1. An Agent-Based Epidemic Model Brendan Greenley Period 3

2. Why An Epidemic Model? Epidemics have been responsible for great losses of like and have acted as a population control (Black Plague, Spanish Influenza) Epidemics are still a cause of concern today and in the future (SARS, Avian Flu) Analyzing certain characteristics of an epidemic outbreak or response can help shape plans in case of a real outbreak.

3. Why Agent-Based? Originally tried System Dynamics Agent-Based Modeling makes more sense –Individual behavior differs and can greatly affect the course of an epidemic outbreak –A user can observe an agent over time –Children can inherit values from two parents –Continuous visual representation of population

4. Scope of project Population/environment bounds dictated by computer resources ~10,000 agents maximum All about maintaining a population balance Unrealistic assumptions are made –Mating –Interactions –Movement

5. Up, up, and away…

6. Extinction

7. NetLogo Still using NetLogo Programming language (Northwestern) Allows for System Dynamics & Agent Based Modeling Crossplatform support –Windows, *Nix, Mac Depends on Java Free!

8. Procedure Agent’s To-Do List: –Move in a random direction –Check for potential mate –Check for possible exposure to disease –Age++ Starting populations, immunity, and original % infected are set by user

9. BehaviorSpace Allows me to export data to Excel Can incrementally increase specified values as the model runs Useful for post-run data analysis

10. Timeline First Quarter –Used System Dynamics Modeling Second Quarter –Late Dec: Switched to Agent-Based Modeling –Jan: Implemented susceptibility distribution Implemented more realistic mating/children characteristics Learned how to use BehaviorSpace

11. Timeline (Continued) February –Implement quarantine –Have agent’s epidemic state affect behavior –Create children a bit after mating March –Possibly allow for drugs/vaccines to counter disease –As time increases, have agents use their past experience with epidemics to make smarter decisions (increase the amount they limit contact with others when a disease is widespread, etc.) April/May/June –Allow myself extra time, as the previously mentioned tasks may take longer than expected –Use BehaviorSpace to collect data and analyze multiple situations –Work on interpreting the data for my final project presentation/poster/etc.

12. Project Evolution System Dynamics -> Agent Based Short-term -> Long-term Predetermined equations -> more complex individual agent decisions Graphs highlight changes