SIR_DES.nlogo

globals [
number ;;number for people in queue
susceptibles_  ;the number of susceptible people
infecteds_ ;the number of infected people
recovereds_  ;the number of recovered people
inf ;;number of infected in this period
  ]

turtles-own[
status ;1 for susceptible, 2 for infected, 3 for recovered
mynumber  ;;number in queue
]

to setup
ca
reset-ticks
crt suscetibles [ht set status 1 set number number + 1 set mynumber number]
ask one-of turtles [set status 2]
change-color

end


to go

;;stop if no agent is infected
if ticks > 10 and count turtles with [status = 2] = 0[stop]

change-color


;;each agent in the susceptible queue has a probability to get infected
if count turtles with [status = 1] > 0[
ask turtles with [status = 1][
 if random-float 1 < (InfectionRate * dt * infecteds_)[set status 2]

]]

;;each agent in the infected queue has a probability to recover
if count turtles with [status = 2] > 0[
ask turtles with [status = 2][
  if random-float 1 < (RecoveryRate * dt)[set status 3]

  ]]

;;update the number of each type of agents
  set susceptibles_ count turtles with [status = 1]
  set infecteds_ count turtles with [status = 2]
  set recovereds_ count turtles with [status = 3]

  change-color

  abm-do-plot
  tick
end


to change-color
;;susceptibles are green, infecteds are red, recovereds are blue
ask turtles[ if status = 1[set color green move-to patch -10 0 st]
             if status = 2[set color red move-to patch 0 0 st]
             if status = 3[set color blue move-to patch 10 0 st]]
end


to abm-do-plot
;;plot the numbers of susceptibles, infecteds, recovereds over time
  if plot-pen-exists? "susceptibles" [
    set-current-plot-pen "susceptibles"
    plotxy ticks susceptibles_
  ]
  if plot-pen-exists? "infecteds" [
    set-current-plot-pen "infecteds"
    plotxy ticks infecteds_
  ]
  if plot-pen-exists? "recovereds" [
    set-current-plot-pen "recovereds"
    plotxy ticks recovereds_
  ]
end
@#$#@#$#@
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"" ""
PENS
"susceptibles" 1.0 0 -13840069 true "" ""
"infecteds" 1.0 0 -2674135 true "" ""
"recovereds" 1.0 0 -13345367 true "" ""

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@#$#@#$#@
## WHAT IS IT?

This is a Discrete Event Simulation (DES) model that simulates the SIR spread of disease model. SIR stands for: susceptibles (S), infectious (I) and recovered (R).

## HOW IT WORKS

A Discrete Event Simulation model has three abstract types of objects:
1) servers, 2) customers, 3) queues
Servers are the processes of getting infected and recovering. The durations people stay in the servers represent the process of getting infected and getting recovered. Customers are susceptible people to be infected, and infected people waiting to recover. There are two queues in this model. As susceptible agents are created, queues for infection are formed while people are waiting to be infected. On the other hand, as people get infected, they form a second queue waiting to recover. The During each iteration (dt), each agent in queue has a probability equals (Infraction Rate * number of infected * dt) to get infected. Each infected agent has a probability to recover = RecoveryRate. After agents recover, they enter the sink of recovered people.

The whole process is illustrated in the figure below.

![alt text](SIR_DES.jpg)

## HOW TO USE IT

1. Use the sliders to set parameters in the model.

2. Press Setup to create susceptible agents.

3. Press Go to run the simulation.


## RELATED MODELS

I have built SIR model using three different approaches, including Agent-Based Modeling, Cellular Automata, and Discrete Event Simulation. Also, there is System Dynamics model of SIR available from Shiflet et al. (2014).

The models are posted on my blog: http://geospatialcss.blogspot.com/

## CREDITS AND REFERENCES

Shiflet, A. B., & Shiflet, G. W. (2014). Introduction to computational science: modeling and simulation for the sciences. Princeton University Press.
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NetLogo 6.1.0
@#$#@#$#@
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<experiments>
  <experiment name="experiment" repetitions="10" runMetricsEveryStep="true">
    <setup>setup</setup>
    <go>go</go>
    <exitCondition>ticks &gt; 10 and count turtles with [status = 2] = 0</exitCondition>
    <metric>susceptibles_</metric>
    <metric>infecteds_</metric>
    <metric>recovereds_</metric>
    <enumeratedValueSet variable="InfectionRate">
      <value value="0.002"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="dt">
      <value value="0.001"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="suscetibles">
      <value value="2500"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="RecoveryRate">
      <value value="0.5"/>
    </enumeratedValueSet>
  </experiment>
</experiments>
@#$#@#$#@
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