globals [
  max-infected
  mobilize-immune
]

turtles-own[
  infected?
  immune?
  social-distancing?
  vaccinated?
  dead?
]

to setup
  clear-all
  setup-world
  setup-turtles
  setup-infected
  setup-social-distancing
  setup-vaccination-rate
  set mobilize-immune true
  set max-infected (count turtles with [infected?])
  reset-ticks
end

to setup-world ;; determine the world
  ask patches [
    set pcolor brown + 4
  ]
end

to setup-turtles ;; setup the agents "people" in the simulation
  create-turtles population [
    set color sky
    set shape "person"
    set size 2
    set infected? false
    set immune? false
    set social-distancing? false
    set vaccinated? false
    set dead? false
    setxy random-pxcor random-pycor
  ]
end

to setup-infected ;; to determine the infected people at the beginnging to infect other people; infected people are colored red
  ask n-of infected-people turtles [
   set color red
   set infected? true
  ]
end

to setup-social-distancing ;; to determine the people who operate social distancing with the slider
  ask n-of social-distancing turtles[
  set social-distancing? true
  ]
end

to setup-vaccination-rate ;; to determine the vaccination rate with the help of the slider; to differentiate the vaccinated people from the unvaccinated people, vaccinated people are colored green
  ask n-of (vaccination-rate * population) turtles [
    set color green
    set vaccinated? true
  ]
end

to go
  if (count turtles with [infected?] = 0)
  or (count turtles with [infected?] = population)
  [stop] ;;stop if everyone or noone is infected
  infect-vac
  infect-unvac
  infect-vac-mask
  infect-unvac-mask
  dead
  recover-infected
  recolor-vac
  recolor-unvac
  move
  calculate-max-infected
  tick
end


to infect-vac ;; infection of other vaccinated people; a person can be infected when another infected person (red) is in the neare and not in quarantine; the probability of infection of vaccinated people can be determend with the slider
  if (masks = false) [
  ask turtles with [vaccinated?][
    let infected-neighbors (count other turtles with [(color != red) and (color != orange)]  in-radius 1 * (1 - quarantine-rate)) ;; quarantine.effort, porpability that infected people are in quarantine and cannot infect others.
    if (random-float 1 <  1 - (((1 - infection-risk-vac) ^ infected-neighbors)) and not immune?) ;; immunized people cannto be infected
    [set infected? true]
  ]
  ]
end

to infect-unvac ;; infection of other unvaccinated people; a person can be infected when another infected person (red) is in the neare and not in quarantine; the probability of infection of unvaccinated people can be determend with the slider
  if (masks = false) [
  ask turtles with [vaccinated? = false][
    let infected-neighbors (count other turtles with [(color != red) and (color != orange)] in-radius 1 * (1 - quarantine-rate)) ;;
    if (random-float 1 <  1 - (((1 - infection-risk-unvac) ^ infected-neighbors)) and not immune?)
    [set infected? true]
  ]
  ]
end

to infect-vac-mask ;; infection of vaccinated people if the people are wearing masks
  if (masks = true) [
  ask turtles with [vaccinated?][
    let infected-neighbors (count other turtles with [(color != red) and (color != orange)] in-radius 1 * (1 - quarantine-rate))
    if (random-float 1 <  1 - (((1 - infection-risk-vac * 0.004) ^ infected-neighbors)) and not immune?)
    [set infected? true]
  ]
  ]
end

to infect-unvac-mask ;; infection of unvaccinated people if the people are wearing masks
  if (masks = true) [
  ask turtles with [vaccinated? = false][
    let infected-neighbors (count other turtles with [(color != red) and (color != orange)] in-radius 1 * (1 - quarantine-rate))
    if (random-float 1 <  1 - (((1 - infection-risk-unvac * 0.004) ^ infected-neighbors)) and not immune?)
    [set infected? true]
  ]
  ]
end

to recolor-vac ;; infected and vaccinated people turnn orange
  ask turtles with [infected?][
  if (vaccinated? = true)
  [ set color orange]
  ]
end

to recolor-unvac ;; infected and unvaccinated people turn red to differentiate from the vaccinated people
  ask turtles with [infected?][
  if (vaccinated? = false)
  [ set color red]
  ]
end


