Run a single instance of the branching process model

outbreak_model(
  num.initial.cases = NULL,
  prop.ascertain = NULL,
  cap_max_days = NULL,
  cap_cases = NULL,
  r0isolated = NULL,
  r0community = NULL,
  r0subclin = NULL,
  disp.iso = NULL,
  disp.com = NULL,
  disp.subclin = NULL,
  k,
  delay_shape = NULL,
  delay_scale = NULL,
  prop.asym = NULL,
  quarantine = NULL
)

Arguments

num.initial.cases: The number of initial or starting cases which are all assumed to be missed.
prop.ascertain: numeric proportion of infectious contacts ascertained by contact tracing (must be 0<=x<=1)
cap_max_days: Stop the simulation when this many days is reached.
cap_cases: Stop the simulation when this many cases is reached.
r0isolated: numeric reproduction number for isolated cases (must be >0)
r0community: numeric reproduction number for non-isolated cases (must be >0)
r0subclin: numeric reproduction number for sub-clinical non-isolated cases (must be >0)
disp.iso: numeric dispersion parameter for isolated cases (must be >0)
disp.com: numeric dispersion parameter for non-isolated cases (must be >0)
disp.subclin: numeric dispersion parameter for sub-clincial non-isolated cases (must be >0)
k: numeric skew parameter for sampling the serial interval from the incubation period
delay_shape: numeric shape parameter of delay distribution
delay_scale: numeric scale parameter of delay distribution
prop.asym: proportion of cases that are completely asymptomatic.
quarantine: logical whether quarantine is in effect, if TRUE then traced contacts are isolated before symptom onset

Value

data.table of cases by week, cumulative cases, and the effective reproduction number of the outreak

Author

Joel Hellewell

Examples


if (FALSE) {
incfn <- dist_setup(dist_shape = 2.322737,dist_scale = 6.492272)
# delay distribution sampling function
delayfn <- dist_setup(2, 4)
# generate initial cases
case_data <- outbreak_setup(num.initial.cases = 5,
                            incfn=incfn,
                            delayfn = delayfn,
                            k=1.95,
                            prop.asym=0)
# generate next generation of cases
case_data <- outbreak_step(case_data = case_data,
                           disp.iso = 1,
                           disp.com = 0.16,
                           disp.subclin = 0.16,
                           r0isolated = 0,
                           r0community = 2.5,
                           r0subclin = 1.25,
                           prop.asym = 0,
                           incfn = incfn,
                           delayfn = delayfn,
                           prop.ascertain = 0,
                           k = 1.95,
                           quarantine = FALSE)
}