy: An Analysis of Internal Tobacco Industry Documents.” PLoS Medicine 7 (1): e1000202.

Ward, Andrew. 2007. “The Social Epidemiologic Concept of Fundamental Cause.” Theoretical Medicine and Bioethics 28 (6): 465–85. https://doi.org/10.1007/s11017-007-9053-x.

Weyland, Kurt. 2005. “Theories of Policy Diffusion Lessons from Latin American Pension Reform.” World Politics 57 (2): 262–95. https://doi.org/10.1353/wp.2005.0019.

Photo: Pathogenic viruses causing infection in host organism, Viral disease outbreak | Shutterstock

Published on June 11, 2019


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