dot-chain_sim: Simulate transmission chains using a stochastic branching...

In superspreading: Understand Individual-Level Variation in Infectious Disease Transmission

Simulate transmission chains using a stochastic branching process

Description

Code modified from the bpmodels::chain_sim() function. The function chain_sim() function from bpmodels is reused with permission and licensed under MIT as is bpmodels. bpmodels is not on CRAN and is retired.

Usage

.chain_sim(
  n,
  offspring,
  stat = c("size", "length"),
  stat_threshold = Inf,
  generation_time,
  tf = Inf,
  ...
)

Arguments

n	Number of simulations to run.
offspring	Offspring distribution: a character string corresponding to the R distribution function (e.g., "pois" for Poisson, where rpois() is the R function to generate Poisson random numbers).
stat	String; Statistic to calculate. Can be one of: "size": the total number of offspring. "length": the total number of ancestors.
stat_threshold	A size or length above which the simulation results should be set to Inf. Defaults to Inf, resulting in no results ever set to Inf
generation_time	The generation time generator function; the name of a user-defined named or anonymous function with only one argument n, representing the number of generation times to generate.
tf	End time (if generation_time interval is given).
...	Parameters of the offspring distribution as required by R.

Value

A ⁠<data.frame>⁠ with columns n (simulation ID), id (a unique ID within each simulation for each individual element of the chain), ancestor (the ID of the ancestor of each element), and generation. A time column is also appended if the generation_time interval is supplied to serial.

Author(s)

Sebastian Funk, James M. Azam, Joshua W. Lambert

superspreading documentation built on April 4, 2025, 3:18 a.m.