Dynamic Graph Analytic Framework (DYGRAF) for biosurveillance support

In this work, we leverage Dynamic Graph Analytic Framework (DYGRAF), a domain agnostic framework from which data alignment, data association and layered multi-modal network analysis can be performed. By applying DYGRAF to the discipline of biosurveillance, and incorporating disparate yet related data sets stemming from medical, communication, and financial domains, salient information about the origin and propagation of a pandemic can be identified, including the key people and locations involved in the spread of a disease within and across communities. Through the identification and leveraging of this information, DYGRAF enables an analyst to gain a greater understanding of the current situation, allowing the analyst to develop strategies to limit the extent and effects of the pandemic.