Sharable simulations of public health for evidence based policy making

Local health policies are not as evidence based as they could be if the public health impacts of policies were easier to simulate. Here we address the inaccessibility of high quality models of public health and policy - presenting the concepts of a new simulation framework, IMPACT, built on Semantic Web principles. Model and simulation data are persisted with rich semantics and context to support sharing and interpretation. For this purpose, graph storage systems are explored alongside a new framework for mapping clinical data objects to graphical models. The computation employs functional programming for the parallelised simulation of locally representative populations/cohorts changing over time. The input data, model information and simulation results are mapped to social networks of policy making using the Work/Research Object and e-Lab paradigm that is emerging in E-Science.