# ABM Pandemic

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turtles-own [ state ;; State of each turtle (S for , I for infectious, R for recovered) ] globals [ delay infection_rate K observer plot-data max-ticks ] to setup clear-all reset-ticks set max-ticks 80 set infection_rate initial_infection_rate create-turtles population-size [ set shape "person" setxy random-xcor random-ycor set state "S" set color green ] ask n-of initial_infections turtles [ set state "I" set color red ] ask n-of initial_recoveries turtles [ set state "R" set color blue ] set K population-size / 4 ;; Carrying capacity in population (logistic growth) end to run-simulation let tick-count 0 while [tick-count < max-ticks] [ ask turtles [ runge-kutta-step count turtles with [state = "S"] count turtles with [state = "I"] count turtles with [state = "R"] ] ask turtles [ move if state = "I" [ ask other turtles in-radius 1 [ if state = "S" and random-float 1 < infection_rate [ set state "I" set color red ] ] ifelse random-float 1 < recovery_rate [ set state "R" set color blue ] [ ;; Infected turtles that do not recover ] ] ] set delay (10 / tick_speed) * 0.1 wait delay tick set tick-count tick-count + 1 ;; Record counts and update plot let current-s count turtles with [state = "S"] let current-i count turtles with [state = "I"] let current-r count turtles with [state = "R"] set plot-data (list current-s current-i current-r) ;; Check if there are still infectious turtles if not any? turtles with [state = "I"] [ stop ] ] end to move rt random 360 fd 1 display end to runge-kutta-step [S I R] let dt 0.1 ;; Time step size let k1 derivative S I R let k2 derivative (S + 0.5 * dt * item 0 k1) (I + 0.5 * dt * item 1 k1) (R + 0.5 * dt * item 2 k1) let k3 derivative (S + 0.5 * dt * item 0 k2) (I + 0.5 * dt * item 1 k2) (R + 0.5 * dt * item 2 k2) ;;print (list "Before update - S: " S " I: " I " R: " R) let k4 derivative (S + dt * item 0 k3) (I + dt * item 1 k3) (R + dt * item 2 k3) set S S + (dt / 6) * (item 0 k1 + 2 * item 0 k2 + 2 * item 0 k3 + item 0 k4) set I I + (dt / 6) * (item 1 k1 + 2 * item 1 k2 + 2 * item 1 k3 + item 1 k4) set R R + (dt / 6) * (item 2 k1 + 2 * item 2 k2 + 2 * item 2 k3 + item 2 k4) ;; Calculate logistic growth let t ticks let logistic-growth-value logistic-growth t ;; Update infection rate based on logistic growth set infection_rate infection_rate + logistic-growth-value ;;print (list "After update - S: " S " I: " I " R: " R) end to-report derivative [S I R] let N count turtles let dS_dt ((-1) * (infection_rate / N) * I * S) let dI_dt ((infection_rate / N) * I * S) - (recovery_rate * I) let dR_dt (recovery_rate * I) report (list dS_dt dI_dt dR_dt) end to-report logistic-growth [t] report K / (1 + initial_infection_rate * exp(- recovery_rate * t)) end

There is only one version of this model, created about 1 month ago by Zeus Morley Pineda.

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