Written By:

Adam Roux

Published On:

February 27, 2019

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    CLSG’s Participatory Simulations in Public Policy

    At the Center for Leadership Simulation and Gaming (CLSG), we use simulations and experimental methods to inform policy teaching, research, and engagements. Here, we provide a brief introduction to a particularly innovative CLSG tool: the Participatory Simulation in Public Policy (PSPPs).


    Noah Myung[1], Andy Ortiz, and Adam Roux

    Center for Leadership Simulation and Gaming, University of Virginia

    February 18, 2019

    As social scientists interested in public policy, we utilize various tools to better understand the complex world. At the Center for Leadership Simulation and Gaming (CLSG), we use simulations and experimental methods to inform policy teaching, research, and engagements. Here, we provide a brief introduction to a particularly innovative CLSG tool: the Participatory Simulation in Public Policy (PSPPs).

    Participatory simulations are immersive, experiential learning tools that provide a bridge between classroom learning and real-world scenarios. They are ideal for future civil servants who want to hone skills like leadership, quantitative methods, critical analysis, and communication. Our PSPPs emphasize topics that require participants to make decisions together while facing real-world constraints, helping them prepare for a career involving group decision-making. Our controlled environments provide public policy students and professionals with opportunities to practice utilizing the same skills they will use in the real world.

    Our PSPPs have three goals. First, participants can better understand the complex issues we present (pandemics, refugees, health care systems, etc). Second, participants can practice thinking analytically in the public policy arena using the limited information and tools at hand. Third, participants must find consensus and work with others. Thus, simulations underscore the importance of decision-making processes within and between groups.

    Our simulations are designed to produce realistic consequences based on the choices participants make, which requires sophisticated mathematical modeling such as System Dynamics Modeling, Agent-Based Modeling, or Discrete Event Simulation. On top of these computational engines, all of our PSPPs share three characteristics:

    1. A Public Policy Focus

    Our simulations are designed to teach participants about potential outcomes of various public policies, as well as opportunities and challenges inherent in policy-making in groups with diverse stakeholders.

    1. Participatory Nature

    The behavior of participants impacts the process and the execution of the simulation. In our PSPPs, we ask participants to take on a specific role (prime minister, etc.) as they make policy decisions with their teams and the other teams in the game. Roles and teams are assigned different—and sometimes conflicting—information, objectives, and abilities. Participants must communicate, cooperate, compete, and learn to make tradeoffs. Simulation outcomes depend on how, where, and when individuals work alone and work together.

    1. Computer-based

    We run simulations on laptops and mobiles devices. Advantages include:

    1. We can send participants alerts on their devices regarding various interactive, situation-based tasks and information.
    2. We can easily change the parameters or difficulty of a game “on the fly.”
    3. We can calculate several complex computations from our models simultaneously and quickly.
    4. Conducting our simulations through our server and participants’ web browsers lowers setup costs and increases our scalability.

    As an example, consider a simplified version of our Pandemic Simulation. A video of our simulation event can be seen here. The Pandemic Simulation is a System Dynamics simulation that was built as an extension of the well-established SEIR Model (Figure 1).


    Figure 1. SEIR Model

    The SEIR model starts with a group of the population who are ‘Susceptible’ to a particular disease. A portion of this group will be exposed to the disease, and a subset will become ‘Infectious.’ Subsets of the ‘Infectious’ group will then either recover or die. The rate at which the population moves from one stage to the next will change according to the policies the participants implement. For example, what type of antivirals have been researched and distributed? When are these antivirals available? Should a government close international borders, schools, or sporting events to implement social distancing? If so, for how long? These considerations of ‘what, when, and who’ will impact how much of the infectious population moves to the ‘Recovered’ or ‘Deceased’ groups. In other words, there is a stock of population in each group (Exposed, Infectious, etc.), and various public policies will impact the flow from one group to the next over time.

    The policy decisions made by the participants directly and indirectly impact the outcome of the SEIR model, but these decisions will also impact other variables in the simulation: GDP, taxation, education, etc. If a participant wishes to distribute antiviral medication, would they tax the population? What projects are prioritized? How does an increase or decrease in the infectious population affect economic well-being? How would a tourist-based economy react if a neighboring country decides to close its borders? Throughout the process, participants learn about a wide range of topics, including epidemiology, crisis management, cost-benefit analysis, leadership, teamwork, and communication.

    Participants in our simulation may never be called upon to handle the sudden outbreak of a lethal communicable disease, but they will definitely encounter situations where they will be asked to make decisions under pressure, with limited information and diverse stakeholders. Our PSPPs help them develop the multidisciplinary skills they will need to be ready.


    We would like to thank Dan Player and Jay Shimshack for their valuable comments.

    [1] Corresponding Author. Email: noah.myung@virginia.edu Phone: 434-243-3731