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

Public Health Relevance

To extend the results of the MIDAS Center's research projects beyond academia, the Software Development team will help translate the research into products that can be used by external researchers and public health officials. The scope of work includes dissemination of the Center's research tools, updating computational tools to suit the needs of users, and integrating multiple tools into coherent, usable platforms.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
1U54GM111274-01
Application #
8796477
Study Section
Special Emphasis Panel (ZGM1-BBCB-5 (MI))
Project Start
Project End
Budget Start
2014-09-12
Budget End
2015-06-30
Support Year
1
Fiscal Year
2014
Total Cost
$181,046
Indirect Cost
$46,312
Name
Fred Hutchinson Cancer Research Center
Department
Type
DUNS #
078200995
City
Seattle
State
WA
Country
United States
Zip Code
98109
Domenech de Cellès, Matthieu; Magpantay, Felicia M G; King, Aaron A et al. (2018) The impact of past vaccination coverage and immunity on pertussis resurgence. Sci Transl Med 10:
Dinh, Vu; Tung Ho, Lam Si; Suchard, Marc A et al. (2018) Consistency and convergence rate of phylogenetic inference via regularization. Ann Stat 46:1481-1512
Yang, Yang; Meng, Ya; Halloran, M Elizabeth et al. (2018) Reply to Aguiar and Stollenwerk. Clin Infect Dis 66:642
Bretó, Carles (2018) Modeling and inference for infectious disease dynamics: a likelihood-based approach. Stat Sci 33:57-69
Doud, Michael B; Lee, Juhye M; Bloom, Jesse D (2018) How single mutations affect viral escape from broad and narrow antibodies to H1 influenza hemagglutinin. Nat Commun 9:1386
Moore, James; Ahmed, Hasan; Antia, Rustom (2018) High dimensional random walks can appear low dimensional: Application to influenza H3N2 evolution. J Theor Biol 447:56-64
Claywell, Brian C; Dinh, Vu; Fourment, Mathieu et al. (2018) A Surrogate Function for One-Dimensional Phylogenetic Likelihoods. Mol Biol Evol 35:242-246
Sun, Kaiyuan; Zhang, Qian; Pastore-Piontti, Ana et al. (2018) Quantifying the risk of local Zika virus transmission in the contiguous US during the 2015-2016 ZIKV epidemic. BMC Med 16:195
Antia, Alice; Ahmed, Hasan; Handel, Andreas et al. (2018) Heterogeneity and longevity of antibody memory to viruses and vaccines. PLoS Biol 16:e2006601
Fourment, Mathieu; Claywell, Brian C; Dinh, Vu et al. (2018) Effective Online Bayesian Phylogenetics via Sequential Monte Carlo with Guided Proposals. Syst Biol 67:490-502

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