simulate_data_dates: Nosocomial transmission data simulation with fixed dates.
In bitrugs: Bayesian Inference of Transmission Routes Using Genome Sequences

Description Usage Arguments Details Value See Also Examples

View source: R/simulatedata.r

Nosocomial transmission data simulation with fixed dated of admission and discharge. Swab test results and genetic information are generated.

1 2	simulate_data_dates(day_adm, day_dis, p = 0.05, z = 0.8, b = 0.005, gamma = 0.3, gamma_gl = 0.03, genpar = 0.8, testdays = 3, model = 2)

`day_adm`	Vector of admission dates (integer values).
`day_dis`	Vector of discharge dates (integer values). Must be same length as `day_adm`.
`p`	Probability of carriage on admission.
`z`	Swab test sensitivity.
`b`	Transmission rate.
`gamma`	Within host/group genetic diversity (geometric distribution parameter).
`gamma_gl`	Between host/group genetic diversity (geometric distribution parameter).
`genpar`	Group clustering parameter (model 1), or transmission chain parameter (model 2). See details below.
`testdays`	Number of days between each carriage test/isolate collection.
`model`	Genetic diversity model (1: Importation clustering model, 2: Transmission chain model). See details below.

We implement two different models of genetic diversification. Model 1 is the importation clustering model, in which each infected host belongs to a group. The probability that a new importation belongs to a new group is genpar. All hosts within the same transmission chain belong to the same group. Pairwise genetic distances are sampled from geometric distributions with parameters gamma and gamma_gl for within-group and between-group pairs respectively. Model 2 is the transmission chain model, in which genetic distances increase as hosts are further separated in the transmission tree. Genetic distances between hosts separated by k transmission links are drawn independently from the geometric distribution with parameter gamma x genpar^k. Genetic distances between hosts in independent transmission chains are drawn from a geometric distribution with parameter gamma_gl.

Returns a list of simulated data;

`epi`	Matrix of epidemiological data, consisting of columns patient ID, day of admission, day of discharge, time of colonization, source of infection, and infection group.
`resmat`	Matrix of test results. Each row represents the corresponding patient in `epi`. Each column represents a day, spanning the interval over which data were collected. 0=Negative, 1=Positive, -1=Missing
`distmat`	Pairwise genetic distance data. Each row and column corresponds to patient ID in `patientseqIDs`.
`patientseqIDs`	Vector of patient IDs corresponding to the rows and columns of `distmat`.

simulate_data to additionally generate admission and discharge dates.

1
2
3

    admissions <- sort(sample(1:100,100, replace=TRUE))
    discharge <- admissions + rpois(100,5) + 1
    Tsim <- simulate_data_dates(day_adm=admissions, day_dis=discharge, p=0.1,b=0.01)