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Chronic Pain and Poor Health
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Sample title of Health News Post
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System Dynamics Modeling for Health Decision Making
This workshop introduces participants to key concepts, theory, and tools of system dynamics modeling (SDM) for application in public health and healthcare. Using diverse examples, it guides participants to the nuts and bolts of SDM, including policy resistance, system structure, causal loops diagrams (CLD), reinforcing and balancing loops, stock and flow diagrams (SFD), integration of CLD and SFD, simulation modeling exercises, and sensitivity analysis, using Vensim and AnyLogic. Participants increase their understanding of how SDM can be used together with traditional analytical methods, including epidemiological and biostatistical methods, systematic reviews, and meta-analyses and develop their own SD models and prepare to make sound decisions and design more effective policies in public health and healthcare.
Systems Thinking in Health Research
This workshop introduces participants to how systems thinking can improve understanding of public health challenges and impactful health policies in a dynamic world. Using scenarios from public health and healthcare, it covers simple and more advanced concepts and techniques (e.g., complex adaptive systems, dynamic complexity, model thinking, causal loop diagrams, mental models, networks, tipping points, simulation). Emphasis is placed on how of community and stakeholder engagement can advance their causes.
Network Analysis in Health Research
This workshop introduces participants to the role of social networks—which lie at the very heart of every society—in public health.
Agent-based Modeling for Health Decision Making
This workshop introduces participants to key concepts, theory, methods, and tools of agent-based modeling (ABM) for application in complex and heterogeneous public health and healthcare contexts.
Combining Network, Data, and Computational Sciences to Improve Health Decision Making
This workshop introduces participants to the convergence of data, network, and computational sciences for improving decision and policy making in diverse public health and healthcare contexts. Using big data, it covers how network analysis, machine learning, statistical learning, AI, algorithm design, data mining, optimization techniques, mathematical modeling, statistical mechanics, information visualization, inferential modeling, and computation, in various combinations, can contribute to more effective decision making in various health contexts.
Hybrid Modeling for Population Health Decision Making
This workshop introduces participants to key concepts, theory, methods, and tools of hybrid modeling and simulation for application in complex public health and healthcare contexts.