TABLE 1.
Source attribution models considered, with model numbers for those that converged
| Model | Type transmission potential terms (q) a | Model of relative abundance of STs in each source | prior | Joint vs. two‐step inference? b | With unsampled source? | |
|---|---|---|---|---|---|
| M1 | Varied | Dirichlet | Dirichlet (1,…,1) | Joint | Yes |
| M2 | No | ||||
| M3 | Dirichlet (0.1,…,0.1) | Yes | |||
| M4 | No | ||||
| M5 | Dirichlet (1,…,1) | Two‐step | Yes | ||
| M6 | No | ||||
| M7 | Asymmetric island | ||||
| * | Equal | Dirichlet | Dirichlet (1,…,1) | Joint | Yes |
| * | No | ||||
| * | Dirichlet (0.1,…,0.1) | Yes | |||
| * | No | ||||
| M8 | Dirichlet (1,…,1) | Two‐step | Yes | ||
| M9 | No | ||||
| M10 | Asymmetric island | ||||
Abbreviation STs, sequence types.
*
The fitting procedure for these models failed to converge, so results are omitted.
a
Type transmission potential terms were either all set to 1 or estimated using a log‐normal hyperprior with unknown variance.
b
In joint models, all parameters were estimated simultaneously in fully joint Bayesian inference; otherwise, the posterior distribution of the relative abundance of STs in each source was estimated separately, and 100 draws from this posterior were used to estimate the remaining parameters in a second inference step.