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Set up initial cases for branching process

Source: R/outbreak_setup.R
outbreak_setup.Rd

Set up initial cases for branching process

Usage

outbreak_setup(initial_cases, delays, event_probs, interventions)

Arguments

initial_cases

a non-negative integer scalar: number of initial or starting cases which are all assumed to be missed by contact tracing (i.e. tracing ascertainment = 0).

delays

a list with class <ringbp_delay_opts>: the delay distribution functions for the ringbp model, returned by delay_opts(). Contains 4 elements: incubation_period, onset_to_isolation, latent_period and onset_to_self_isolation

event_probs

a list with class <ringbp_event_prob_opts>: the event probabilities for the ringbp model, returned by event_prob_opts(). Contains 5 elements: asymptomatic, presymptomatic_transmission, alpha, symptomatic_traced and symptomatic_self_isolate

interventions

a list with class <ringbp_intervention_opts>: the intervention settings for the ringbp model, returned by intervention_opts(). Contains 2 elements: quarantine and test_sensitivity

Value

data.table of cases in outbreak so far. data.table columns are:

  • $exposure: numeric

  • $asymptomatic: logical

  • $caseid: integer

  • $infector: numeric

  • $traced: logical

  • $onset: numeric

  • $new_cases: integer

  • $self_isolate: logical

  • $isolated_time: numeric

  • $sampled: logical

Examples

delays <- delay_opts(
  incubation_period = \(n) rweibull(n = n, shape = 2.32, scale = 6.49),
  onset_to_isolation = \(n) rweibull(n = n, shape = 1.65, scale = 4.28)
)
event_probs <- event_prob_opts(
  asymptomatic = 0,
  presymptomatic_transmission = 0.15,
  symptomatic_traced = 0
)
interventions <- intervention_opts()

# generate initial cases
case_data <- outbreak_setup(
  initial_cases = 5,
  delays = delays,
  event_probs = event_probs,
  interventions = interventions
)
case_data
#> Index: <self_isolate__asymptomatic>
#>    exposure asymptomatic caseid infector traced    onset new_cases self_isolate
#>       <num>       <lgcl>  <int>    <num> <lgcl>    <num>     <int>       <lgcl>
#> 1:        0        FALSE      1        0  FALSE 7.382506        NA        FALSE
#> 2:        0        FALSE      2        0  FALSE 3.488553        NA        FALSE
#> 3:        0        FALSE      3        0  FALSE 8.338751        NA        FALSE
#> 4:        0        FALSE      4        0  FALSE 5.577247        NA        FALSE
#> 5:        0        FALSE      5        0  FALSE 5.306659        NA        FALSE
#>    isolated_time sampled
#>            <num>  <lgcl>
#> 1:     11.098008   FALSE
#> 2:     10.795869   FALSE
#> 3:     14.142051   FALSE
#> 4:      6.343947   FALSE
#> 5:     11.410506   FALSE