It is difficult nowadays to open a popular science magazine, or a leading science journal, without reading about complexity, the approach to science that is expected to “define the scientific agenda for the 21st century.” But this has had little influence on the theory and practice of epidemiology. Complexity is the study of complex adaptive systems, and they key concepts are: self-organisation, adaptation, upheavals at the edge of chaos, the unpredictability of the effects of small changes in the initial conditions, and the existence of simplicity at some levels while chaos exists at others. There are very few examples of the use of complexity theory in epidemiology—the main ones to date involve communicable disease—but there are many examples of epidemiological problems for which complexity theory is relevant. In particular, a focus on the population level, and the socio-cultural context, does not necessitate the use of complexity theory, but it does make its value and potential more relevant. However, complexity theory doesn't fit with standard approaches to epidemiology. If we are not to be “prisoners of the proximate” then it will be necessary to develop new epidemiologic methods that are more appropriate for addressing the complexity of population health. These new methods will look less like a randomised controlled trial, and more like complex observational research such as evolutionary biology and cosmology. If we are going to address the major public health problems of the 21st century, then complexity theory is likely to play an important role.