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DiseaseDynamicsSD_InsightMaker.pdf

10/6/2019 Disease Dynamics (SD) | Insight Maker

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This tutorial describes how to construct a model of an infectious disease.This tutorial describes how to construct a model of an infectious disease.

Before starting the tutorial, make sure you have familiarized yourself withBefore starting the tutorial, make sure you have familiarized yourself with

how to how to create primitivescreate primitives and and run modelsrun models..

Table of Contents Insight Maker Guide

Getting Help

Features

Types of Modeling

System Dynamics

Agent Based Modeling

Collaborate and Share

Free and Open Source

Tutorials

Disease Dynamics (SD)

Disease Dynamics (ABM)

Predator-Prey Interactions (SD)

Manual

Model Diagramming

Ghosting

Keyboard Shortcuts

Equations and Formulae

Built-In Functions

Advanced Equations

Types of Primitives

Stocks

Flows

Variables

Links

Converters

States

Transitions

Actions

Agent Populations

Running a Model

Model Verification

Constraints

Units

Storytelling

Agent Geography

Spatial Geography

Network Geography

Sensitivity Testing

Optimization

Vectors

Macros

Model Scripting

User login

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Disease Dynamics (SD)

Create a new Create a new StockStock named named HealthyHealthy ..11

Create a new Create a new StockStock named named InfectedInfected ..22

The model diagram should now look something like this:The model diagram should now look something like this:33

Create a new Create a new FlowFlow going from the primitive going from the primitive HealthyHealthy to the primitive to the primitive InfectedInfected . Name. Name

that flow that flow InfectionInfection ..

44

The model diagram should now look something like this:The model diagram should now look something like this:

The basic model structure has been laid-out, we can startThe basic model structure has been laid-out, we can start

to define parameter values and equations. We'll start withto define parameter values and equations. We'll start with

a very simple model containing a population of 100a very simple model containing a population of 100

people and where 2 people becoming sick each year.people and where 2 people becoming sick each year.

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Change the Change the Initial ValueInitial Value of the primitive of the primitive HealthyHealthy to to 100100 ..66

Change the Change the Flow RateFlow Rate of the primitive of the primitive InfectionInfection to to 22 ..77

Run the model. Here are sample results:Run the model. Here are sample results:

The results are as we would expect. However this is not aThe results are as we would expect. However this is not a

model of an infectious disease as the infection rate doesmodel of an infectious disease as the infection rate does

not depend on the presence of infected individuals. Let'snot depend on the presence of infected individuals. Let's

change the infection rate so it depends on the contactchange the infection rate so it depends on the contact

rates between sick and healthy people.rates between sick and healthy people.

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Change the Change the Flow RateFlow Rate of the primitive of the primitive InfectionInfection to to 0.006*[Healthy]*[Infected]0.006*[Healthy]*[Infected] ..99

Run the model. Here are sample results:Run the model. Here are sample results:

That's strange. No one ever gets sick. Why is that? It turnsThat's strange. No one ever gets sick. Why is that? It turns

out it is because we start the simulation with no infectedout it is because we start the simulation with no infected

people in the model. Since we're modeling an infectiouspeople in the model. Since we're modeling an infectious

disease, this means there is no one to start the epidemic!disease, this means there is no one to start the epidemic!

Let's change that we'll add a single infected person to getLet's change that we'll add a single infected person to get

the epidemic started.the epidemic started.

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Change the Change the Initial ValueInitial Value of the primitive of the primitive InfectedInfected to to 11 ..1111

Run the model. Here are sample results:Run the model. Here are sample results:

That looks about right. Before moving on, let's spend aThat looks about right. Before moving on, let's spend a

moment to improve our model structure. Right now if wemoment to improve our model structure. Right now if we

wanted to edit the infection rate, we would have to digwanted to edit the infection rate, we would have to dig

down in the equations to find the right number. Let'sdown in the equations to find the right number. Let's

make our model more modular, without changing anymake our model more modular, without changing any

results, by separating the infection rate into its ownresults, by separating the infection rate into its own

variable.variable.

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Create a new Create a new VariableVariable named named Infection RateInfection Rate ..1313

Create a new Create a new LinkLink going from the primitive going from the primitive Infection RateInfection Rate to the primitive to the primitive InfectionInfection ..1414

The model diagram should now look something like this:The model diagram should now look something like this:1515

Change the Change the EquationEquation of the primitive of the primitive Infection RateInfection Rate to to 0.0060.006 ..1616

Change the Change the Flow RateFlow Rate of the primitive of the primitive InfectionInfection to to

[Infection Rate]*[Healthy]*[Infected][Infection Rate]*[Healthy]*[Infected] ..

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Run the model. Here are sample results:Run the model. Here are sample results:1818

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We can hide the display of the infection rate primitive byWe can hide the display of the infection rate primitive by

configuring the display.configuring the display.

Run the model. Here are sample results:Run the model. Here are sample results:

Now that we have our basic model working, let's extend itNow that we have our basic model working, let's extend it

by adding the phenomena of people recovering from theby adding the phenomena of people recovering from the

disease. We'll model something like the Chicken Poxdisease. We'll model something like the Chicken Pox

where people become immune to the disease after theywhere people become immune to the disease after they

recover.recover.

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Create a new Create a new StockStock named named ImmuneImmune ..2020

Create a new Create a new FlowFlow going from the primitive going from the primitive InfectedInfected to the primitive to the primitive ImmuneImmune . Name. Name

that flow that flow RecoveryRecovery ..

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Create a new Create a new VariableVariable named named Recovery RateRecovery Rate ..2222

Create a new Create a new LinkLink going from the primitive going from the primitive Recovery RateRecovery Rate to the primitive to the primitive

RecoveryRecovery ..

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‹ Tutorials up Disease Dynamics (ABM) ›

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The model diagram should now look something like this:The model diagram should now look something like this:2424

Change the Change the EquationEquation of the primitive of the primitive Recovery RateRecovery Rate to to 0.10.1 ..2525

Change the Change the Flow RateFlow Rate of the primitive of the primitive RecoveryRecovery to to [Recovery Rate]*[Infected][Recovery Rate]*[Infected] ..2626

Change the Change the EquationEquation of the primitive of the primitive Infection RateInfection Rate to to 0.0080.008 ..2727

Run the model. Here are sample results:Run the model. Here are sample results:

Fantastic! Now we have a working disease simulation. YouFantastic! Now we have a working disease simulation. You

can experiment with different population sizes, infectioncan experiment with different population sizes, infection

rates and recovery rates to see how the results change.rates and recovery rates to see how the results change.

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