QuOVPro

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Model Description

Quantifying Population Fear for Optimal Vaccination Program

Vaccination program is one of the control measures recommended by the authorities to prevent the spread of infectious diseases and also build the immunization in the population in order to eradicate the diseases. Individuals’ vaccination decision is important to determine whether the vaccination program is successful. The vaccination decisions of the individuals are affected by their feeling of fear on the infectious diseases. The fear is associated as human behavior. This invention is to simulate the vaccination decision of the individuals in a population with the incorporation of human behavioral changes. The simulation is to imitate the real world vaccination process of vaccination program and visualize its results. The results of this simulation will be visualized as how many percent of feared individuals engage in vaccination program.

HOW IT WORKS

The individuals (aka agents) in the model is assigned with two random numbers to represent their health status and mindset. The individuals are also assigned with a set of rule according to the groups they belong to. There are five groups (or subpopulations) in the model, namely susceptible, infected, feared, vaccinated, and recovered. The rules allowed them to interact and move randomly in the environment. Once the susceptible individuals are in contact with infected individuals, the health status of the susceptible individuals will be compared with the disease transmission rate per contact per unit time. If it is lower, the susceptible is infected by the disease and will be moved to the group of infected. On the other hand, when the susceptible is interacting with the feared, the mindsest of the susceptible will be compared to the probability of getting feared, and if it is lower, the susceptible will get feared. the feared individuals are given the opportunity to make their vaccination decision. They will consider the risks of the vaccination and infection. If the feared decides to engage in vaccination program, he/ she will be vaccinated and moved to the group of vaccinated. Else, he/ she will be given another opportunity to make the vaccination decision at the next time step. In the meantime, the feared is assumed to take some other precautions such as intensified hygienic care in order to avoid infectious. However, if they interact with the infected, they might get infected as well at the reduced disease transmission rate. The vaccinated individuals will be susceptible again after the duration of the effectiveness of vaccines. The infected individuals will be recovered after the duration of infectious.

HOW TO USE IT

The simulator is divided into four sections, namely Input, Operations, Results, and Environment View.

Users have to enter the necessary inputs that listed in the interface: 1. Location: Users can choose the location they wish to simulate based on the dropdown list. 2. Type of diseases: Users can choose the disease they wish to simulate based on the dropdown list. 3. Population fear: Users are required to enter the population fear factor in the text box according to the scale of awareness program.

There are four buttons in the section of Operations: 1. Setup: to let the users setup the environment according to the inputs. 2. Go: to start the simulation. 3. Stop: to force the simulation stop. A message of "Simulation is terminated" will be prompted and users are required to click on "Halt" if wish to stop the simulation. 4. Find_%: to calculate the percentage of feared population, vaccinators from the feared population, individuals that take the other precautions, the difference between vaccinators and individuals that take the other precautions.

The results of the simulation will be displayed in the section of Results. The interaction of the individuals will be shown in the section of Environment View.

THINGS TO NOTICE

Java version of users' environmenthas to be Version 7 or below the Java security level has to be set to medium. Users have to allow the plugins to be run in the browser in order to use the simulator.

CREDITS AND REFERENCES

This work is supported by Universiti Malaysia Sarawak through the research grant scheme number F08(S159)/1170/2014(24). The authors also would like to give credits to Unesco for the approaches of organizing awareness program.

Comments and Questions

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globals[
  initial-susceptible
  initial-fear
  initial-vaccinator
  transmission
  fear_infect-chance
  vaccine-duration
  recovery-rate
  imitation_rate
  risk_vaccination
  risk_infection
  strategies
  payoff_NV
  payoff_V
  omega 
  kappa
  sampling_rate
  x
  max_infected
  cur_infected
  time
  fear_counter
  vaccinator_counter
  population
  feared_%_population
  vaccinator_%_population
  precautions_%_population
  difference_vac_precautions
 ]

breed[susceptibles susceptible]
breed[infecteds infected]
breed[recovereds recovered]
breed[fears fear]
breed[vaccinates vaccinate]

turtles-own [
  health-state
  mind-set
  own_strategy
  susceptible?
  infected?
  recovered?
  fear?
  vaccinate?
  infection-length
  vaccination-period
  number_of_infected
  previous_infected
  number_of_recovered 
  ]

patches-own[
 turtle?
]

;;allocate initial Susceptible individual

to allocateSusceptibles 
  set color blue
  set size 1.2
  set shape "person"
  set heading random 360
  setxy int random-xcor int random-ycor
  set health-state random-float 1
  set mind-set random-float 1
end  

