摘要：The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. By applying a remedy to one sore, you will provoke another; and that which removes the one ill symptom produces others, whereas the strengthening one part of the body weakens the rest. — Sir Thomas More, Utopia, Part I (1516) DESPITE REMARKABLE successes in some areas, the health enterprise in America still faces difficult challenges in meeting its primary objective of reducing the burden of disease and injury. Examples include the growth of the underinsured population, epidemics of obesity and asthma, the rise of drug-resistant infectious diseases, ineffective management of chronic illness, 1 long-standing racial and ethnic health disparities, 2 and an overall decline in the health-related quality of life. 3 Many of these complex problems have persisted for decades, often proving resistant to attempts to solve them. 4 It has been argued that many public health interventions fall short of their goals because they are made in piecemeal fashion, rather than comprehensively and from a whole-system perspective. 5 This compartmentalized approach is engrained in the financial structures, intervention designs, and evaluation methods of most health agencies. Conventional analytic methods are generally unable to satisfactorily address situations in which population needs change over time (often in response to the interventions themselves), and in which risk factors, diseases, and health resources are in a continuous state of interaction and flux. 6 The term dynamic complexity has been used to describe such evolving situations. 7 Dynamically complex problems are often characterized by long delays between causes and effects, and by multiple goals and interests that may in some ways conflict with one another. In such situations, it is difficult to know how, where, and when to intervene, because most interventions will have unintended consequences and will tend to be resisted or undermined by opposing interests or as a result of limited resources or capacities.
