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To characterize the site-specific mechanical and histological properties in fracture repair and to relate these properties to the initial mechanical situation, an experimental fracture model was used in the metatarsus of 42 sheep. The mechanical situation of a transverse osteotomy was described by three gap sizes (1, 2, or 6 mm) and two amounts of strain (7 or 31%). An external fixator that allowed a defined axial movement provided control of these settings. Nine weeks following surgery, the healing area was dissected and tensile and compressive properties were measured in subregions of the fracture gap and the periosteal callus. The central, sagittal section was used for quantitative histology. We found the quality of the tissue along the osteotomy line to be most important for regaining mechanical stability. Increasing the size of osteotomy gaps resulted in poorer mechanical and histological qualities, and the repair process was less complete. Interfragmentary strain did not significantly influence the repair process. The smaller strain levels had already stimulated the secondary repair process, and this stimulatory effect could not be further enhanced by increasing the amount of strain. Our finding that large gaps between bone segments were not as well healed as were smaller gaps suggests that it is advantageous to avoid large gaps in fracture treatment.

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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.