Simulacra & Simulation (& Health Care-Associated Infections)

1. Simulacra & Simulation(& Health Care-Associated Infections) Michael Rubin, MD, PhD Section Chief, Epidemiology VA Salt Lake City Health Care System

2. Military Simulations • Models in which theories of warfare can be tested and refined without the need for actual hostilities • Provide insights that can be applied to real-world situations • a non-prescriptive attempt to inform the decision-making process

3. Military Simulations • Exist in many different forms, with varying degrees of realism • Are they really useful?

6. Models in Healthcare Research • Familiar models • Statistical regression models: • Linear, Logistic, Poisson, etc. • Used for prediction, inference, hypothesis testing, and modeling of causal relationships • Rely heavily on the underlying simplifying assumptions being satisfied

7. Models in Healthcare Research • Familiar models • Equation-based models • Compartmental models, Differential Equation models βI(t) r I(t) R(t) S(t) S I R

8. Models in Healthcare Research • Less familiar models: simulations • Many different types of simulations • Continuous Dynamic simulations • Discrete Event simulations • Monte Carlo simulations • Agent-based simulations

9. Agent-Based Models • Agent-based models • Individual-based models/Individual-agent models • System is modeled as collection of autonomous decision-making entities (agents) which exist/interact within an environment or framework • Each agent assesses its situation and makes decisions based on a set of rules (behaviors) and characteristics (parameters) • System-level observables emergefrom individual actions

10. Agent-Based Models S I R Each individual agent exists in a particular “state” (“Statechart”) States correspond to the different compartments in the SIR model Transitions between states are governed by rates Susceptible Infected Recovered

11. Agent-Based Models • Agent-based models: Benefits • Can explore dynamics out of the reach of pure mathematical methods • Events occur stochastically rather than deterministically • Can exhibit complex behavior patterns, sometimes unanticipated • Captures emergent phenomena • Provides a natural description of a system • What-if experimentation is accommodated

12. Agent-Based Models • Situations appropriate for simulation • questions that are too expensive, complicated, or difficult to answer in meatspace • situations where it is impossible (or extremely difficult) to know the absolute "truth" • systems with complex interactions or behaviors that are difficult to express with mathematical equations

13. MRSA Simulation • Detailed simulation of hospital setting • Patient admissions, transfers, discharges • ICU and non-ICU wards; private and double rooms • Healthcare worker (doctor, nurse) contacts with patients • Environmental contamination • Performance of surveillance testing

14. Model Components • Patient • Room • Ward/ICU • Nurse • Physician • Network structure • Surveillance

15. Transmission pathways • Patient  nurse  patient • Patient  physician  patient • Patient  environment  nurse  patient • Patient  environment  physician  patient • Patient  environment  roommate • Patient  environment  subsequent occupant

16. Agents and states patient room nurse ADMISSION CLINICAL EVENTS COLONIZATION EVENT asymptomatic off antibiotics node-colonization uncontaminated no isolation unoccupied uncontaminated not colonized uncontaminated symptomatic on antibiotics de-colonization colonized contaminated contaminated contact isolation occupied contaminated DISCHARGE physician

17. Contact Networks

18. Model animation

19. Types of Interventions • Alternative surveillance approaches • Reduce (or increase) antibiotic use • Improve hand hygiene • Modify health care worker - patient contact networks • Expedite discharge • Selectively screen contacts • Decolonize • Carriers versus high-risk patients • Health care workers

20. MRSA Simulation • Types of questions that can be addressed: • Time to observe decrease in MRSA acquisition? • Do interventions exhibit threshold effects? • How long will it take for a policy to exhibit an effect? • Better to decolonize at admission or discharge? • Time course for effects on community prevalence? These questions cannot be fully addressed by clinical trials

21. Rural Health Care Access • Can simulation be used to study and optimize access to care in rural settings? • How to optimize access to care across a population in a catchment area • Goal is to design an interactive agent-based simulation model that can be used by researchers and planners to test varying strategies of addressing access in their system