This is a generated data set of an outbreak based on a branching process model with fixed parameters. There is a both the full infection line list as it happened in the simulation and the subset of this data that might have been observed in a contact tracing exercise where identification is done through symptoms.
Source
https://ai4ci.github.io/ggoutbreak/articles/simulation-test-models.html#line-list-simulations
Details
sim_outbreak is a named list with 3 items
| Item | Type | Description |
parameters | list[dbl] | the ground truth of the simulation parameters |
outbreak_truth | df[outbreak_truth]* | the full infection line list |
contact_tracing | df[contact_tracing]* | the "observed" contact tracing subset |
df[outbreak_truth] dataframe with 663 rows and 11 columns
The simulation details
| Column | Type | Description |
time | dbl | The true time of infection |
id | int | Person unique id |
generation_interval | dbl | The time since infector's infection |
infector | int | The unique id of the infector |
generation | dbl | Which generation is this infection since the simulation start |
symptom | lgl | Did this person experience symptoms |
symptom_delay | dbl | How long after infection were their symptoms? |
symptom_time | dbl | When? (from the simulation start) |
observation | lgl | Was this person detected (only if symptoms) |
observation_delay | dbl | How long after symptoms were they observed? |
observation_time | dbl | When? (from the simulation start) |
df[contact_tracing] dataframe with 663 rows and 4 columns
A minimal set of data that might be collected in a contact tracing exercise.
| Column | Type | Description |
id | int | Unique person id |
contact_id | int | Unique id of infectious contact |
onset_time | int | Time of symptom onset (from the simulation start) |
obs_time | int | Time of observation (from the simulation start) |