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Overview
CausalPaths Analytics was established in 2025 to support a research sub-award from RAND Corporation to UCLA, enabling continued work on NIH-funded mathematical modeling and epidemiological research. While the consultancy currently comprises one principal researcher, the vision is to build collaborative networks with domain experts, behavioral scientists, and fellow modelers as projects demand. This page will expand as those partnerships develop.
Raffaele Vardavas, Ph.D.
Principal, CausalPaths Analytics
Dr. Raffaele Vardavas is a mathematical modeler with 17 years of experience at RAND Corporation, where he developed simulation-based analyses of complex systems for high-stakes policy decisions. He holds a Ph.D. in Physics from Imperial College London and specializes in coupling mathematical models with behavioral dynamics to study disease transmission, policy interventions, and social systems. His research focuses on understanding tipping points, cascades, and critical transitions in systems characterized by deep uncertainty—where prediction is impossible but robust pathway mapping is essential. As Principal Investigator on over $8 million in federal research funding, including two major NIH grants on COVID-19 and influenza transmission dynamics, he has pioneered methods for integrating human behavior and risk perception into epidemiological models. At CausalPaths Analytics, he brings rigorous mathematical frameworks to organizations navigating complexity across health policy, economics, social dynamics, and financial systems.
Part of a Broader Network
Through Dr. Vardavas's role as a manager of the Alliance for Policy Research (APR), CausalPaths Analytics leverages expertise from a broader consortium of policy researchers and methodological experts with experience spanning America's leading think tanks, academic institutions, and government agencies. While CausalPaths focuses on mathematical modeling and simulation-based analysis, this connection to APR provides access to a wider ecosystem of interdisciplinary expertise for clients requiring comprehensive policy research capabilities.
APR members bring advanced research methods—including AI-enhanced analysis—to policy-relevant questions across domains including:
- Health care and public health
- Climate and environmental health
- Emergency management and disaster preparedness
- Emergency medical services
- Education policy
- Labor and workforce development
- Artificial intelligence and technology policy
- Immigration policy
- National security
- Social and criminal justice
- Economic policy
- International development
This collaborative structure enables CausalPaths Analytics to assemble project-specific teams combining quantitative modeling expertise with domain knowledge, behavioral science, qualitative methods, and policy implementation experience—delivering research excellence without institutional overhead.
🔗 Learn more about the Alliance for Policy Research on LinkedIn