![]() The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist.Ĭapacity of Safe Outdoor Activity Space and Facilities CSSHF,įig 1. ![]() The U54 project is co-funded by the NICHD and the NIH Office of Behavioral and Social Sciences Research (OBSSR). ![]() This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the paper and its Supporting Information files.įunding: The study was supported by research grants from the Chinese National Social Science Foundation (12CGL103) and the Fundamental Research Funds for the Central Universities to SL, and the Southwestern University of Finance and Economics, the US National Institutes of Health (NIH) (research grants 1R01HD064685-01A1 and U54HD070725 to YW from the Eunice Kennedy Shriver National Institute of Child Health & Human Development ). Received: JAccepted: MaPublished: April 25, 2018Ĭopyright: © 2018 Liu et al. PLoS ONE 13(4):Įditor: Yong Deng, Southwest University, CHINA As this technology becomes more mature, one can design policy flight simulators by which policy/intervention designers can test a variety of assumptions when they evaluate different alternatives interventions.Ĭitation: Liu S, Triantis KP, Zhao L, Wang Y (2018) Capturing multi-stage fuzzy uncertainties in hybrid system dynamics and agent-based models for enhancing policy implementation in health systems research. It can aid the improvement of the optimal allocation of resources for targeted group (s) and the achievement of maximum utility. This research can help practitioners and decision makers to gain better understanding on the dynamics and complexities of precision intervention in healthcare. This research not only enriches the application of fuzzy set theory by capturing the dynamics of variables associated with interacting fuzzy agents that lead to aggregate behaviors but also informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data meaningful and quantifiable in a simulation environment. This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model.
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