Agent-Based Model

Disease Spread

Imagine you want to simulate how a pathogen spreads within a population over a certain period of time. Agents influence each other — they infect one another when they meet by chance. States constantly change from "susceptible" to "infected" to "recovered." The following step-by-step guide shows you how to build your first agent-based model in just a few steps!

1. Create a new model

✔︎ Create a new model and name it "Disease Spread"

CreateModel

2. Create agent type "Person"

✔︎ Add an agent and name it "Person"

✔︎ Resize the primitive's window on the canvas to fit the next primitives inside

AddAgent

3. Create state "susceptible"

✔︎ Add a state to the "Person" agent and name it "susceptible"

✔︎ At the start time, this state is correct, so set the parameter to true

✔︎ Holding time: 0

CreateState

4. Create state "infected"

✔︎ Add a state to the "Person" agent and name it "infected"

✔︎ Connect the "susceptible" state to the "infected" state

✔︎ At the start time, this state is not [susceptible]. You can use the value from the connected "susceptible" primitive

✔︎ Holding time: 0

CreateState

5. Create state "recovered"

✔︎ Add a state to the "Person" agent and name it "recovered"

✔︎ At the start time, this state is false, so set the parameter to false

✔︎ Holding time: 0

CreateState

6. Create transition "Pathogen"

✔︎ Add a transition to the "Person" agent and name it "Pathogen"

✔︎ Connect the "susceptible" state to the "infected" state via this transition

✔︎ The trigger is a "Condition" caused by contact with other agents after 5 years

✔︎ Set value to Self.Index()=1 and Years=5

✔︎ Recalculate value at every time step

CreateTransition

7. Create transition "Recovery"

✔︎ Add a transition to the "Person" agent and name it "Recovery"

✔︎ Connect the "infected" state to the "recovered" state via this transition

✔︎ The trigger is "Probability". The assumption is that 9% of infected individuals recover per time step.

✔︎ Set value to 0.09

✔︎ Recalculate value at every time step

CreateTransition

8. Create transition "Transmission"

✔︎ Add a transition to the "Person" agent and name it "Transmission"

✔︎ Connect the "susceptible" state to the "infected" state via this transition

✔︎ The trigger is "Probability". The probability of infection depends on the population, which we will model later.

CreateTransition

9. Create action "Catch Pathogen"

✔︎ Add an action to the "Person" agent and name it "Catch Pathogen"

✔︎ Connect the "susceptible" state to this action

✔︎ The trigger is a "Condition" that also depends on the population we will model next.

CreateAction

10. Create population

✔︎ Add a population that applies the agent "Person" behavior to the entire population

✔︎ Set values as follows:

Population size: 100
Geo width: 200
Geo height: 200
Geo placement: "Random"
Network type: "none"

✔︎ Set population as output parameter

CreatePopulation

11. Equations for action "Catch Pathogen"

✔︎ Connect the population to the "Catch Pathogen" action in the "Person" agent

✔︎ Set action function to Self.moveTowards([Population].FindState([infected]).FindNearest(Self), -0.5)

✔︎ Set condition to [susceptible] and [Population].FindState([infected]).count()> 0

CreateEquations

12. Equations for transition "Transmission"

✔︎ Connect the population to the "Transmission" transition in the "Person" agent

✔︎ Set value to:

infectors <- [Population].FindState([infected]).FindNearby(Self, 25)
probInfect <- min(1, infectors.Map(1/(distance(x, Self))^.75))
1 - Product(Join(1, 1 - probInfect))

✔︎ Recalculate value at every time step

CreateEquations