simrabid: Simulate a spatially-explicit, individual-based model of...
In mrajeev08/simrabid: Individual-based model of canine rabies

This function simulates the rabies IBM at the specified scale. Inputs much match between the setup_sim and setup_space functions in terms of the space and timesteps being simulated.

simrabid(
  start_up,
  start_vacc,
  I_seeds,
  vacc_dt,
  params = c(list(R0 = 1.2, k = 1, iota = 4), param_defaults),
  days_in_step = 7,
  observe_fun = beta_detect_monthly,
  serial_fun = serial_lognorm,
  dispersal_fun = steps_weibull,
  secondary_fun = nbinom_constrained,
  incursion_fun = sim_incursions_pois,
  movement_fun = sim_movement_continuous,
  sequential = TRUE,
  allow_invalid = TRUE,
  leave_bounds = TRUE,
  max_tries = 100,
  summary_fun = return_env,
  track = TRUE,
  weights = NULL,
  row_probs = NULL,
  coverage = FALSE,
  break_threshold = 0.8,
  by_admin = FALSE,
  extra_pars = NULL,
  routine_vacc = 0
)

`start_up`	objects for start up generated `setup_sim`
`start_vacc`	numeric vector 0, 1, starting proportion vaccinated either length 1 or length of cells being tracked
`I_seeds`	integer, initial number of infections to seed randomly
`vacc_dt`	data.table with three columns: vacc_times (the timestep of vaccination, should correspond to the same timesteps as being simulated), vacc_ests (either coverage or number vaccinated), and vacc_locs (the location id corresponding to the shapefile)
`params`	parameter list, should include all parameters for simulation functions (i.e. serial_, dispersal_, secondary_, incursion_, etc.)
`days_in_step`	integer, the number of days in each time step being simulated (i.e. 7 for weekly, 1 for daily)
`observe_fun`	function for simulating observation/detection, should take two parameters: I_dt (the line list of cases generated in simrabid) and params (the list of params that will be passed through the `param`)
`serial_fun`	function for drawing the serial interval between cases
`dispersal_fun`	function for drawing the dispersal distance/step length
`secondary_fun`	function for generating secondary cases
`incursion_fun`	function for seeding incursions
`movement_fun`	function for simulating movement, current options are `sim_movement_continuous` and `sim_movement_prob`
`sequential`	boolean, whether movements should be sequential or drawn as a kernel
`allow_invalid`	boolean, whether movements to invalid locations should be kept or movements should be resampled (i.e. then transmission events can fail due to movement into an unihabited patch
`leave_bounds`	boolean, whether movements to locations outside the bounds of the area being simulated should be kept or those movements should be resampled (i.e. transmission events can fail due to movement outside of the district
`max_tries`	the maximum number of times to resample invalid movements if either or both `allow_invalid` and `leave_bounds` is false.
`summary_fun`	function for summarizing simulation, should take two parameters a character vector of object names from the simrabid environment that you need for use in the function.
`track`	boolean, whether to track failed transmission events in the line list of cases (I_dt), i.e. invalid movements, contacts with V/E/I individuals
`weights`	numeric vector of the length of the number of cells (both tracked and untracked) in the raster being simulated (for use with `sim_movement_prob`
`row_probs`	numeric vector of the length of the number of tracked cells for allocating vaccinations by (i.e. if you except vaccinations to be more likely in certain grid cells vs. others)
`coverage`	boolean, are the vaccination estimates number of individuals (FALSE) or the proportion vaccinated (TRUE)
`break_threshold`	numeric 0, 1, whether to cut-off the simulation if population declines to below this threshold (to stop run-away simulations)
`by_admin`	boolean, whether simulation is being aggregated to the grid cell or administrative (or arbitrary unit) based on the shapefile
`extra_pars`	list, additional parameters that you might need for the summary or any other custom functions
`routine_vacc`	proportion of new born dogs vaccinated, defaults to zero