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.
This workshop introduces participants to the role of social networks—which lie at the very heart of every society—in public health.
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.