Calculate whether outbreaks went extinct or not

detect_extinct(outbreak_df_week, cap_cases, week_range = 12:16)

Arguments

outbreak_df_week: a data.table: weekly cases produced by the outbreak model
cap_cases: a positive integer scalar: number of cumulative cases at which the branching process (simulation) was terminated
week_range: a positive integer vector: giving the (zero indexed) week range to test for whether an extinction occurred. Default is 12:16.

Value

A data.table, with two columns sim and extinct, for a binary classification of whether the outbreak went extinct in each simulation replicate. 1 is an outbreak that went extinct, 0 if not.

Details

The cap_cases argument should be equal to the value supplied to outbreak_model() (possibly passed from scenario_sim()).

Author

Joel Hellewell

Examples

res <- scenario_sim(
  n = 10,
  initial_cases = 1,
  offspring = offspring_opts(
    community = \(n) rnbinom(n = n, mu = 2.5, size = 0.16),
    isolated = \(n) rnbinom(n = n, mu = 0.5, size = 1)
  ),
  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 = 0.5,
    symptomatic_ascertained = 0.2
  ),
  interventions = intervention_opts(quarantine = FALSE),
  sim = sim_opts(cap_max_days = 350, cap_cases = 4500)
)
detect_extinct(outbreak_df_week = res, cap_cases = 4500)
#>       sim extinct
#>     <int>   <num>
#>  1:     1       1
#>  2:     2       1
#>  3:     3       1
#>  4:     4       1
#>  5:     5       1
#>  6:     6       0
#>  7:     7       1
#>  8:     8       1
#>  9:     9       1
#> 10:    10       1