Abstract
Data obtained from biosurveillance can be used by public health systems to detect and respond to disease outbreaks and save lives. However, existing data is distributed across large geographic areas, and both the quality and type of data vary in space and time. We discuss a framework for analyzing biosurveillance information to minimize detection time and maximize detection accuracy while scaling the analysis over large regions. We propose that strategies used by canonical biological complex systems, which are adapted to diverse environments, provide good models for the design of a robust, adaptive, and scalable biosurveillance system. Drawing from knowledge of the adaptive immune system, and ant colonies, we examine strategies that support the scaling of detection in order to search and respond in large areas with dynamic distributions of data. Based on this research, we discuss a bioinspired approach for a distributed, adaptive, and scalable biosurveillance system.
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Acknowledgments
We gratefully acknowledge funding from a Sandia National Laboratories Academic Alliance LDRD Award. TPF and MEM also acknowledge funding from the McDonnell Foundation Complex Systems Scholar Award. We also thank Judy Cannon for her insightful guidance on immune system memory cells, Stephanie Forrest for insightful discussions about negative selection and its relevance to biosurveillance, and Louise Maffitt for helpful editing suggestions.
Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. The views expressed in the article do not necessarily represent the views of the U.S. Department of Energy or the United States Government.
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Flanagan, T., Beyeler, W., Levin, D., Finley, P., Moses, M. (2019). Movement and Spatial Specificity Support Scaling in Ant Colonies and Immune Systems: Application to National Biosurveillance. In: Georgiev, G., Smart, J., Flores Martinez, C., Price, M. (eds) Evolution, Development and Complexity. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-00075-2_15
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DOI: https://doi.org/10.1007/978-3-030-00075-2_15
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