simulate: CDI Agent-Based Simulation Function
In PippintheFoolhardy/SimFunctions: CDI Simulator R Functions

Description Usage Arguments Value Examples

Take in the list of all agents and the contact matrix, call the C++ function "propogate" that spreads the infection, and return statistics about how much the infection spreads and to whom it spreads

simulate(
  ml_data,
  mod,
  timestep = 24L,
  agents,
  contact_matrix,
  initial_set,
  plot_now = FALSE,
  num,
  secondary_infections,
  hcw_to_pat_infections,
  pat_to_hcw_infections,
  pat_to_pat_infections,
  hcw_to_hcw_infections,
  secondary_patient_infected,
  secondary_hcw_infected,
  R0,
  attack_curve,
  pat_to_hcw,
  hcw_to_pat,
  hcw_to_hcw,
  iters,
  discharged,
  total_pat,
  transmission_dir
)

`ml_data`	The data to be used in the machine learning algorithm to calculate risk of CDI
`mod`	The machine-learning model to be used to calculate risk of CDI
`timestep`	Number of iterations for the simulation to loop through
`agents`	List of all agents in the simulation
`contact_matrix`	Matrix of contacts between all individual agents
`initial_set`	Initial set of infected agents
`plot_now`	TRUE if you want to watch attack rate over time; FALSE if you don't
`num`	Variable that keeps track of number of timesteps completed
`secondary_infections`	Variable keeps track of number of secondary infections
`hcw_to_pat_infections`	Variable keeps track of number of healthcare worker to patient transmissions
`pat_to_hcw_infections`	Variable keeps track of number of patient to healthcare worker transmissions
`pat_to_pat_infections`	Variable keeps track of number of patient to patient transmissions
`hcw_to_hcw_infections`	Variable keeps track of number of healthcare worker to healthcare worker transmissions
`secondary_patient_infected`	Variable keeps track of number of secondary infections spread to patients
`secondary_hcw_infected`	Variable keeps track of number of secondary infections spread to healthcare workers
`R0`	Variable to store the basic reproduction number of the model
`attack_curve`	Variable to store the attack curve, currently just the total number of secondary infections, in the model
`pat_to_hcw`	Variable to store number of transmissions from patients to healthcare workers as a vector for later use
`hcw_to_pat`	Variable to store number of transmissions from healthcare workers to patients as a vector for later use
`hcw_to_hcw`	Variable to store number of transmissions from healthcare workers to other healthcare workers as a list for later use
`iters`	Variable to store iteration number as a list for later use
`discharged`	Variable to store the number of discharged patients
`total_pat`	Variable to store the total number of patients, initial plus discharged
`transmission_dir`	Variable containing directory name where the C++ transmission function is stored

Long list containing updated agents and simulation statistics

sim_results <- simulate(ml_data, mod, timestep = 24L, agents, contact_matrix, initial_set, plot_now = FALSE, num, secondary_infections, hcw_to_pat_infections, pat_to_hcw_infections, pat_to_pat_infections, hcw_to_hcw_infections, secondary_patient_infected, secondary_hcw_infected, R0, attack_curve, pat_to_hcw, hcw_to_pat, hcw_to_hcw, iters, discharged, total_pat, transmission_dir)