Objective

1. To develop a comprehensive model characterization framework

to describe epidemiological models in an operational context.

2. To apply the framework to characterize “operational” models

for specific infectious diseases and provide a web-based directory,

the biosurveillance analytics resource directory (BARD) to the global

infectious disease surveillance community.

Introduction

Epidemiological modeling for infectious disease is useful for

disease management and routine implementation needs to be

facilitated through better description of models in an operational

context. A standardized model characterization process that allows

selection or making manual comparisons of available models and

their results is currently lacking. Los Alamos National Laboratory

(LANL) has developed a comprehensive framework that can be used

to characterize an infectious disease model in an operational context.

We offer this framework and an associated database to stakeholders of

the infectious disease modeling field as a tool for standardizing model

description and facilitating the use of epidemiological models. Such a

framework could help the understanding of diverse models by various

stakeholders with different preconceptions, backgrounds, expertise,

and needs, and can foster greater use of epidemiological models as

tools in infectious disease surveillance.

Methods

We define, “operational” as the application of an epidemiological

model to a real-world event for decision support and can be used by

experts and non-experts alike. The term “model” covers three major

types, risk mapping, disease dynamics and anomaly detection.

To develop a framework for characterizing epidemiological models

we collected information via a three-step process: a literature search

of model characteristics, a review of current operational infectious

disease epidemiological models, and subject matter expert (SME)

panel consultation. We limited selection of operational models to

five infectious diseases: influenza, malaria, dengue, cholera and

foot-and-mouth disease (FMD). These diseases capture a variety

of transmission modes, represent high or potentially high epidemic

or endemic burden, and are well represented in the literature. We

also developed working criteria for what attributes can be used to

comprehensively describe an operational model including a model’s

documentation, accessibility, and sustainability.

To apply the model characterization framework, we built the

BARD, which is publicly available (http://brd.bsvgateway.org).

A document was also developed to describe the usability requirements

for the BARD; potential users (and non-users) and use cases are

formally described to explain the scope of use.

Results

1. Framework for model characterization

The 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 which

has several sub-categories for characterizing each aspect of a model.

2. Application to model characterization

Models for five infectious diseases—cholera, malaria, influenza,

FMD and dengue were characterized

using the framework and are included in the BARD database. Our

framework characterized disparate models in a streamlined fashion.

Model information could be binned into the same categories, allowing

easy manual comparison and understanding of the models.

3. Development of the BARD

Our model characterization framework was implemented into an

actionable tool which provides specific information about a model

that has been systematically categorized. It allows manual categoryto-

category comparison of multiple models for a single disease and

while the tool does not rank models it provides model information in

a format that allows a user to make a ranking or an assessment of the

utility of the model.

Conclusions

With the model characterization framework we hope to encourage

model developers to start describing the many features of their models

using a common format. We illustrate the application of the framework

through the development of the BARD which is a scientific and

non-biased tool for selecting an appropriate epidemiological model

for infectious disease surveillance. Epidemiological models are not

necessarily being developed with decision makers in mind. This gap

between model developers and decision makers needs to be narrowed

before modeling becomes routinely implemented in decision making.

The characterization framework and the tool developed (BARD) are

a first step towards addressing this gap.

Keywords

epidemiological models; database; decision support