slsirSimu: ABM SIR

In simoncarrignon/slsir: How Social Learning Shapes the Efficacy of Preventative Health Behaviors in an Outbreak

ABM SIR

Description

Main model

Usage

slsirSimu(
  pop,
  tstep,
  p = 1,
  i0 = 1,
  di = 2,
  recovery = 10,
  speed = 0.8,
  xsize = 100,
  ysize = 100,
  visu = FALSE,
  inf = 0.5,
  sat = 10,
  sat_r = 10000,
  inf_r = 1.1,
  log = F,
  checkcountact = F,
  ts = T,
  ap = F,
  p_i = 1,
  foldername = F,
  strategy = "all",
  sl_rad = 10,
  bt = 0,
  recover = 10
)

Arguments

tstep	the duration of the simulation
p	the probability for one agent to transmit the disease to another one. This can be a single value, in that case the probability is the same for all agent, or a vector of probabilities, in which case the vector represents the probability of transmission for different behaviors. If the p is a vector a column of behavior should be present in pop.
i0	the number of initial infections
di	the distance between two agents under which the disease can be transmitted
speed	the speed at which agents move
visu	TRUE or FALSE, if output should be plotted
inf	inflexion point of the sigmoid
sat	speed of saturation of the sigmoid
log	TRUE or FALSE, if a simple log (number of time step) should be outputed
ts	count and return the number of users during the run
ap	keep and return the full population for each time step, this can slow the model a lot
p_i	the probability for one agent to learn individually.
foldername	if a string, the output is written in a file (instead of being show in the screen) and the string is used as the name of the folder
strategy	which social learning will be used (ie which agents will be copied)
sl_rad	the distance between two agents under which social learning can occur
bt	burning time, a number of timestep during which no learning occurs
N	the number of agents
reco	time for agent to Recover

simoncarrignon/slsir documentation built on Feb. 11, 2024, 3:07 p.m.