Extracts the matrix of transmission data for each transmission event that occurred within a network epidemic model.
Arguments
- x
An
EpiModel
object of classnetsim
.- sim
Simulation number of extracted network.
- deduplicate
If
TRUE
, randomly select one transmission event in the case that multiple events current 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.
Examples
## 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 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: 24 × 8
#> # Groups: at, sus [24]
#> at sus inf network infDur transProb actRate finalProb
#> <dbl> <int> <int> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 2 2 15 1 9 0.3 1 0.3
#> 2 3 71 2 1 1 0.15 1 0.15
#> 3 3 95 19 1 5 0.15 1 0.15
#> 4 3 97 83 1 9 0.15 1 0.15
#> 5 4 6 19 1 6 0.3 1 0.3
#> 6 4 23 71 1 1 0.3 1 0.3
#> 7 4 40 94 1 11 0.3 1 0.3
#> 8 4 86 100 1 4 0.15 1 0.15
#> 9 5 68 62 1 7 0.15 1 0.15
#> 10 5 75 97 1 2 0.15 1 0.15
#> # ℹ 14 more rows