John Levander

Probabilistic, Decision-theoretic Disease Surveillance and Control

The Pittsburgh Center of Excellence in Public Health Informatics has developed a probabilistic, decision-theoretic system for disease surveillance and control for use in Allegheny County, PA and later in Tarrant County, TX. This paper describes the software components of the system and its knowledge bases. The paper uses influenza surveillance to illustrate how the software components transform data collected by the healthcare system into population level analyses and decision analyses of potential outbreak-control measures.

The Apollo Structured Vocabulary: an OWL2 ontology of phenomena in infectious disease epidemiology and population biology for use in epidemic simulation

BackgroundWe developed the Apollo Structured Vocabulary (Apollo-SV)—an OWL2 ontology of phenomena in infectious disease epidemiology and population biology—as part of a project whose goal is to increase the use of epidemic simulators in public health practice. Apollo-SV defines a terminology for use in simulator configuration. Apollo-SV is the product of an ontological analysis of the domain of infectious disease epidemiology, with particular attention to the inputs and outputs of nine simulators.ResultsApollo-SV contains 802 classes for representing the inputs and outputs of simulators, of which approximately half are new and half are imported from existing ontologies. The most important Apollo-SV class for users of simulators is infectious disease scenario, which is a representation of an ecosystem at simulator time zero that has at least one infection process (a class) affecting at least one population (also a class). Other important classes represent ecosystem elements (e.g., households), ecosystem processes (e.g., infection acquisition and infectious disease), censuses of ecosystem elements (e.g., censuses of populations), and infectious disease control measures.In the larger project, which created an end-user application that can send the same infectious disease scenario to multiple simulators, Apollo-SV serves as the controlled terminology and strongly influences the design of the message syntax used to represent an infectious disease scenario. As we added simulators for different pathogens (e.g., malaria and dengue), the core classes of Apollo-SV have remained stable, suggesting that our conceptualization of the information required by simulators is sound.Despite adhering to the OBO Foundry principle of orthogonality, we could not reuse Infectious Disease Ontology classes as the basis for infectious disease scenarios. We thus defined new classes in Apollo-SV for host, pathogen, infection, infectious disease, colonization, and infection acquisition. Unlike IDO, our ontological analysis extended to existing mathematical models of key biological phenomena studied by infectious disease epidemiology and population biology.ConclusionOur ontological analysis as expressed in Apollo-SV was instrumental in developing a simulator-independent representation of infectious disease scenarios that can be run on multiple epidemic simulators. Our experience suggests the importance of extending ontological analysis of a domain to include existing mathematical models of the phenomena studied by the domain. Apollo-SV is freely available at: http://purl.obolibrary.org/obo/apollo_sv.owl.

Mo1342 A Concept Recognition Tool to Identify the Surgical Complications of Crohn's Disease in Electronic Health Records

Background: Previous studies have shown that diagnosis of Crohns disease (CD) in childhood is associated with a different phenotype when compared to adults (higher risk for ileocolonic disease and fibrostenotic behavior), and may be associated with a more aggressive form of disease requiring more surgery. Those diagnosed at an older age have been reported to have an increased rate of isolated colonic disease and a milder course of disease requiring less surgery. Methods: A comprehensive medical chart review was done for 571 CD patients that were followed in a tertiary referral IBD clinic. Among the parameters that were recorded for each patient at specific time intervals were parameters of disease phenotype according to the Montreal Classification (A1 diagnosed ,16, n=88, A2 diagnosed 16-40, n=287, A3 diagnosed .40, n=77) as well as having surgery. Results: The study included 452 patients that had complete data in the charts. At 6 years from diagnosis and at last follow-up (median11 years), A3 had a higher rate of isolated colonic disease than A1 but not in comparison to A2. Perianal involvement was significantly less common in A3 than A1 or A2. Complicated disease behavior (B2/B3) was similar for all three groups at both time frames. Nonetheless, at 6 years and last follow-up, IBD-related abdominal surgery rates were significantly lower for A1 vs. A2 and vs A3. Conclusions: While there are some disease location differences that emerge with increasing age of presentation (more isolated colonic disease and less perineal disease) disease behavior over time is similar regardless of age at diagnosis and surgeries were least likely in those diagnosed prior to age 16. Our study did not corroborate a more aggressive course for CD that presents in the pediatric age group. Outcomes at 6 years from diagnosis

A Decision-Theoretic Model of Disease Surveillance and Control and a Prototype Implementation for the Disease Influenza

This paper first describes a decision-theoretic model of disease surveillance and control. It then describes a prototype system for influenza monitoring based on the model. The decision-theoretic model connects disparate work epidemiological modelling and disease control under a uniform mathematical formulation. We expect that this model will stimulate new avenues of research in both fields.