to move ;; the people move random through the environment
  ask turtles
  [
    if (social-distancing? = false)
    [
      right random 360 ;; get a new random position if they are not doing social distancing
      forward random-normal mobility 0.01]
    ifelse mobilize-immune
    [if (social-distancing? = true and immune? = true)
      [set social-distancing? false]]
      [if (social-distancing? = true and immune? = true)
      [set social-distancing?  true]
    ]
    ]
end


to recover-infected ;; infected people become immun after a certain recovery time
  ask turtles with [infected?]
  [
    if random-float 1 < recovery-time ;; defines the recovery time and can be changed by the slider
    [
      set infected? false
      ifelse immunity-possibility
      [
        set immune? true
        set color gray ;; immunized people turn grey
      ]
      [
        set color sky
      ]
    ]
  ]
end

to-report prop-infected ;;; defines the propotion of the population, that is or was infected
  report (count turtles with [infected?] / count turtles)
end

to-report total-infections
  report (count turtles with [(infected?) or (immune?) or (dead?)])
end


to dead ;; simulates the death by Covid-19
  ask turtles with [infected?]
  [if (random-float 1000 < (mortality-rate-in%))
      [ set dead? true
      set shape "x"
      set color black
      set social-distancing? true]
    ]
end

to-report inf-vac-people
  report (count turtles with [(infected?) or (immune?) or (dead?) and (vaccinated?)])
end

to-report prob-inf-vac
  report ((count turtles with [(infected?) or (immune?) or (dead?) and (vaccinated?)]) / count turtles with [vaccinated?])
end

to-report not-inf-vac
  report (count turtles with [(vaccinated?) and (infected? = false) and (immune? = false) and (dead? = false)])
end

to-report inf-unvac-people
  report (count turtles with [(infected?) or (immune?) or (dead?) and (vaccinated? = false)])
end

to-report prob-inf-unvac
  report ((count turtles with [(infected?) or (immune?) or (dead?) and (vaccinated? = false)]) / count turtles with [vaccinated? = false])
end

to-report not-inf-unvac
  report (count turtles with [(vaccinated? = false ) and (infected? = false) and (immune? = false) and (dead? = false)])
end

to-report deaths
  report (count turtles with [dead?])
end

to-report people
  report (population - count turtles with [dead?])
end

to-report current-infections
  report(count turtles with [infected?])
end

to calculate-max-infected ;; determins the highest number of infections during the simulation
  let x (count turtles with [infected?])
  if x > max-infected
  [set max-infected x]
end

to-report max-infected-people
  report max-infected
end
@#$#@#$#@
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setup
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go
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Relative results
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proportion infected
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100.0
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true
true
"" ""
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people
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Infection rate of vaccinated people
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10.0
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"" ""
PENS
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PLOT
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Infection rate of unvaccinated people 
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propotion infection
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"" ""
PENS
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Absolute results
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absolute numbers
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"infected and vaccinated" 1.0 0 -955883 true "" "plot (count turtles with [(infected?) and (vaccinated?)])"
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299
Infected people 
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NIL
0.0
10.0
0.0
1.0
true
true
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current-infections
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@#$#@#$#@
## WHAT IS IT?

COVID-19 Virus Spread Model is an Agent-Based-Model built from the skeleton of an SIR model developed by Paul Smaldino currently (2020) at the Cognitive and Information Sciences Department at the University of California, Merced; and was further developed by Nich Martin at the University of Florida, Department of Entomology and Nematology as a tool to help educate the public on how interaction models concerning the current COVID-19 pandemic are used to make predictions and recommendations to the public. 

## HOW IT WORKS

An initial population of agents (blue-colored humanoids) are randomly placed in the model space with an initial population of infected individuals (red). As time moves forward, agents move randomly through the model space according to specified parameters such as number of stationary individuals and mobility. Infected individuals transmit the virus to susceptible individuals by coming within a certain distance of each other. Whether the susceptible individual becomes infected is determined by a random probability, the likelihood of which increases as transmission rate increases. The model can be run with and without immune individuals; when ran with immunity, infected individuals will become immune (color changes to gray) according to a random probability, the liklihood of which increases with increasing recovery rate. Mortality rate can be adjusted. The ability of hospitals to cope with the proportion of infected individuals can be adjusted as well. Once the proportion of infected individuals is greater than _health care capacity_ mortality increases an order of magnitude, as predicted by other current models. 

