Set up initial cases for branching process

outbreak_setup(num.initial.cases, incfn, delayfn, k, prop.asym)

Arguments

num.initial.cases: a nonnegative integer scalar: number of initial or starting cases which are all assumed to be missed.
incfn: a function that samples from incubation period Weibull distribution; generated using dist_setup()
delayfn: a function that samples from the onset-to-hospitalisation delay Weibull distribution; generated using dist_setup()
k: a numeric scalar: skew parameter for sampling the serial interval from the incubation period
prop.asym: a nonnegative numeric scalar: proportion of cases that are completely asymptomatic (sublinical) (between 0 and 1)

Value

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

$exposure: numeric
$asym: logical
$caseid: integer
$infector: numeric
$missed: logical
$onset: numeric
$new_cases: logical
$isolated_time: numeric
$isolated: logical

Author

Joel Hellewell

Examples

# incubation period sampling function
incfn <- dist_setup(dist_shape = 2.32, dist_scale = 6.49)
# delay distribution sampling function
delayfn <- dist_setup(dist_shape = 1.65, dist_scale = 4.28)
out <- outbreak_setup(
  num.initial.cases = 1,
  incfn = incfn,
  delayfn = delayfn,
  k = 1.95,
  prop.asym = 0
)
out
#>    exposure   asym caseid infector missed    onset new_cases isolated_time
#>       <num> <lgcl>  <int>    <num> <lgcl>    <num>    <lgcl>         <num>
#> 1:        0  FALSE      1        0   TRUE 8.118098        NA      9.679915
#>    isolated
#>      <lgcl>
#> 1:    FALSE