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![Page 1: Simulacra & Simulation (& Health Care-Associated Infections) Michael Rubin, MD, PhD Section Chief, Epidemiology VA Salt Lake City Health Care System.](https://reader030.fdocuments.in/reader030/viewer/2022032802/56649e175503460f94b027fb/html5/thumbnails/1.jpg)
Simulacra & Simulation(& Health Care-Associated Infections)
Michael Rubin, MD, PhDSection Chief, Epidemiology
VA Salt Lake City Health Care System
![Page 2: Simulacra & Simulation (& Health Care-Associated Infections) Michael Rubin, MD, PhD Section Chief, Epidemiology VA Salt Lake City Health Care System.](https://reader030.fdocuments.in/reader030/viewer/2022032802/56649e175503460f94b027fb/html5/thumbnails/2.jpg)
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
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Military Simulations
• Exist in many different forms, with varying degrees of realism
• Are they really useful?
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![Page 5: Simulacra & Simulation (& Health Care-Associated Infections) Michael Rubin, MD, PhD Section Chief, Epidemiology VA Salt Lake City Health Care System.](https://reader030.fdocuments.in/reader030/viewer/2022032802/56649e175503460f94b027fb/html5/thumbnails/5.jpg)
![Page 6: Simulacra & Simulation (& Health Care-Associated Infections) Michael Rubin, MD, PhD Section Chief, Epidemiology VA Salt Lake City Health Care System.](https://reader030.fdocuments.in/reader030/viewer/2022032802/56649e175503460f94b027fb/html5/thumbnails/6.jpg)
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
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Models in Healthcare Research
• Familiar models– Equation-based models• Compartmental models, Differential Equation models
S(t) R(t)I(t)βI(t) r
S I R
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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
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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
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Agent-Based ModelsS I R
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
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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
![Page 12: Simulacra & Simulation (& Health Care-Associated Infections) Michael Rubin, MD, PhD Section Chief, Epidemiology VA Salt Lake City Health Care System.](https://reader030.fdocuments.in/reader030/viewer/2022032802/56649e175503460f94b027fb/html5/thumbnails/12.jpg)
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
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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
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Model Components
• Patient• Room• Ward/ICU• Nurse• Physician• Network structure• Surveillance
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Transmission pathways
– Patient nurse patient– Patient physician patient– Patient environment nurse patient– Patient environment physician patient– Patient environment roommate– Patient environment subsequent occupant
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roomroom
patientpatientADMISSIONADMISSION
DISCHARGEDISCHARGE
COLONIZATION EVENT
colonizedcolonized
not colonizednot colonized
CLINICAL EVENTS
asymptomaticasymptomatic
symptomaticsymptomatic
off antibioticsoff antibiotics
on antibioticson antibiotics
node-colonization
node-colonization
de-colonizationde-colonization
unoccupiedunoccupied
occupiedoccupied
uncontaminateduncontaminated
contaminatedcontaminated
no isolationno isolation
contact isolationcontact isolation
nursenurse
physicianphysician
uncontaminateduncontaminated
contaminatedcontaminated
uncontaminateduncontaminated
contaminatedcontaminated
Agents and states
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Contact Networks
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Model animation
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• 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
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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
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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