Selecting essential information for biosurveillance--a multi-criteria decision analysis.

The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels." However, the strategy does not specify how "essential information" is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being "essential". The question of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of "essential information" for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.

Advancing a framework to enable characterization and evaluation of data streams useful for biosurveillance.

In recent years, biosurveillance has become the buzzword under which a diverse set of ideas and activities regarding detecting and mitigating biological threats are incorporated depending on context and perspective. Increasingly, biosurveillance practice has become global and interdisciplinary, requiring information and resources across public health, One Health, and biothreat domains. Even within the scope of infectious disease surveillance, multiple systems, data sources, and tools are used with varying and often unknown effectiveness. Evaluating the impact and utility of state-of-the-art biosurveillance is, in part, confounded by the complexity of the systems and the information derived from them. We present a novel approach conceptualizing biosurveillance from the perspective of the fundamental data streams that have been or could be used for biosurveillance and to systematically structure a framework that can be universally applicable for use in evaluating and understanding a wide range of biosurveillance activities. Moreover, the Biosurveillance Data Stream Framework and associated definitions are proposed as a starting point to facilitate the development of a standardized lexicon for biosurveillance and characterization of currently used and newly emerging data streams. Criteria for building the data stream framework were developed from an examination of the literature, analysis of information on operational infectious disease biosurveillance systems, and consultation with experts in the area of biosurveillance. To demonstrate utility, the framework and definitions were used as the basis for a schema of a relational database for biosurveillance resources and in the development and use of a decision support tool for data stream evaluation.

An epidemiological model of spatial coupling for trips longer than the infectious period.

One of the standard methods of accounting for inter-population disease spread in equation-based epidemiology models is through a transportation operator. Implicit in the use of the transportation operator, however, is an assumption that daily travel volumes are small compared to overall population sizes, an assumption that can break down for modern rates of international travel or local commuter traffic. Alternative types of coupling have been proposed in the limit that trip durations are much shorter than the infectious period. We present an extension of these phenomenological models that relaxes both assumptions. We show that the approach produces more accurate results when assessing the impact of mitigative actions using modern travel volumes.

Reaerosolization of Bacillus spp. in outdoor environments: a review of the experimental literature.

Reaerosolization or resuspension-that is, the reintroduction of previously airborne particles into the atmosphere-is a complex phenomenon. Microbial reaerosolization is particularly poorly understood because few studies have been done in this area, and many of the studies that have been performed are not in the peer-reviewed literature. The reaerosolization of Bacillus anthracis in outdoor environments is of particular concern because of its stability and potential for use as a biological weapon. This review pulls together data from more than 30 publications, spanning field and laboratory experiments, to summarize the current state of our understanding of Bacillus spp. reaerosolization in outdoor environments.

Topology of two-dimensional turbulence.

Velocity differences in the direct enstrophy cascade of two-dimensional turbulence are correlated with the underlying flow topology. The statistics of the transverse and longitudinal velocity differences are found to be governed by different structures. The wings of the transverse distribution are dominated by strong vortex centers, whereas the tails of the longitudinal differences are dominated by saddles. Viewed in the framework of earlier theoretical work, this result suggests that the transfer of enstrophy to smaller scales is accomplished in regions of the flow dominated by saddles.