;;allocate initial Infected individual 

to allocateInfected
  set color red
  set size 1.2
  set shape "person"
  set heading random 360
  setxy int random-xcor int random-ycor
end 
 
;;allocate initial Feared individual

to allocateFear
  ;set color yellow
  set size 1.2
  set shape "person"
  set heading random 360
  setxy int random-xcor int random-ycor
end 

;;allocate initial vaccinator

to allocateVaccinator
  set color violet
  set size 1.2
  set shape "person"
  set heading random 360
  setxy int random-xcor int random-ycor
end 

;;let agents to move

to move
  ask turtles [
    right random 45
    left random 45
    forward 1
  ] 
end 

;;to assign health state and mindset to turtles

to assign_status
  ask turtles [
    set health-state random-float 1
    set mind-set random-float 1
  ]
end 

;;disease is spreading and human get infect

to infect 
  ask turtles with [infected?] [
    let nearby-uninfected (turtles-on neighbors)
    with [not infected? and not recovered? and not fear? and not vaccinate?]
    
    if nearby-uninfected != nobody [
      ask nearby-uninfected [
        if health-state < transmission [
          set infection-length 0
          set number_of_infected (number_of_infected + 1) 
          set infected? true
          set fear? false
          set vaccinate? false
          set susceptible? false
          set recovered? false
          set breed infecteds
          set shape "person"
          set color red
          set heading random 360
        ]
      ]
    ]
  ]
end 

;;to create fear in the population

to fear_influence
  ask turtles with [fear?] [
    let nearby-not-fear (turtles-on neighbors)
    with [not infected? and not recovered? and not fear? and not vaccinate?]
    
    if nearby-not-fear != nobody [
      ask nearby-not-fear [ 
        if mind-set < fear-factor [
          set susceptible? false
          set infected? false
          set fear? true
          set vaccinate? false
          set recovered? false
          set breed fears
          set shape "person"
          set size 1.2
          set color yellow
          set heading random 360
          set fear_counter fear_counter + 1
        ]
      ]
    ]
  ]
end 

;;to make decision to vaccinate or not

to decision_vaccinate
  ask turtles with [fear?] [
    let nearby-vaccinated (turtles-on neighbors) with [not infected? and not recovered? and not susceptible? and not fear? and vaccinate?]
    if nearby-vaccinated != nobody [
        if payoff_V > payoff_NV [
          if mind-set < imitation_rate [
            set vaccination-period 0
            set susceptible? false
            set infected? false
            set fear? false
            set vaccinate? true
            set recovered? false
            set breed vaccinates
            set shape "person"
            set size 1.2
            set color violet
            set own_strategy "Vaccinate"
            set heading random 360
            set vaccinator_counter vaccinator_counter + 1
          ]
        ]
      ;]
    ]
  ]
end  

;;disease spread among feared individual with lower probability

to fear_infect
  ask turtles with [infected?] [
    let nearby-fear-not-infected (turtles-on neighbors) 
    with [not infected? and not recovered? and not susceptible? and fear? and not vaccinate?]
    
    if nearby-fear-not-infected != nobody [
      ask nearby-fear-not-infected [
        if health-state < fear_infect-chance [
          set infection-length 0
          set number_of_infected (number_of_infected + 1)
          set susceptible? false
          set infected? true
          set fear? false
          set vaccinate? false
          set recovered? false
          set breed infecteds
          set shape "person"
          set size 1.2
          set color red
          set heading random 360
        ]
      ]
    ]
  ]
end 

;;vaccination period over

to vac-sus
  ask turtles with [vaccinate?] [
    set vaccination-period (vaccination-period + 1)
    if vaccination-period > vaccine-duration [
      set susceptible? true
      set infected? false
      set fear? false
      set vaccinate? false
      set recovered? false
      set breed susceptibles
      set shape "person"
      set size 1.2
      set color blue
    ]
  ]
end 
      
;;to check whether individuals have recovered from infections

to recover
  ask turtles with [infected?][
    set infection-length infection-length + 1
    if infection-length > 1 / recovery-rate
      [
        set number_of_recovered (number_of_recovered + 1)
        set recovered? true
        set breed recovereds
        set heading random 360
        set shape "person"
        set color green
      ]
  ]
end 

;;show the label of strategies that the turtles carry: violet=vaccinate; yellow= not vaccinate

to show_label
  ask turtles [
    if color = violet
    [ set label "V"]
    if color = yellow
    [ set label "NV"]
  ]
end 

