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Extract Transmissions Matrix from Network Epidemic Model

Source: R/dendo.R, R/get.R
get_transmat.Rd

Extracts the matrix of transmission data for each transmission event that occurred within a network epidemic model.

Usage

is.transmat(x)

get_transmat(x, sim = 1, deduplicate = TRUE)

Arguments

x

An EpiModel object of class netsim().

sim

Simulation number of extracted network.

deduplicate

If TRUE, randomly select one transmission event in the case that multiple events occur per newly infected agent within a time step.

Value

A data frame with the following standard columns:

  • at: the time step at which the transmission occurred.

  • sus: the ID number of the susceptible (newly infected) node.

  • inf: the ID number of the infecting node.

  • infDur: the duration of the infecting node's disease at the time of the transmission.

  • transProb: the probability of transmission per act.

  • actRate: the rate of acts per unit time.

  • finalProb: the final transmission probability for the transmission event.

A simulation without transmissions gives a data frame with no rows and the columns of the other simulations in x, or, if none of them has a transmission either, the columns at, sus, and inf.

Examples

# \donttest{
## Simulate SI epidemic on two-group Bernoulli random graph
nw <- network_initialize(n = 100)
nw <- set_vertex_attribute(nw, "group", rep(1:2, each = 50))
formation <- ~edges
target.stats <- 50
coef.diss <- dissolution_coefs(dissolution = ~offset(edges), duration = 20)
est <- netest(nw, formation, target.stats, coef.diss, verbose = FALSE)
#> Starting simulated annealing (SAN)
#> Iteration 1 of at most 4
#> Finished simulated annealing
#> Starting maximum pseudolikelihood estimation (MPLE):
#> Obtaining the responsible dyads.
#> Evaluating the predictor and response matrix.
#> Maximizing the pseudolikelihood.
#> Finished MPLE.
param <- param.net(inf.prob = 0.3, inf.prob.g2 = 0.15)
init <- init.net(i.num = 10, i.num.g2 = 10)
control <- control.net(type = "SI", nsteps = 10, nsims = 3, verbose = FALSE)
mod <- netsim(est, param, init, control)

## Extract the transmission matrix from simulation 2
get_transmat(mod, sim = 2)
#> # A tibble: 8 × 8
#> # Groups:   at, sus [8]
#>      at   sus   inf network infDur transProb actRate finalProb
#>   <int> <int> <int>   <int>  <dbl>     <dbl>   <dbl>     <dbl>
#> 1     2    89    34       1      3      0.15       1      0.15
#> 2     3    23    20       1      9      0.3        1      0.3 
#> 3     3    52    65       1      2      0.15       1      0.15
#> 4     3    88    36       1      3      0.15       1      0.15
#> 5     4    18    88       1      1      0.3        1      0.3 
#> 6     5    71    84       1     12      0.15       1      0.15
#> 7     7    44    31       1      9      0.3        1      0.3 
#> 8    10    83    70       1     11      0.15       1      0.15
# }