## HOW TO USE IT

After adjusting the parameters, described below, simply click the _setup_ button and click _go_. The model will continue to run until there are either no more infected individuals or no more susceptible individuals.

### Initial Population

Control population size by adjusting the _init-population_ slider.

### Initial Number of Infected Individuals

Controls initial number of infected using the _init-infected_ slider.

### Transmission Rate

Current estimates are between 0.50 and 0.70. Set transmission rate by moving the _transmission.rate_ slider.

### Number of Stationary Individuals

The _stationary_ slider allows the user to control the number of individals not moving (represents physical/social distancing) in the model space.

### Mobility

The _mobility_ slider allows the user to set how much distance non-stationary individuals move throughout the model space.

### Recovery Rate

Set the _recovery.rate_ slider low for longer recovery time and high for quick recovery. Suggested recovery rate for the current virus is 0.15.

### Immunity

Activate individuals' ability to recover from infection by turning on the _immunity?_ switch.

### Initial Number of Immune Individuals

Use the _init-immune_ slider to adjust the number of individuals immune to the virus before the model runs.

###  Mobilize the Immune

By activating the _mobilize-immune?_ switch, individuals who were once stationary are allowed to move throughout the model space once they become immune. 

### Quarantine Effort

By adjusting the _quarantine.effort_ slider, users can control infected individuals' ability to infect susceptibles.

### Health Care Capacity

The _healthcare.capacity_ slider changes the proportion of infected individuals hospitals can provide care for. Once the proportion of infected individuals exceeds health care capacity (which I'm told should realistically be set at least below 0.30) mortality rate increases one order of magnitude from where it was initially set.

### Mortality Rate

The _infected.mortality_ slider changes the base-line mortality rate for those infected. Estimates for mortality rate range from 1 to 10%, averaging around 3.6 when not accounting for health care capacity.


## THINGS TO NOTICE

You can watch the model space and individuals moving throughout it to see how disease spreads throughout a population.

The model has two plot outputs. The first shows the number of susceptible, infected, and immune individuals through time. This same figure also shows a line for health care capacity. 

The plot below the first shows the total number of individuals who have died as the model moves through time. 

There are also a number of indicator values including the maximum propotion of individuals infected, the proportion uninfected, the number of people who have died, and the current population size. 


## THINGS TO TRY

Try adjusting the _init-population_ slider to see how more sparse, rural areas are affected vs. densely populated cities.

Adjust the _stationary_ slider to see how many people "social distancing" it takes to "flatten the curve".

Adjust the _init-immune_ slider to see what outcomes would look like if a vaccine was available, and how many individuals getting vaccinated it would take to see the effects of "herd immunity".

By adjusting the _quarantine.effort_ you can see what the effects of isolating individuals already infected has on the dynamics of the system. 

## EXTENDING THE MODEL

If you have any suggestions for things to add or change in the model feel free to contact me at n.martin@ufl.edu. I (Nich Martin) am not an epidemiologist, so if there are epidemiologists out there who feel the model needs drastic improvement, please contact me. But please also bear in mind, this was developed as an educational tool so changes will likely only be made if they serve an educational benefit. Netlogo users are encouraged to adjust the code as they see fit; I would be delighted if you send me your updates; I am new to agent-based modeling and would like useful feedback.

