A Dynamic Model of the Opioid Drug Epidemic with Implications for Policy

Background: The U.S. opioid epidemic has caused substantial harm for over 20 years. Policy interventions have had limited impact and sometimes backfired. Experts recommend a systems modeling approach to address the complexities of opioid policymaking. Objectives: Develop a system dynamics simulation model that reflects the complexities and can anticipate intended and unintended intervention effects. Methods: The model was developed from literature review and data gathering. Its outputs, starting 1990, were compared against 12 historical time series. Illustrative interventions were simulated for 2020-2030: reducing prescription dosage by 20%, cutting diversion by 30%, increasing addiction treatment from 45% to 65%, and increasing lay naloxone use from 4% to 20%. Sensitivity testing was performed to determine effects of uncertainties. No human subjects were studied. Results: The model fits historical data well with error percentage averaging 9% across 201 data points. Interventions to reduce dosage and diversion reduce the number of persons with opioid use disorder (PWOUD) by 11% and 16%, respectively, but each reduces overdoses by only 1%. Boosting treatment reduces overdoses by 3% but increases PWOUD by 1%. Expanding naloxone reduces overdose deaths by 12% but increases PWOUD by 2% and overdoses by 3%. Combining all four interventions reduces PWOUD by 24%, overdoses by 4%, and deaths by 18%. Uncertainties may affect these numerical results, but policy findings are unchanged.Conclusion: No single intervention significantly reduces both PWOUD and overdose deaths, but a combination strategy can do so. Entering the 2020s, only protective measures like naloxone expansion could significantly reduce overdose deaths

Creating Clinically Useful \u3ci\u3eIn Silico\u3c/i\u3e Models of Intracranial Pressure Dynamics

To create clinically useful computer simulation models of intracranial pressure (ICP) dynamics by using prospective clinical data to estimate subject-specific physiologic parameters

A Hybrid Simulation Model for Studying Acute Inflammatory Response

The modeling of complex biological systems presents a significant challenge. Central to this challenge is striking a balance between the degree of abstraction required to facilitate analysis and understanding, and the degree of comprehensiveness required for fidelity of the model to its reference-system. It is likely necessary to utilize multiple modeling methods in order to achieve this balance. Our research created a hybrid simulation model by melding an agent-based model of acute local infection with a system dynamics model that reflects key systemic properties. The agent based model was originally developed to simulate global inflammation in response to injury or infection, and has been used to simulate clinical drug trials. The long term objective is to develop models than can be scaled up to represent organ and system level phenomena such as multiple organ failure associated with severe sepsis. The work described in this paper is an initial proof of concept of the ability to combine these two modeling methods into a hybrid model, the type of which will almost certainly be needed to accomplish the ultimate objective of comprehensive in silico research platforms

A Systems Approach to Stress, Stressors and Resilience in Humans

The paper focuses on the biology of stress and resilience and their biomarkers in humans from the system science perspective. A stressor pushes the physiological system away from its baseline state towards a lower utility state. The physiological system may return towards the original state in one attractor basin but may be shifted to a state in another, lower utility attractor basin. While some physiological changes induced by stressors may benefit health, there is often a chronic wear and tear cost due to implementing changes to enable the return of the system to its baseline state and maintain itself in the high utility baseline attractor basin following repeated perturbations. This cost, also called allostatic load, is the utility reduction associated with both a change in state and with alterations in the attractor basin that affect system responses following future perturbations. This added cost can increase the time course of the return to baseline or the likelihood of moving into a different attractor basin following a perturbation. Opposite to this is the system’s resilience which influences its ability to return to the high utility attractor basin following a perturbation by increasing the likelihood and/or speed of returning to the baseline state following a stressor. This review paper is a qualitative systematic review; it covers areas most relevant for moving the stress and resilience field forward from a more quantitative and neuroscientific perspective

A Computer Model of Intracranial Pressure Dynamics During Traumatic Brain Injury that Explicitly Models Fluid Flows and Volumes

This report documents a computer model of intracranial pressure (ICP) dynamics that is used to evaluate clinical treatment options for elevated ICP during traumatic brain injury (TBI). The model uses fluid volumes as primary state variables and explicitly models fluid flows as well as the resistance, compliance, and pressure associated with each of the compartments (arteries and arterioles, capillary bed, veins, venous sinus, ventricles, and brain parenchyma). The model has been tested to assure that it reproduces a correct physiologic response to intra-and extra-parenchymal hemorrhage and edema, and to therapies directed at reducing ICP such as cerebral spinal fluid drainage, mannitol administration, head elevation, and mild hyperventilation. The model is able to replicate observed clinical behavior in many cases, including elevated ICP associated with severe cerebral edema, subdural hematoma, and cerebrospinal fluid blockage. The model also successfully reproduces tne cerebrovascular regulatory mechanisms that are activated during TBI in response to various abnormalities such as high or low systemic blood pressure. We conclude that incorporating fluid volumes and flows into a model of lCP dynamics significantly improved its clinical utility. Additional improvements are anticipated (or wil1 accrue or will result) as the specific mechanisms that modify cerebral compliance and autoregulation during TBI and elevated ICP are further delineated

Key Data Gaps for Understanding Trends in Prescription Opioid Analgesic Abuse and Diversion Among Chronic Pain Patients and Nonmedical Users

Population dynamics of medical and nonmedical prescription opioid usage and adverse outcomes were modeled. Critical parameter values were determined by their amount of influence on model behavior. Results suggest that closing these data gaps would help researchers to better identify ways to reduce the risk of adverse outcomes

Metamodeling Aspects of Model Conceptualization

This paper suggests a technique for improving the conceptualization of models. The key aspect of this technique is to set aside the main model for a period of time during the model conceptualization process and focus on building a watchdog submodel. The primary purpose of the watchdog submodel is to assure that the main model remains internally consistent during its operation. In the experience of this author, such a submodel can help to identify model conceptualization errors and to determine if a model is sufficiently robust to adequately replicate the behavior of the system being modeled. This is not a research paper. Rather, it is a discussion paper intended to stimulate thought and to encourage dialogue among modelers regarding the challenging task of model conceptualization. The ideas presented herein have not been fully tested by this author through appropriate research; they are merely concepts that appear to have potential within the modeling field

The Judging Process for SyM Bowl: A High School System Dynamics Modeling Competition

This “paper” describes the judging process used to determine the winners in SymBowl, a high school system dynamics modeling competition held in Portland, Oregon the past three years. SymBowl was created by Ed Gallaher, a medical researcher at the Portland VA Hospital and Associate Professor at Oregon Health Sciences University. The judging criteria and judging process were developed by Wakeland, who has served as the judging coordinating for past three years, overseeing the process, compiling results, etc. Wakeland is an Adjunct Professor of System Science at Portland State University where he teaches graduate-level modeling and simulation classes

Microcomputer MRP in Three Months: Photon Kinetics

Information about the company Photon Kinetics, a small, privately-held manufacturer of fiber optics test equipment, located in Beaverton, Oregon

Measuring the Accuracy of Predictions from Patient-Specific Models of Intracranial Pressure Dynamics

Objective: Determine the prediction capability of a computer model of Intracranial pressure (ICP) dynamics