The broad aim of the proposed work is to make epidemic models as readily available to health agencies, and as easy-to-use as are weather models for local TV stations. The project will standardize the vocabulary and syntax used in epidemic modeling. By standardizing the many parameters that epidemic models require to represent disease transmission, the health status of a population, disease transmission, and disease control measures, the project will decrease the time and effort required to develop epidemic models and will make them more available to scientific and clinical users of these models.
The specific aims are to (1) develop a standard vocabulary for the field of epidemic modeling using a tool called Prot?g?;(2) create two extensions to Prot?g? that are needed by the project;(3) develop a standard syntax using the vocabulary for representing the inputs (e.g., disease control measures) and outputs of epidemic models and to use this syntax in an existing system called the Apollo Web Service that makes it possible for other computer programs to access epidemic models;and (4) to increase the capacity to run epidemic models on supercomputers so as to demonstrate the value of the work of the first three aims. The project will work with epidemic modelers from the MIDAS research network to develop the standard vocabulary and syntax. It will use the extended Prot?g? software to develop the standard vocabulary as an ontology, which is a formal representation of objects and their interrelations. It will represent syntax using the XML language. An analysis of the input and output data currently used by epidemic models will drive the design of the syntax. The expected impact of the proposed research is that state and federal officials with responsibility t respond to epidemics will routinely and effortlessly incorporate the predictions of epidemic models into their decision making, thereby increasing significantly the value of the science of epidemic modeling to society.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Biodata Management and Analysis Study Section (BDMA)
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Eckstrand, Irene A
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University of Pittsburgh
Schools of Medicine
United States
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Hanna, Josh; Bian, Jiang; Hogan, William R (2016) An accurate and precise representation of drug ingredients. J Biomed Semantics 7:7
Hogan, William R; Wagner, Michael M; Brochhausen, Mathias et al. (2016) The Apollo Structured Vocabulary: an OWL2 ontology of phenomena in infectious disease epidemiology and population biology for use in epidemic simulation. J Biomed Semantics 7:50
Wagner, Michael M; Levander, John D; Brown, Shawn et al. (2013) Apollo: giving application developers a single point of access to public health models using structured vocabularies and Web services. AMIA Annu Symp Proc 2013:1415-24
Hogan, William R; Hanna, Josh; Joseph, Eric et al. (2013) Towards a Consistent and Scientifically Accurate Drug Ontology. CEUR Workshop Proc 1060:68-73