Project 3: Zombie Invasion

A Zombie Santa Claus.
Zombie Santa Claus.

1. Modeling the Unthinkable: Spatial Dynamics of Zombie Epidemics

In the realm of complex systems modeling, epidemic spread represents a fascinating challenge for computational scientists. While traditional epidemiological models focus on human diseases, our project explores a more extreme scenario: a zombie outbreak. This simulation moves beyond academic abstraction, challenging you to develop a rigorous computational model that captures the nonlinear dynamics of infectious transformation. The zombie apocalypse serves as a compelling proxy for understanding critical aspects of disease transmission, population dynamics, and spatial interaction. By creating a sophisticated agent-based model, you will:

  • Translate theoretical epidemiological concepts into computational logic
  • Explore how movement constraints and infection parameters influence systemic behavior
  • Develop skills in computational modeling, data analysis, and scientific visualization

This project is not just about zombies – it’s about understanding complex adaptive systems, developing computational thinking, and bridging theoretical models with computational implementation.

Research Goal:

Develop a computational framework that reveals emergent epidemic behaviors through systematic parameter exploration.

2. Learning Objectives

  • Implement a spatial agent-based modeling using techniques learned in class
  • Develop complex system simulation skills by creating a new model based on a given scenario
  • Practice computational modeling and data visualization
  • Analyze interaction between movement and infection dynamics in the build model

3. Problem Overview

In this computational modeling project, you will develop an agent-based model to simulate zombie epidemic dynamics. The core challenge is understanding how local interaction rules and movement parameters generate population-level infection outcomes. It is expected that your model is well documented, and that it it also realistic (to a certain amount, right?).

3.1 Model Behavior Expectations:

It is expected that your model accounts for the following behaviors:

  • Agents exist on a spatial grid with defined movement capabilities
  • Healthy agents can be transformed into zombies through direct contact
  • Zombies have distinct movement characteristics:
    • Slower movement speed compared to healthy agents
    • Limited survival time without consuming human hosts
    • Probabilistic infection transmission

Therefore, you will need to create two new parameters: one for controlling the movement speed of infected agents, and another one for the death rate of the infected agents. Feel free to include other behaviors that you find interesting to be explored.

3.2 Key Modeling Questions:

You will be trying to answer the following questions as you report your results:

  • Does limiting zombie’s movement affect infection spread?
  • What factors reduce or increase outbreak severity? Consider outbreak severity the time it takes for the zombie outbreak to kill everyone in your model.
  • What would happen if healthy agents were aware of the promiximity of zombies and avoided them?

3.3 Computational Approach:

The model will simulate agent interactions, tracking:

  • Individual agent states (healthy/infected)
  • Spatial movement patterns
  • Infection transmission events
  • Population transformation over time

For that,

  1. Develop a formal description of the zombie invasion model
  2. Define key parameters:
    • Zombie movement speed
    • Zombie death rate from starvation (can zombies feed themselves from each other?)
    • Infection transmission probability
    • Agent movement behavior
  3. Specify initial population characteristics
  4. Describe agent interaction rules

In your computational model, you might want to

  1. Implement agent classes:
    • Healthy agents
    • Zombie agents
  2. Code interaction rules for agent movement and infection
  3. Develop outcome tracking mechanisms (monitors and graphics?)

For the experimental design perspective, you might want to

  • Vary zombie movement speed (0.5-2.0)
  • Vary zombie death rate (0.01-0.1)
  • Run multiple simulation iterations, collecting data on:
    • Total infected agents
    • Death rate per time step
    • Population survival time

From the standpoint of analysis and visualization, you might want to

  • Generate line plots showing:
    • Infection progression
    • Population dynamics
    • Relationship between parameters and outbreak severity
  • Calculate statistical summaries
  • Interpret simulation results

Our initial starting point is the model SI created in class, accessible by clicking in this link.

Download the code in your computer, and make sure it runs without errors.

Perform batch runs to answer the key modeling questions, and plot the results. Write your discussion in the Info tab.

Submission

Submit your Netlogo code on Moodle until Tuesday, December 3. Document well your code and report the answers for all the steps in the Info tab.

Note that I didn’t give you information about how many times to run or how to implement some of the specifics of the model. Feel free to come up with your solution where the assignment is not clear.

Grading Rubric

This project will be graded the following way: 100 pts total

The criteria to get a good grade will be based on:

  • 20pts: Model complexity (not too complex, not too simple) and realism (does it make sense?)
  • 20pts: Code quality and documentation
  • 10pts: Experimental design rigor (batch run designs)
  • 10pts: Data visualization (graphs and outputs given by the batch runs)
  • 20pts: Analytical depth (interpretation of your own results)
  • 20pts: Writing clarity

Reasons for losing points:

  • -100pts: Model doesn’t run
  • -20pts: Model doesn’t have all features requested in the assignment
  • -100pts: Model is exactly the same as other people’s models