Objective1. To develop a comprehensive model characterization frameworkto describe epidemiological models in an operational context.2. To apply the framework to characterize “operational” modelsfor specific infectious diseases and provide a web-based directory,the biosurveillance analytics resource directory (BARD) to the globalinfectious disease surveillance community.IntroductionEpidemiological modeling for infectious disease is useful fordisease management and routine implementation needs to befacilitated through better description of models in an operationalcontext. A standardized model characterization process that allowsselection or making manual comparisons of available models andtheir results is currently lacking. Los Alamos National Laboratory(LANL) has developed a comprehensive framework that can be usedto characterize an infectious disease model in an operational context.We offer this framework and an associated database to stakeholders ofthe infectious disease modeling field as a tool for standardizing modeldescription and facilitating the use of epidemiological models. Such aframework could help the understanding of diverse models by variousstakeholders with different preconceptions, backgrounds, expertise,and needs, and can foster greater use of epidemiological models astools in infectious disease surveillance.MethodsWe define, “operational” as the application of an epidemiologicalmodel to a real-world event for decision support and can be used byexperts and non-experts alike. The term “model” covers three majortypes, risk mapping, disease dynamics and anomaly detection.To develop a framework for characterizing epidemiological modelswe collected information via a three-step process: a literature searchof model characteristics, a review of current operational infectiousdisease epidemiological models, and subject matter expert (SME)panel consultation. We limited selection of operational models tofive infectious diseases: influenza, malaria, dengue, cholera andfoot-and-mouth disease (FMD). These diseases capture a varietyof transmission modes, represent high or potentially high epidemicor endemic burden, and are well represented in the literature. Wealso developed working criteria for what attributes can be used tocomprehensively describe an operational model including a model’sdocumentation, accessibility, and sustainability.To apply the model characterization framework, we built theBARD, which is publicly available (http://brd.bsvgateway.org).A document was also developed to describe the usability requirementsfor the BARD; potential users (and non-users) and use cases areformally described to explain the scope of use.Results1. Framework for model characterizationThe framework is divided into six major components (Figure 1):Model Purpose, Model Objective, Model Scope, Biosurveillance(BSV) goals, Conceptual Model and Model Utility; each of whichhas several sub-categories for characterizing each aspect of a model.2. Application to model characterizationModels for five infectious diseases—cholera, malaria, influenza,FMD and dengue were characterizedusing the framework and are included in the BARD database. Ourframework characterized disparate models in a streamlined fashion.Model information could be binned into the same categories, allowingeasy manual comparison and understanding of the models.3. Development of the BARDOur model characterization framework was implemented into anactionable tool which provides specific information about a modelthat has been systematically categorized. It allows manual categoryto-category comparison of multiple models for a single disease andwhile the tool does not rank models it provides model information ina format that allows a user to make a ranking or an assessment of theutility of the model.ConclusionsWith the model characterization framework we hope to encouragemodel developers to start describing the many features of their modelsusing a common format. We illustrate the application of the frameworkthrough the development of the BARD which is a scientific andnon-biased tool for selecting an appropriate epidemiological modelfor infectious disease surveillance. Epidemiological models are notnecessarily being developed with decision makers in mind. This gapbetween model developers and decision makers needs to be narrowedbefore modeling becomes routinely implemented in decision making.The characterization framework and the tool developed (BARD) area first step towards addressing this gap.Keywordsepidemiological models; database; decision support
Operationalizing Cooperative Research for Infectious Disease Surveillance: Lessons Learned and Ways Forward
