turtles-own [ hours speed ] globals [ start-speed ] to setup clear-all reset-ticks set start-speed 0.5 create-turtles people-count [ setxy random-xcor random-ycor set shape "person" set color green set speed start-speed ] ask one-of turtles [ set color orange ] end to go ask turtles [ fd speed * (1 - 1 / social-distance) right 45 - random 90 set hours hours + 1 ] ask turtles [ if (color = red) or (color = orange) [ ask turtles in-radius 1 [ if random 100 < infection-probability [ if color = green [ set color orange set hours 0 ] ] ] ] if (color = orange) and (hours > (incubation-time * 24)) [ set color red set hours 0 set speed 0 ] if (color = red) and (hours = (illness-duration * 24)) [ ifelse random 100 < severity-rate [ set color violet set hours 0 set speed 0 ] [ set color cyan set hours 0 set speed start-speed ] ] if (color = violet) [ if count turtles with [color = violet] > hospital-capacity [ set color gray set speed 0 set hours 0 ] ] if (color = violet) and (hours = (illness-duration * 24)) [ ifelse random 100 < death-rate [ set color gray set hours 0 set speed 0 ] [ set color cyan set hours 0 set speed start-speed ] ] ] if finished? [stop] tick end to-report finished? if (count turtles with [color = orange] = 0) and (count turtles with [color = red] = 0) and (count turtles with [color = violet] = 0) [ report true ] report false end @#$#@#$#@ GRAPHICS-WINDOW 336 60 773 498 -1 -1 13.0 1 10 1 1 1 0 1 1 1 -16 16 -16 16 0 0 1 ticks 30.0 BUTTON 411 545 546 579 Setup simulation setup NIL 1 T OBSERVER NIL S NIL NIL 1 BUTTON 549 545 697 579 Run simulation go T 1 T OBSERVER NIL R NIL NIL 1 SLIDER 337 505 509 538 people-count people-count 10 500 200.0 10 1 NIL HORIZONTAL SLIDER 35 507 239 540 social-distance social-distance 0.05 1 0.85 0.01 1 NIL HORIZONTAL SLIDER 36 84 240 117 infection-probability infection-probability 0 100 5.0 1 1 % HORIZONTAL SLIDER 37 139 239 172 incubation-time incubation-time 0 27 5.0 1 1 days HORIZONTAL SLIDER 37 202 237 235 severity-rate severity-rate 0 100 20.0 1 1 % HORIZONTAL SLIDER 37 275 239 308 death-rate death-rate 0 100 19.0 1 1 % HORIZONTAL SLIDER 35 396 239 429 illness-duration illness-duration 0 50 14.0 1 1 days HORIZONTAL PLOT 810 63 1154 291 How many people are... hours NIL 0.0 10.0 0.0 10.0 true true "" "" PENS "healthy" 1.0 0 -13840069 true "" "plot count turtles with [color = green]" "infected" 1.0 0 -955883 true "" "plot count turtles with [color = orange]" "ill" 1.0 0 -2674135 true "" "plot count turtles with [color = red]" "severe" 1.0 0 -8630108 true "" "plot count turtles with [color = violet]" "immune" 1.0 0 -8990512 true "" "plot count turtles with [color = cyan]" "dead" 1.0 0 -7500403 true "" "plot count turtles with [color = gray]" MONITOR 1034 296 1155 341 Dead % count turtles with [color = gray] / people-count * 100 3 1 11 MONITOR 810 295 891 340 Days passed ticks / 24 1 1 11 SLIDER 601 505 774 538 hospital-capacity hospital-capacity 0 100 20.0 1 1 NIL HORIZONTAL TEXTBOX 36 34 246 67 Facts about the illness 15 0.0 1 TEXTBOX 36 59 249 81 How likely are people to contract the disease from contact? 8 0.0 1 TEXTBOX 37 126 241 150 How long before first symptoms show up? 8 0.0 1 TEXTBOX 37 187 245 206 How many people need to go the hospital? 8 0.0 1 TEXTBOX 40 251 237 273 How many people in the hospital do not survive?\t 8 0.0 1 TEXTBOX 37 371 245 392 How long are people ill? Also long will people need to go to the hospital? 8 0.0 1 TEXTBOX 37 480 244 504 To what degree do people refrain from interaction? 