Mathematical modeling in life course research

Approaching (chronic) diseases within a 'life course' framework provides primarily answers to two main questions: What are the long-term effects on health of life events and of previous exposures to risk (or protecting) factors during sensitive periods (e.g. childhood, adolescence) of life? What are the effects of the onset (and course) of a chronic disease on all other variables (such as social and economic pathway, marital status, etc.) that define a life trajectory and how can this influence be modulated by medical and social interventions? In order to tackle such ambitious questions, to collect epidemiological data related to them and to attempt to provide forecasts concerning the effect of interventions, it will be necessary to represent life course trajectories by formal means within a mathematical model in order to render the trajectories classifiable and 'measurable'. We outline briefly some important concepts and techniques that can be applied to the purpose of modeling life course, such as multistate models, Markov models, latent class analysis and sequence analysis.