American Journal of Epidemiology Advance Access originally published online on October 12, 2007
American Journal of Epidemiology 2007 166(11):1242-1243; doi:10.1093/aje/kwm285
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Morabia Responds to "The Context and Challenge of von Pettenkofer's Contributions to Epidemiology"
From the Center for the Biology of Natural Systems, Queens College, City University of New York, Flushing, NY
Correspondence to Dr. Alfredo Morabia, Center for the Biology of Natural Systems, Queens College, City University of New York, Flushing, NY 11365 (e-mail: alfredo.morabia{at}qc.cuny.edu).
Received for publication August 16, 2007. Accepted for publication August 30, 2007.
In their invited commentary, Oppenheimer and Susser (1) have exquisitely synthesized the issues at stake. They abundantly cite Evans's book (2), which should belong in every epidemiology curriculum (3). In their last paragraph, Oppenheimer and Susser mention a possible disagreement with me for not having specified that, in von Pettenkofer's view, interactions could have taken place at both the individual and the societal levels. It was definitely not my intention to, as McMichael (4) would put it, "imprison" von Pettenkofer's ideas in the proximate, individual level. My paper (5), however, may express more skepticism than that by Oppenheimer and Susser (1) about the extent to which epidemiologic methods can deal with interactions. I believe that attempting to account for too many potential interactions is incompatible with epidemiology. To understand why, let us zoom out from the Koch-von Pettenkofer debate and consider it within a wider historical context of causal thinking about epidemic diseases.
The word "interaction" is big in science but trivial in everyday language. In epidemiology, statistics, or system theory, it describes situations of effect amplification (e.g., synergy), contraction (e.g., antagonism) or, more generally, departure from simple combinations of elementary properties of causes. In common language, to interact simply means "to act together" and includes interacting and noninteracting (in the scientific sense of the word) instances. The word is trivial because human intelligence perceives interactions as ubiquitous. On the topic of health, for example, early (traditional) medical theories are replete with interactions.
Consider the medical systems of antiquity in ancient Egypt, India, China, and Greco-Roman Europe. With some variations, they were all based on theories linking human health to almost everything else in the universe. If we put aside the poetic feel of these holistic theories, we find that they were refined attempts to explain health and disease as the result of complex interactions. These approaches distinguished micro- and macrocosmic levels of organization and connected elements, planets, compass points, organs, climates, seasons, colors, tastes, body fluids, facial expressions, and so on by use of rich arrays of correspondence.
Interactions, however, are double-edged swords: They lump causes but split effects. There is a density of interactions at which each individual event appears to result from a unique set of causes. Let us refer to this as individualistic thinking. Considering each new case of plague as being determined by a specific set of causes is an obstacle when trying to understand the epidemic's origin. An individual event, as opposed to the probability of an event in a population, cannot be predicted with certainty and does not provide for comparative causal research.
In 1637, the French philosopher René Descartes (1596–1650) proposed a radically different treatment of interactions in science. The Cartesian method of knowledge acquisition comprised three rules: trust only "evidence," break up complex systems into simple parts, and ignore interactions (6, pp. 39–40). The approach was in essence reductionist, yet this reduction of complexity made epidemiology possible: A single determinant, isolated from a complex array of causes, could be responsible for many different individual events. Instead of multiple interacting causes that explained an individual event, there could now be one cause that explained a set of events for a multitude of individuals. The Cartesian step liberated probabilistic and population thinking. Group comparison and population thinking, that is, epidemiology (7), applied to simple causal models (e.g., contagious "cholera poison" being transmitted by water) generated more knowledge about epidemic diseases than centuries of holistic thinking had previously uncovered. All human societies that emerged from foraging economies, about 10,000 years ago, were recurrently hit and at times almost destroyed by epidemics of infectious diseases without being able to understand their causes. This situation began to change during the second half of the 19th century, as illustrated by John Snow's work on the mode of transmission of cholera. In the 20th century, identifying the effect of smoking on health must have been the first case of a society's discovering the emerging and modifiable cause of an epidemic and consciously acting to remove it.
Thus, ignoring interactions has advantages, but it also has limitations (1, 5). The historical role of von Pettenkofer was to start reintegrating complexity in a way that lent itself to epidemiologic research. The challenge for us is to progressively stretch our methods and concepts, as in life-course (8) or contextual epidemiology (9), so that interactions are soluble in epidemiology without epidemiology's dissolving in interactions. This is an exciting time to be (or become) an epidemiologist!
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ACKNOWLEDGMENTS |
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Conflict of interest: none declared.
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References |
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 TOP References |
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- Oppenheimer GM, Susser E. Invited commentary: The context and challenge of von Pettenkofer's contributions to epidemiology. Am J Epidemiol (2007) 166:1239–41.
[Abstract/Free Full Text] - Evans RJ. Death in Hamburg: society and politics in the cholera years. (2005) London, United Kingdom: Penguin Books.
- Morabia A. Re: "Death in Hamburg: society and politics in the cholera years." (Book review). Prev Med (2007) 45:240–2.[CrossRef]
- McMichael AJ. Prisoners of the proximate: loosening the constraints on epidemiology in an age of change. Am J Epidemiol (1999) 149:887–97.
[Abstract/Free Full Text] - Morabia A. Epidemiologic interactions, complexity, and the lonesome death of Max von Pettenkofer. Am J Epidemiol (2007) 166:1233–8.
[Abstract/Free Full Text] - Descartes R. Discours de la méthode. (1992) Paris, France: Garnier-Flammarion. (Re-publication of 1637 edition).
- Morabia A. Epidemiology: an epistemological perspective. In: History of epidemiological methods and concepts—Morabia A, ed. (2004) Basel, Switzerland: Birkhäuser. 1–126.
- Kuh D, Ben-Schlomo Y. A life course approach to chronic disease epidemiology. (2004) New York, NY: Oxford University Press.
- Diez-Roux AV. Bringing context back into epidemiology: variables and fallacies in multilevel analysis. Am J Public Health (1998) 88:216–22.
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Related articles in Am. J. Epidemiol.:
- Epidemiologic Interactions, Complexity, and the Lonesome Death of Max von Pettenkofer
- Alfredo Morabia
Am. J. Epidemiol. 2007 166: 1233-1238.[Abstract] [FREE Full Text]
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