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

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

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

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

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

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

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 emerge from individual actions

Agent-Based Models SIR Susceptible Infected Recovered 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

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

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

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

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

Transmission pathways – Patient  nurse  patient – Patient  physician  patient – Patient  environment  nurse  patient – Patient  environment  physician  patient – Patient  environment  roommate – Patient  environment  subsequent occupant

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

Contact Networks

Model animation

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 Types of Interventions

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

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