;;assign the strategy for turtles

to assign_strategy
  ask turtles [
    if color = violet and vaccinate? = true
    [ set own_strategy "Vaccinate" 
      set payoff_V (-1 * (risk_vaccination))
    ]
    if color = yellow and fear? = true
    [ set own_strategy "Not_vaccinate" 
      set payoff_NV (-1 * (risk_infection) * (1000) * count Infecteds)
    ]
  ]
end 

to turtleown                                                                                    
  ask patches [ ifelse any? other turtles-here [ set turtle? 1 ]                                
                                               [ set turtle? 0 ] ]
end 

;;plot graph

to doPlot
  set-current-plot "Population vs Time"                                               
  set-current-plot-pen "Infected"
  plot (count infecteds * 500)
end 

to find_%
  set population ((count susceptibles + count infecteds + count recovereds + count vaccinates + count fears) * 500)
  set feared_%_population (((fear_counter * 500)/ population) * 100)
  set vaccinator_%_population (((vaccinator_counter * 500) / (fear_counter * 500)) * 100)
  set precautions_%_population ((1 - ((vaccinator_counter * 500) / (fear_counter * 500))) * 100)
  set difference_vac_precautions (vaccinator_%_population - precautions_%_population)
end 

to setup_parameters
  if (location = "Kuching" and disease = "Tuberculosis") [
    set initial-susceptible 615665 / 500
    set initial-fear 10
    set initial-vaccinator 10
    set transmission 0.023
    set fear_infect-chance 0.023 * 0.7
    set vaccine-duration 782
    set recovery-rate 1 / 36
    set imitation_rate 0.05
    set risk_vaccination 0.05
    set risk_infection 0.95
    
    create-susceptibles initial-susceptible [
      allocateSusceptibles
      set susceptible? true
      set infected? false
      set recovered? false
      set fear? false
      set vaccinate? false
    ]
    create-infecteds initial-infectious [
      allocateInfected
      set susceptible? false
      set infected? true
      set recovered? false
      set fear? false
      set vaccinate? false
    ]
    create-fears initial-fear [
      allocateFear
      set own_strategy "Not-vaccinate"
      set color yellow
      set susceptible? false
      set infected? false
      set recovered? false
      set fear? true
      set vaccinate? false
    ]
    create-vaccinates initial-vaccinator [
      allocateVaccinator
      set own_strategy "Vaccinate"
      set susceptible? false
      set infected? false
      set recovered? false
      set fear? false
      set vaccinate? true
    ]
  ]
  if (location = "Limbang" and disease = "Tuberculosis") [
    set initial-susceptible 48519 / 500
    set initial-fear 10
    set initial-vaccinator 10
    set transmission 0.06
    set fear_infect-chance 0.06 * 0.7
    set vaccine-duration 782
    set recovery-rate 1 / 36
    set imitation_rate 0.01
    set risk_vaccination 0.05
    set risk_infection 0.95
    
    create-susceptibles initial-susceptible [
      allocateSusceptibles
      set susceptible? true
      set infected? false
      set recovered? false
      set fear? false
      set vaccinate? false
    ]
    create-infecteds initial-infectious [
      allocateInfected
      set susceptible? false
      set infected? true
      set recovered? false
      set fear? false
      set vaccinate? false
    ]
    create-fears initial-fear [
      allocateFear
      set own_strategy "Not-vaccinate"
      set color yellow
      set susceptible? false
      set infected? false
      set recovered? false
      set fear? true
      set vaccinate? false
    ]
    create-vaccinates initial-vaccinator [
      allocateVaccinator
      set own_strategy "Vaccinate"
      set susceptible? false
      set infected? false
      set recovered? false
      set fear? false
      set vaccinate? true
    ]
  ]
end 

to setup
  __clear-all-and-reset-ticks
  turtleown
  set max_infected initial-infectious 
  setup_parameters
  show_label
end 

to go
  turtleown
  show_label
  assign_strategy
  if ticks > 0[
    move
    assign_status
    infect
    fear_influence
    fear_infect
    decision_vaccinate
    vac-sus
    recover
    set cur_infected (count infecteds * 500)
    if max_infected < cur_infected [
     set max_infected cur_infected
     set time ticks
    ]
  ]
  doPlot
  tick
end 

to stopping
  user-message (word "Simulation is terminated")
  stop
end

There is only one version of this model, created over 10 years ago by Shian Li Teoh.

Attached files

File	Type	Description	Last updated
QuOVPro.png	preview	Preview for 'QuOVPro'	over 10 years ago, by Shian Li Teoh	Download

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