Software Development & Core Facilities

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The overall goal of the software development and core facilities section is to make the new methodologies, algorithms, and models developed in the MIDAS Center's research projects more accessible to both the research and public health communities. To do so, we will integrate some of the independently developed tools to create a coherent computational infrastructure that is more than the sum of its methodological parts. In particular, we propose to develop and to maintain a suite of computational tools for infectious disease modeling and analysis centered around a multi-scale modeling computational platform (MCP), optimized for cloud deployment. The major aims of the software developments are: i) Develop an MCP capable of integrating large scale stochastic modeling approaches working at different scales of resolution. We will start by creating a multiscale hybrid model based on combining the global individual-based metapopulation model GLEAM with the US scale agent-based influenza model FluTE. The MCP architecture will be designed around the existing GLEAMviz client-server architecture. It will be expanded with the development of Application Programming Interfaces (APIs) for the plug-in of models developed by the MIDAS research community. The MCP will consist of computationally intensive tools, so we plan to design and to deploy a cloud computing environment with elastic capabilities, ii) Develop new features and graphical user interfaces (GUIs) for statistical tools developed in the context of the research activities of the Center such as extensions of pomp, TranStat, among others. We will develop integrated workflows aimed at allowing those programs to exchange data and parameter estimates with the MCP in an automated way. iii) Develop a website that will act as a sharing repository for the software developed in this MIDAS Center, with training materials, manuals, and workflow examples. We aim to provide the best accessibility and to foster adoption of the developed software by MIDAS, the research community, and public health agencies by using best practices and public repositories