Public Health Dynamics Laboratory Using computational models to advance the theory and practice of Public Health Mark S. Roberts, MD, MPP Professor and Chair, Health Policy and Management Director, PHDL Briefing for Michelle Dunn, PhD Senior Advisor, Data Science Training, Diversity and Outreach Office of the Associate Director for Data Science National Institutes of Health PHDL Overview

Public Health Decision Mental & Computational Models in Public Health "All decisions are made on the basis of models. Most models are in our heads. Mental models are not true and accurate images of our surroundings, but are only sets of assumptions and observations gained from experiences ... Computer simulation models can compensate for weaknesses in mental models" (Forrester, 1994). Prior individual knowledge Mental Model Public Health Decision Expert advice Why open access to public health data is important NOW vs. previously: - new methods for analysis - more data collected Statistical models Mechanistic Models & Simulations Data PHDL Overview

Mission of the Public Health Dynamics Lab Develop interdisciplinary approaches using computational models to advance the theory and practice of Public Health Contribute to "Systems Thinking" in the training of the next generation of health professionals Develop and distribute computational tools to be used to improve real-world population health decision- making PHDL Overview

“Systems Public Health” A Systems Approach to Public Health “Systems Public Health” Scale 108 m Earth 106 m Country 104 m City 102 m Village 100 m Human 10-2m Organ 10-4 m Lymph Follicle 10-6 m Cell 10-8 m DNA 10-10 m Nucleotide 10-12 X Ray 10-14 Atomic Nucleus “Systems Biology” PHDL Overview

Sponsors and Partners Models of Infectious Disease Agent Study (MIDAS) National Center of Excellence PI: Burke Sponsor: NIGMS/NIH (Harvard, Washington, 12 others) Vaccine Modeling Initiative PI Burke Sponsor: Bill & Melinda Gates Foundation (Imperial and Princeton) Public Health Adaptive Systems Studies PI: Potter Sponsor: CDC Public Health International Modeling Fellows Program PI: Grefenstette/Burke Sponsor: Benter Foundation Partners: www.midas.pitt.edu www.vaccinemodeling.org www.phasys.pitt.edu Benter Foundation PHDL Overview

FRED (Framework for Reconstructing Epidemiological Dynamics) PHDL Overview

Census-matched Synthetic Population PHDL Overview 7

Matched actual demographics Iterative proportional fitting assures that synthetic attributes are distributed as real ones are

Individual-based models focus on how interactions among individual simulated agents can result in complex patterns at a population level. Here is a movie of our team’s first large scale model (of the possible introduction of avian influenza into the USA). Each agent is explicitly modeled and tracked Agents have individual features: age, sex, occupation, health Agents interact with a limited set of other agents based on shared activity Agents have bounded rationality and make use of realistic decision rules based on local information Agents usually interact within an explicit geographical environment Over time, agent interactions can generate large-scale macrosopic phenomena of fundamental interest Ferguson NM, Cummings DA, Fraser C, Cajka JC, Cooley PC, Burke DS. Strategies for mitigating an influenza epidemic Nature July 27, 2006; 442: 448-52 PHDL Overview

Prediction – Pushing the Boundaries PHDL Overview

Modeling to Inform Policy We have seen several example of PHDL-derived tools used in policy FRED used to estimate mitigation strategies in 2009 Flu epidemic Tycho and FRED Measles to inform consequences of vaccination rates Our expertise has provided a platform (PI Everette James) to conduct research for PA: “University will assist DPW in monitoring and evaluating changes in health insurance coverage; access to care; health care and Medicaid financing; state and federal policies, regulations and legislation affecting health care; and the quality of health care delivery in the Commonwealth’s Medicaid program.” PHDL Overview

FRED Measles http://fred.publichealth.pitt.edu/measles/ PHDL Overview

Fred Ages and Stages PHDL Overview

Goal: High Resolution Detail in FRED Diseases: Diabetes Heart Disease Hypertension Asthma COPD other chronic dz  Environmental Characteristics Pollution Walkability Food deserts PHDL Overview

Clinically complex model of Hepatitis C Aspirational future Social Network/ Behavioral Research . Infection/Transmission Research . . . . . . . . . . . . . . . . Cardiovascular Disease . . . . . . . . Influenza . . . . . . . . . . . . . . . . . . . . . . HIV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Clinically complex model of Hepatitis C . . . . . . . . Geographic/Social Specificity Legal and Regulatory Population Behavior Health Care Simulation Health Care Resources Engine Costs Disease Interventions in silico Pennsylvania Agent-Based Simulation Model (FRED) PHDL Overview 15