Hogan, W. (Principal Investigator on subcontract from the University of Pittsburgh / Professor, Health Outcomes & Policy, University of Florida and Director of Biomedical Informatics, UF Clinical & Translational Science Institute), Espino, J. (Principal Investigator / MD, Department of Biomedical Informatics, University of Pittsburgh), Wagner, M. (Principal Investigator / Associate Professor, Director of Cooperate Relations, Department of Biomedical Informatics, University of Pittsburgh). UPITT NIH (NIGMS). 8/5/14– 4/30/15. Award amount: $2,375,816.
The overall goal of the Modeling Infectious Disease Agent Study (MIDAS) Informatics Services Group is to provide a set of services to the MIDAS network and its customers: researchers, practitioners, and agencies responsible for the public’s health. The services range from expert consultations to software development. Dr. Hogan is developing a catalog service that indexes and facilitates the retrieval of information items that include datasets, publications, reports, white papers, and epidemic simulators. An innovative feature of this catalog is that it contains an ontological representation of the biological phenomena that the information items are about, and then indexes the items against this representation. We hypothesize that this reality-based approach will outperform a term-based, conceptual approach of typical resources like Medical Subject Headings, as well as unify diverse information items including datasets and publications in a single catalog.
Apollo: Increasing Access and Use of Epidemic Models Through the Development and Adoption of a Standard Ontology
Hogan, W. (Principal Investigator / Professor, Health Outcomes & Policy, University of Florida and Director of Biomedical Informatics, UF Clinical & Translational Science Institute), Wagner, M. (Principal Investigator / Associate Professor, Department of Biomedical Informatics, University of Pittsburgh). UPITT NIH (NIGMS). 7/1/14– 3/31/15. Award amount: $1,065,968.
The science and practice of infectious disease epidemiology, like climate science, is increasingly reliant on computational simulation. The simulators — known as epidemic simulators or more generally disease transmission models (DTMs) — require machine-interpretable information about pathogens, rates of infection transmission, populations of hosts, interventions, and the outcomes of infections. Using this input information — which we refer to as an infectious disease scenario — a simulator’s algorithm computes the progression of one or more infections in one or more populations over time, under zero or more interventions. The result of this computation — the output of the simulator — is information on which decision makers can base policy or decisions about disease control. To address this problem, we are developing machine- interpretable representations for the input and outputs of DTMs and promulgating their adoption as de facto standards. The key goal of the standards is to enable an analyst to specify the same infectious disease scenario exactly once, and run the scenario on multiple simulators with no additional effort. Dr. Hogan is leading the development of the Apollo-SV ontology that is the terminological component of the overall Apollo standard.