Individual-level outcomes simulated from an SIIR model for 500 households, in
which infection splits into symptomatic (Is) and asymptomatic (Ia)
compartments. The two infectious compartments have separate intra-household
infection probabilities. Each individual has three binary observations: one
informative about active infection (e.g. a PCR test), one informative about
recovery (e.g. an IgG antibody test), and one indicating symptoms.
Format
A data frame with one row per individual per day and the following columns:
- t
Day of observation.
- part_id
Participant identifier within the household.
- enroll
Enrollment indicator (1 = enrolled, 0 = not enrolled).
- state
True latent compartment (1 = S, 2 = Is, 3 = Ia, 4 = R).
- hh_size
Household size.
- hh_id
Household identifier.
- pcr
Binary outcome informative about active infection.
- igg
Binary outcome informative about recovery.
- symp
Binary outcome indicating symptoms.