The Modeling Core targets the development, validation and re?nement of models to predict pathogen genetic and host immune response and physiological features affecting viral hemorrhagic fever survival and long-term sequelae of Lassa virus (LASV) and Ebola virus (EBOV) infection. Our multidisciplinary team carries expertise across statistical thinking, mathematical modeling, evolutionary biology and computing to leverage sequenc- ing, immunological pro?ling, mobile sensor and clinical data. We provide to the Consortium for Viral Systems Biology Cores and Projects guidance in phylogenetic reconstruction to de?ne evolutionary trajectories and cataloguing LASV and EBOV intra-host variants, genetic association studies mapping host determinants and, importantly, consultation on all statistical aspects of experimental design in the Projects. Our chief innova- tions are three-fold. First, we incorporate viral sequence evolution into predictive survival models through the development of phylogenetic survival analysis to uncover the viral and host genetic determinants of host time-to-event health outcomes while appropriately controlling for shared evolutionary history and incorporat- ing adaptive immunity repertoire development. We integrate large-scale non-omics data into these survival models using advancing computing technology to include time-dependent immunological and physiological features arising from wireless patient monitors and clinical tests. Third, we exploit systems-level prediction evaluation and re?nement for iterative model building with internal validation, biological experimentation and network analysis. The Core will deliver effective analysis tools enabled for real-time and scriptable use in open- source, reproducible research and will marshall both hands-on short-courses and a regular virtual quantitative clinic to catalyze the interactions between modeling and experimentation.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI135995-04
Application #
10087876
Study Section
Special Emphasis Panel (ZAI1)
Project Start
2018-02-01
Project End
2023-01-31
Budget Start
2021-02-01
Budget End
2022-01-31
Support Year
4
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Scripps Research Institute
Department
Type
DUNS #
781613492
City
La Jolla
State
CA
Country
United States
Zip Code
92037
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