Bryan C. P. Demianyk

Agent-Based Modeling of the Spread of Influenza-Like Illness in an Emergency Department: A Simulation Study

The objective of this paper was to develop an agent based modeling framework in order to simulate the spread of influenza virus infection on a layout based on a representative hospital emergency department in Winnipeg, Canada. In doing so, the study complements mathematical modeling techniques for disease spread, as well as modeling applications focused on the spread of antibiotic-resistant nosocomial infections in hospitals. Twenty different emergency department scenarios were simulated, with further simulation of four infection control strategies. The agent based modeling approach represents systems modeling, in which the emergency department was modeled as a collection of agents (patients and healthcare workers) and their individual characteristics, behaviors, and interactions. The framework was coded in C + + using Qt4 libraries running under the Linux operating system. A simple ordinary least squares (OLS) regression was used to analyze the data, in which the percentage of patients that be came infected in one day within the simulation was the dependent variable. The results suggest that within the given instance con text, patient-oriented infection control policies (alternate treatment streams, masking symptomatic patients) tend to have a larger effect than policies that target healthcare workers. The agent-based modeling framework is a flexible tool that can be made to reflect any given environment; it is also a decision support tool for practitioners and policymakers to assess the relative impact of infection control strategies. The framework illuminates scenarios worthy of further investigation, as well as counterintuitive findings.

Technologies to generate contact graphs for personal social networks

This paper presents three novel means of collecting and analyzing data to generate contact graphs of personal social networks. The means of collection include a web based service, an RFID system, and a network application running on a wireless sensor network. Data generated from networks of personal contact are demonstrated to be of utility in estimating the potential of the spread of a infection such as would be associated with the recent outbreak of H1N1 influenza.

Uncertainties inherent in RFID tracking systems in an emergency department

This paper presents an agent based modeling tool to assist in the deployment of RFID based tracking systems in healthcare facilities. The environment modeled here is an emergency department, with emphasis on patient tracking. The focus of the work is to quantify and assess the uncertainty and error associated with RFID tracking systems. The work extends the utility of RFID systems beyond asset and inventory control to patient tracking and highlights uncertainty as a critical issue in the data obtained via RFID tracking systems.

Improving Agent Based Models and Validation through Data Fusion

This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level.

A Distributed Mobile Application for Data Collection with Intelligent Agent Based Data Management Policy

This chapter presents a potential application area for SmartData (Tomko GJ, Kwan H, Borrett D. SmartData: The need, the goal, the challenge. Report, University of Toronto, Identify Privacy & Security Institute, 2012) research of importance in the near future. Technological and sociopolitical trends augur for development and adoption of a mobile distributed system for personal data collection and storage that incorporates the ideals of Privacy by Design (Tomko GJ, Kwan H, Borrett D. SmartData: The need, the goal, the challenge. Report, University of Toronto, Identify Privacy & Security Institute, 2012). Such a system will necessarily encompass a comprehensive interface which implements a complex data privacy, security, and sharing policy. This privacy management and sharing policy for distributed sensing participants represents a potential early embodiment for SmartData agents with unprecedented importance. Furthermore, distributed systems such as these form a convenient population of individuals embedded within the environment in order to exploit parallelism for crowd-sourced distributed learning. Such populations of participating users and their devices represent an intriguing opportunity to collaboratively develop a test-bed for the training and validation of SmartData agents directly within the target environment. Such embodiment and embeddedness within the 3D environment of the real-world forming a “mobile cloud” of Pervasive Internet devices is complementary to and converges with the vision of SmartData agents operating in virtual 3D online environments. A possible simulation test-bed for gaining insight into evolutionary dynamics in such a distributed learning context is discussed.

Work in progress — Developing educational opportunities in agent-based modeling

This paper outlines opportunities for student work in agent-based modeling, with reference to applications to community-level epidemic modeling, modeling patient waiting times in a hospital emergency departments, and modeling the spread of infection within a hospital. The applications demonstrate the educational opportunities inherent in agent-based modeling, which can address the educational and professional context calling graduate engineers to have a wider range of professional skills, including communication, teamwork, self-management, creativity, and awareness. Agent-based modeling applications lend themselves naturally to interdisciplinary exposure and professional skill development. Agent-based modeling is also supported by concepts in teaching and learning theory.