  Today's most troublesome population health challenges are often driven by
social and environmental determinants, which are difficult to model using
traditional epidemiological methods. We agree with those who have argued for
the wider adoption of agent-based modelling (ABM) in taking on these
challenges. However, while ABM has been used occasionally in population health,
we argue that for ABM to be most effective in the field it should be used as a
means for answering questions normally inaccessible to the traditional
epidemiological toolkit. In an effort to clearly illustrate the utility of ABM
for population health research, and to clear up persistent misunderstandings
regarding the method's conceptual underpinnings, we offer a detailed
presentation of the core concepts of complex systems theory, and summarise why
simulations are essential to the study of complex systems. We then examine the
current state of the art in ABM for population health, and propose they are
well-suited for the study of the `wicked' problems in population health, and
could make significant contributions to theory and intervention development in
these areas.
