ABM Lassa Virus Transmission

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Default-person Victor Odoh (Author)

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agent-based model 

Tagged by Victor Odoh almost 2 years ago

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; ABM - LASSA FEVER TRANSMISSION
; STUDENT NAME: VICTOR ODOH
; ID: C2397722
; SCEDT, TEESSIDE UNIVERSITY
; Year: 2022




; Two agentsets are involved in this Model (Humans and rats)
; Hence defining two breeds as follows
breed [humans human]
breed [rats rat]

;       COLOUR CODES:
; Red rat (red - 2) - Multimammate Rat (All Assumed to be infectious)
; White Human - Healthy, not infected/infectious
; Yellow Human - Infected but not infectious (within virus incubation period)
; Orange Human (orange + 2) - Infectious with Mild Symptoms
; Red Human - Infectious with Severe Symptoms
; Cyan Human - Recovered, immune but still Infectious
; Lime Human (lime + 1) - Fully recovered and immune
; Gray Human - Dead


; Declaring humans owned variables
humans-own [
  hours            ; each tick represents an hour
  human_speed      ; to control human speed
]

; Declaring all global variables used...
; (excluding the sliders which do not need to be declared here)
globals [
  control_speed               ; to regulate speed of model
  infected_not_infectious     ; current count of infected humans within virus incubation period
  initial_mild_cases
  initial_severe_cases
  mild_cases_count         ; current count of all mild cases
  severe_cases_count       ; current count of all severe cases
  severe_cases             ; counting variable for infected humans with severe symptoms
  mild_cases               ; counting variable for infected humans with mild symptoms or asymptomatic
  total_mild_cases         ; includes intial mild cases
  total_severe_cases       ; includes initial severe cases
  fatalities               ; counting variable for human deaths
  total_fatalities         ; count of all deaths ever recorded
  immune_infectious      ; current count of recovered and immune humans that are still carriers
  immune_not_infectious  ; current count of immune humans who are no longer carriers
  %Mild_Cases
  %infected
  %uninfected
  %immune
  average_%CFR           ; average case fatality rate in percentage

  immune_or_severe_%infectiousness     ; virus spread chance of immune/recovered carriers
                                       ; or humans with severe symptoms assuming that they are hospitalized/isolated and pose little
                                       ; risk of infecting others

  current_cases       ; number of cases at the curent time
  total_cases         ; Count of all cases ever recorded : addition of counting variables (mild_cases + severe_cases)
  total_immune        ; includes both immune carriers and immune with no virus
  total_infected      ; all carrier humans
  total_infectious    ; all carrier humans excluding infected_not_infectious
]

; Defining the "setup" command procedure:
; Assigning initial values

to setup
  clear-all
  reset-ticks
  set %Mild_Cases (100 - %Severe_Cases)
  set initial_mild_cases (Initial_Number_Of_Cases * %Mild_Cases) / 100
  set initial_severe_cases (Initial_Number_Of_Cases * %Severe_Cases) / 100
  set immune_or_severe_%infectiousness %Infectiousness_Human_to_Human * (1 - Human_Behaviour_Factor)

  ; Declaring basic constant of the model
  set control_speed 1


  ; creating the rat agents with their properties
  ; Distributing them randomly across the patches/world
  create-rats Multimammate_Rat_Population [
    setxy random-xcor random-ycor
    set shape "mouse side"
    set color red - 2
    set size 0.8
  ]

  ; creating the human agents with initially infected humans
  ; Distributing them randomly across the patches/world
  create-humans Human_Population [
    setxy random-xcor random-ycor
    set shape "person"
    set color white
    set size 1
    set human_speed control_speed
  ]

  ; color coding to identify initial mild/severe cases
  ask n-of initial_mild_cases Humans
   [set color orange + 2]
  ask n-of initial_severe_cases Humans
   [ set color red ]
end        ; end of setup command procedure

; Defining the "go" command procedure:

to go
  ; asking rats to move randomly across the world
  ask rats [
    fd control_speed * -1 * ((1 / Human_Behaviour_Factor) * 0.01)
    rt random 100 lt random 100
  ]
  ; asking humans to move randomly across the world
  ask humans [
    fd human_speed * ((1 / Human_Behaviour_Factor) * 0.01)
    rt random 45 lt random 45
    set hours hours + 1    ; advancing hours counting variables
  ]

