Michael Joffe ^1* Jennifer Mindell ¹

¹ Imperial College London

^* To whom correspondence should be addressed. E-mail: m.joffe{at}imperial.ac.uk.

	Abstract

Causal diagrams are rigorous tools for controlling confounding. They also can be used to describe complex causal systems, which is done routinely in communicable disease epidemiology. The use of change diagrams has advantages over static diagrams, because change diagrams are more tractable, relate better to interventions, and have clearer interpretations.

Causal diagrams are a useful basis for modeling. They make assumptions explicit, provide a framework for analysis, generate testable predictions, explore the effects of interventions, and identify data gaps. Causal diagrams can be used to integrate different types of information and to facilitate communication both between public health experts and with experts in other fields. Causal diagrams allow the use of instrumental variables, which can help control confounding and reverse causation.

Key Words: Epidemiology, Health Policy, Prevention, Socioeconomic Factors