run_daily_import_model_par: Run the full simulation of daily importations
In HopkinsIDD/covidImportation: Estimating the Number of Imported COVID-19 Cases

Run the full simulation of daily importations

run_daily_import_model_par(
  n_sim = 10000,
  input_data,
  travel_data_monthly = travel_data_monthly,
  travel_dispersion = 3,
  travel_restrictions = data.frame(loc = "Hubei", min = "2020-01-25", max =
    "2020-04-01", p_travel = 0),
  allow_travel_variance = FALSE,
  meanD_mat,
  tr_inf_redux,
  u_origin,
  get_detection_time = FALSE,
  time_inftotravel,
  time_inftodetect,
  project_name = NULL,
  batch = NULL,
  version = NULL,
  print_progress = TRUE,
  cores = 4,
  save_sims = FALSE
)

`n_sim`	number of simulations to run
`input_data`	full importation input data, including case, travel, and population data
`travel_data_monthly`	monthly travel data between sources and destinations
`travel_dispersion`	how evenly the monthly travel should be distributed across days
`travel_restrictions`	data.frame of travel restrictions
`allow_travel_variance`	whether to sample from the travel variance
`meanD_mat`	matrix of mean duration during which infected individuals can travel
`tr_inf_redux`	proportion reduction in travel when individuals are infected
`u_origin`	reporting rate, origin
`get_detection_time`	logical; return importation detection or not
`time_inftotravel`	time from infection to traveling
`time_inftodetect`	Time from infection to detection
`project_name`	project name, if saving in the function
`batch`	run batch, if saving in the function
`version`	run version, if saving in the function
`print_progress`	logical, whether to print the progress of the simulations
`cores`	number of cores for parallel processing

list consisting of two objects: 1) an array of importations by date, location, and simulation, 2) a dataframe with negative binomial parameters for each location and date

HopkinsIDD/covidImportation documentation built on Sept. 14, 2020, 2:43 p.m.