  ; asking humans that are infectious and applying human to human infection probability..
  ; ..to a nearby uninfected human, for possible infection
  ; color coding to identify each case
  ask humans [
    ifelse (color = orange + 2) [
      ask other humans-here [
        if random 100 < %Infectiousness_Human_to_Human [
          if color = white [
            set color yellow
            set infected_not_infectious infected_not_infectious + 1
            set hours 0
          ]
        ]
      ]
    ]

    ; asking rats and applying rat to human infection probability
    ; to nearby uninfected human in contact, for possible infection
    [
      ask rats [
        ask other humans-here [
          if random-float 100 < %Infectiousness_rat_to_Human [
            if color = white [
              set color yellow
              set hours 0
            ]
          ]
        ]
      ]
    ]

    ; If hospitalized or immune carrier, applying infection probability for possible infection...
    ; ... of other uninfected humans nearby
    if (color = cyan) or (color = red) [
      ask other humans-here [
        if random-float 100 < immune_or_severe_%infectiousness [
          if (color = white) [
            set color yellow
            set hours 0
          ]
        ]
      ]
    ]

    ; converting incubation period in days to hours
    ; what should happen if infection has exceded incubation period?
    ; applying %Severe_Cases probabilty to determine if an infected human...
    ; ... falls under the mild or severe case
    if (color = yellow) and (hours > (incubation_Period * 24)) [
      ifelse random-float 100 < %Severe_Cases [
        set color red
        set severe_cases severe_cases + 1   ; advancing severe_cases counting variable
        set hours 0
        set human_speed 0          ; if severe, assumes human is hospitalized and stops moving
      ]
      [
        set color orange + 2
        set mild_cases mild_cases + 1       ; advancing mild_cases counting variable
        set hours 0
        set human_speed 0.5        ; value assigned to variable to make speed a bit slower than that of other agents
      ]
    ]


    ; converting "days before recovery or death" in days to hours
    ; what should happen if infection has lingered for this period?
    ; applying case fatality probabilty of both type of cases to determine...
    ; ... if an infected human dies or survives
    ; "orange + 2" for mild case, red for severe case
    if (color = orange + 2) and (hours = (Sick_Days * 24)) [
      ifelse random-float 100 < CFR_Mild_Case [
        set color gray
        set fatalities fatalities + 1        ; advancing fatalities counting variable
        set hours 0
        set human_speed 0            ; if dead, human stops moving
      ]
      [
        set color cyan               ; if they survived, they become immune but still carriers (cyan from color coding)
        set hours 0
        set human_speed 0.5
      ]
    ]

    if (color = red) and (hours = (Sick_Days * 24)) [
      ifelse random-float 100 < CFR_Severe_Case [
        set color gray
        set fatalities fatalities + 1
        set hours 0
        set human_speed 0
      ]
      [
        set color cyan
        set hours 0
        set human_speed control_speed
      ]
    ]

    ; what should happen if immune carriers have exceeded the Infectious days after recovery?
    ; mark them as immune and no longer infectious (Lime)
    if (color = cyan) and (hours = (Infectious_Days_After_Recovery * 24)) [
      set color lime + 1       ; lime human is immune and no longer infectious
      set hours 0
      set human_speed control_speed
    ]
  ]

  ; Updating global variables for plotting purposes and for output display on monitor
  set infected_not_infectious count humans with [color = yellow]
  set mild_cases_count count humans with [color = orange + 2]
  set severe_cases_count count humans with [color = red]
  set immune_infectious count humans with [color = cyan]
  set immune_not_infectious count humans with [color = lime + 1]
  set total_immune (immune_infectious + immune_not_infectious)
  set current_cases (mild_cases_count + severe_cases_count)
  set total_mild_cases (mild_cases + initial_mild_cases)
  set total_severe_cases (severe_cases + initial_severe_cases)
  set total_cases (total_mild_cases + total_severe_cases)
  set total_infectious (current_cases + immune_infectious)
  set total_infected (infected_not_infectious + total_infectious + total_fatalities)
  set total_fatalities count humans with [color = gray]
  set average_%CFR (fatalities / total_cases) * 100
  set %infected (total_infected / Human_Population) * 100
  set %uninfected ((count humans with [color = white]) / Human_Population) * 100
  set %immune (total_immune / Human_Population) * 100

  if infected_not_infectious + current_cases + count humans with [color = white] = 0 [stop]   ; condition (if true) to halt simulation
  tick     ; advancing the tick counter by 1
end 

There is only one version of this model, created almost 2 years ago by Victor Odoh.

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