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Public health policy decision makers need analytical and interactive features in epidemic simulation systems, along with the ability to simulate disease propagation over large scale populations, ranging over millions of individuals. To fulfill these requirements, we decided to re-engineer existing epidemiological software systems and integrate them together such that the performance of the overall system was minimally affected. The systems that were part of the integration effort included EpiFast, an HPC-based simulation engine, that simulates disease diffusion over multiple regions; ISIS, a web-based visual interface tool, used for analyzing the role of different parameters in disease propagation; and a database management system, storing and operating on the demographic and geographic information about different city populations. We analyzed the feasibility of existing middleware platforms to support the integration and developed a new architecture that achieves seamless and efficient integration of component systems. The integrated software system provides a combination of capability along with usability and flexibility, required by public health policy decision makers to study epidemics holistically. It also allows reuse of complex intervention strategies defined by multiple users through the web-based interface and reduces the overall time to set-up experiments and manage data. In this paper, we describe the flexible architecture that made the integration of these distinct software components possible and report on the case studies that show considerable improvement in productivity of decision makers and epidemiologists using the new integrated tool.