Set up initial cases for branching process
Arguments
- initial_cases
a non-negative
integer
scalar: number of initial or starting cases which are all assumed to be missed.- delays
a
list
with class<ringbp_delay_opts>
: the delay distributionfunction
s for the ringbp model, returned bydelay_opts()
. Contains two elements:incubation_period
andonset_to_isolation
- event_probs
a
list
with class<ringbp_event_prob_opts>
: the event probabilities for the ringbp model, returned byevent_prob_opts()
. Contains three elements:asymptomatic
,presymptomatic_transmission
andsymptomatic_ascertained
Value
data.table
of cases in outbreak so far. data.table
columns are:
$exposure
:numeric
$asymptomatic
:logical
$caseid
:integer
$infector
:numeric
$missed
:logical
$onset
:numeric
$new_cases
:logical
$isolated_time
:numeric
$isolated
: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_ascertained = 0
)
# generate initial cases
case_data <- outbreak_setup(
initial_cases = 5,
delays = delays,
event_probs = event_probs
)
case_data
#> Index: <asymptomatic>
#> exposure asymptomatic caseid infector isolated missed onset new_cases
#> <num> <lgcl> <int> <num> <lgcl> <lgcl> <num> <lgcl>
#> 1: 0 FALSE 1 0 FALSE TRUE 5.327302 NA
#> 2: 0 FALSE 2 0 FALSE TRUE 10.248073 NA
#> 3: 0 FALSE 3 0 FALSE TRUE 9.878893 NA
#> 4: 0 FALSE 4 0 FALSE TRUE 1.781222 NA
#> 5: 0 FALSE 5 0 FALSE TRUE 5.395534 NA
#> isolated_time
#> <num>
#> 1: 7.479154
#> 2: 11.923502
#> 3: 15.219283
#> 4: 4.397555
#> 5: 18.466834