## RELATED MODELS

This model is based off an initial model by Paul Smaldino
"SIR Model with random movement"
http://smaldino.com/wp/


## CREDITS AND REFERENCES

CREATIVE COMMONS LICENSE
This code is distributed by Nich Martin under a Creative Commons License:
Attribution-ShareAlike 4.0 International (CC 4.0)
https://creativecommons.org/licenses/by/4.0/
@#$#@#$#@
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Circle -16777216 true false 234 174 42
Rectangle -7500403 true true 181 185 214 194
Circle -16777216 true false 144 174 42
Circle -16777216 true false 24 174 42
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Polygon -10899396 true false 195 90 225 75 245 75 260 89 269 108 261 124 240 105 225 105 210 105
Polygon -10899396 true false 105 90 75 75 55 75 40 89 31 108 39 124 60 105 75 105 90 105
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Polygon -10899396 true false 85 204 60 233 54 254 72 266 85 252 107 210
Polygon -7500403 true true 119 75 179 75 209 101 224 135 220 225 175 261 128 261 81 224 74 135 88 99

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Circle -16777216 true false 30 30 240
Line -7500403 true 150 285 150 15
Line -7500403 true 15 150 285 150
Circle -7500403 true true 120 120 60
Line -7500403 true 216 40 79 269
Line -7500403 true 40 84 269 221
Line -7500403 true 40 216 269 79
Line -7500403 true 84 40 221 269

wolf
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Polygon -7500403 true true 2 194 13 197 30 191 38 193 38 205 20 226 20 257 27 265 38 266 40 260 31 253 31 230 60 206 68 198 75 209 66 228 65 243 82 261 84 268 100 267 103 261 77 239 79 231 100 207 98 196 119 201 143 202 160 195 166 210 172 213 173 238 167 251 160 248 154 265 169 264 178 247 186 240 198 260 200 271 217 271 219 262 207 258 195 230 192 198 210 184 227 164 242 144 259 145 284 151 277 141 293 140 299 134 297 127 273 119 270 105
Polygon -7500403 true true -1 195 14 180 36 166 40 153 53 140 82 131 134 133 159 126 188 115 227 108 236 102 238 98 268 86 269 92 281 87 269 103 269 113

x
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@#$#@#$#@
NetLogo 6.2.1
@#$#@#$#@
@#$#@#$#@
@#$#@#$#@
<experiments>
  <experiment name="experiment-122" repetitions="30" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="9999"/>
    <metric>ticks</metric>
    <enumeratedValueSet variable="num-turtles">
      <value value="200"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="transmissibility">
      <value value="0.1"/>
      <value value="0.9"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="recovery-rate">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init-infected">
      <value value="3"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="speed">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="turning-angle">
      <value value="10"/>
      <value value="180"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="remove-recovered?">
      <value value="false"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="HW7-1" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <metric>count turtles</metric>
    <steppedValueSet variable="num-turtles" first="50" step="50" last="500"/>
    <enumeratedValueSet variable="transmissibility">
      <value value="0.1"/>
      <value value="0.9"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="recovery-rate">
      <value value="0"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init-infected">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="speed">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="turning-angle">
      <value value="60"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="remove-recovered?">
      <value value="false"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="HW7-2" repetitions="10" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <steppedValueSet variable="num-turtles" first="50" step="50" last="500"/>
    <enumeratedValueSet variable="transmissibility">
      <value value="0.1"/>
      <value value="0.9"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="recovery-rate">
      <value value="0.01"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init-infected">
      <value value="3"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="speed">
      <value value="1"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="turning-angle">
      <value value="60"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="remove-recovered?">
      <value value="true"/>
    </enumeratedValueSet>
  </experiment>
  <experiment name="experiment-covid" repetitions="30" runMetricsEveryStep="false">
    <setup>setup</setup>
    <go>go</go>
    <timeLimit steps="100000"/>
    <metric>max-infected-prop</metric>
    <metric>prop-uninfected</metric>
    <enumeratedValueSet variable="num-turtles">
      <value value="500"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="transmissibility">
      <value value="0.3"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="recovery-rate">
      <value value="0.01"/>
    </enumeratedValueSet>
    <enumeratedValueSet variable="init-infected">
      <value value="3"/>
    </enumeratedValueSet>
    <steppedValueSet variable="speed" first="0.25" step="0.25" last="10"/>
    <enumeratedValueSet variable="remove-recovered?">
      <value value="true"/>
    </enumeratedValueSet>
  </experiment>
</experiments>
@#$#@#$#@
@#$#@#$#@
default
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0.0 1 1.0 0.0
0.2 0 0.0 1.0
link direction
true
0
Line -7500403 true 150 150 90 180
Line -7500403 true 150 150 210 180
@#$#@#$#@
0
@#$#@#$#@