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Table 1 Description of dynamic simulation modelling case studies and context

From: Decision makers’ experience of participatory dynamic simulation modelling: methods for public health policy

Topic area Type of model Model development period Context Application to decision making
Reduction of alcohol-related harms (Alcohol) Agent based model 2015–2016 Alcohol misuse is an important public health issue for which there are complex causal mechanisms and contested intervention options. This model was developed to inform jurisdictional government strategies for reducing alcohol-related harms. The model represents the heterogeneity of alcohol use across the population, how the dynamics of drinking behaviours vary across the life course, the harms, both short and long term, that arise from alcohol use, and the differential effects of interventions across subgroups in the population.
Reduction of childhood overweight and obesity (Obesity) System dynamics model 2016 In 2015, an Australian State Premier set an ambitious target to reduce childhood overweight and obesity in children by 5 % over 10 years. It was predicted that additional strategies, or combinations of strategies, would be required to achieve the Premier’s target. Decision makers were presented with the challenge of determining where best to focus resources and efforts. The model explores the complex issue of child overweight and obesity, incorporates existing programs and tests the likely impacts of a range of policies and programs. It forecasts the combination of interventions required to achieve the Premier’s target.
Prevention and management of Diabetes in Pregnancy (DIP) Hybrid model (system dynamics, agent based modelling and discrete event simulation) 2016–2017 . Diabetes in pregnancy is increasing in Australia and internationally and exploration of new strategies to prevent and manage the condition is needed. The model considers the short, and long-term implications of the increasing prevalence of both DIP and associated risk factors. The model focuses on the development of Diabetes in Pregnancy (DIP) from the perspective of the individual. Prevention interventions were prioritised in the model as delays in the development of diabetes will potentially result in reduction in the longer-term burden of disease and costs to the health system. However, the model can also explore clinical interventions. Health service utilisation has been captured in the model enabling it to explore the resource impact of model of care scenarios.