8 0.0 1 TEXTBOX 36 453 256 472 Facts about behavior 15 0.0 1 TEXTBOX 812 38 1092 74 Outcome of the Simulation 15 0.0 1 PLOT 810 347 1090 497 Free Hospital capacity NIL NIL 0.0 10.0 0.0 10.0 true false "" "" PENS "Free beds" 1.0 0 -16777216 true "" "plot hospital-capacity - count turtles with [color = violet]" MONITOR 895 296 1030 341 Unaffected % count turtles with [color = green] / people-count * 100 2 1 11 MONITOR 146 315 196 352 % severity-rate * death-rate / 100 2 1 9 TEXTBOX 37 323 153 347 This should lead to a total death rate of: 8 0.0 1 BUTTON 550 581 698 615 Step simulation go NIL 1 T OBSERVER NIL NIL NIL NIL 1 TEXTBOX 467 20 694 44 Flatten the curve 22 0.0 1 TEXTBOX 287 554 437 572 First, click here -> 13 15.0 1 TEXTBOX 705 554 855 572 <- Next, click here 12 15.0 1 TEXTBOX 28 545 214 577 Then, play aroud with this ^ 13 15.0 1 @#$#@#$#@ ## WHAT IS IT? This is a model that explains how the spread of disease affects a community. It incorporates a three stage illness model and a spatial model of contagion. Two remedies are modeled: Hospital size and social distancing. ## HOW IT WORKS Agents walk around in "random walks" simulating normal social behavior. One agent has become infected but is in incubation time. During incubation time behavior is normal but other agents can become infected. Whether or not an agent gets affected depends on the infection-probability. After the incubation-time agents become ill and reduce their social interaction by stopping movement. They are still infections if other agents "visit" them. After the illness-duration agents can become severly-ill, depending on the severity-rate. Severly ill agents no longer infect other agents as they are in isolation. When no hospital beds are available severly ill agents die. All other severly ill agents recover after another illness-duration. With the exception of some agents. Depending on the death-rate some agents do not recover from severe illness. Social distancing regulates the distances travelled by each agent and thus also the amount of possible interaction. Strong social distancing reduces community spread, but increases the likelihood of infecting very near agents (infecting other household members in quarantine). ## HOW TO USE IT The model calculates an expected rate of deaths from the illness information. By manipulating social distancing and hotel capacity (with respect to total agents) different outcomes can occur. As outcome variables the overall duration of the epidemic is shown as well as the amount of agents that have died. ## THINGS TO NOTICE The amount of ill people grows exponentially leading to a quick reduction in social interaction. When the hospital capacity reaches zero, death rate increases drastically. ## THINGS TO TRY Try exploring the social distancing and hospital capacity sliders for fixed population sizes. You can restart the simulation by pressing the "S" key and run the simulation by pressing the "R" key. This allows to quickly compare model runs. In the default configuration interesting differences occur between 0.7 and 0.95 social distancing. ## EXTENDING THE MODEL This model assumes fixed times. Extensions could include random incubation periods, random illness-durations and more agent heterogeneity. Currently all agents are affected equally from the disease. Age or gender dependent reactions could be implemented. The spatial model is a high level of abstraction from real human interaction. ## CREDITS AND REFERENCES by André Calero Valdez (@sumidu) web calerovaldez.com @#$#@#$#@ default true 0 Polygon -7500403 true true 150 5 40 250 150 205 260 250 airplane true 0 Polygon -7500403 true true 150 0 135 15 120 60 120 105 15 165 15 195 120 180 135 240 105 270 120 285 150 270 180 285 210 270 165 240 180 180 285 195 285 165 180 105 180 60 165 15 arrow true 0 Polygon -7500403 true true 150 0 0 150 105 150 105 293 195 293 195 150 300 150 box false 0 Polygon -7500403 true true 150 285 285 225 285 75 150 135 Polygon -7500403 true true 150 135 15 75 150 15 285 75 Polygon -7500403 true true 15 75 15 225 150 285 150 135 Line -16777216 false 150 285 150 135 Line -16777216 false 150 135 15 75 Line -16777216 false 150 135 285 75 bug true 0 Circle -7500403 true true 96 182 108 Circle -7500403 true true 110 127 80 Circle -7500403 true true 110 75 80 Line -7500403 true 150 100 80 30 Line -7500403 true 150 100 220 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