scenario_sim: Run a specified number of simulations with identical...
In lgs85/covidsch: School-based network model for COVID-19

Description Usage Arguments Value Author(s) Examples

Run a specified number of simulations with identical parameters

scenario_sim(
  n.sim = 1,
  net,
  df,
  prop.ascertain,
  cap_max_days,
  R,
  presymrate,
  delay_shape,
  delay_scale,
  num.initial.cases,
  asym.adult,
  asym.child,
  asym.adult.inf,
  sym.child.inf,
  asym.child.inf,
  scenario,
  outside,
  sensitivity = "high",
  testing = "none",
  output = "daily",
  cap_max_tests = NULL
)

`n.sim`	number of simulations to run
`net`	network from which to sample cases
`prop.ascertain`	Probability that cases are ascertained by contact tracing
`cap_max_days`	Maximum number of days to run process for
`R`	scaling factor for infection probability
`presymrate`	rate of presymptomatic transmission (must be 0 <= x <= 1)
`delay_shape`	shape of distribution for delay between symptom onset and isolation
`delay_scale`	scale of distribution for delay between symptom onset and isolation
`num.initial.cases`	Initial number of cases in each initial cluster (must be 0 <= x <= 1)
`scenario`	character - must be either ("nothing","isolation","primary_quarantine", or "secondary_quarantine")
`outside`	infection rate from outside the network (must be 0 <= x <= 1)
`sensitivity`	character - must be "high" or "low"
`testing`	character - must be "realistic", "random" or "none"
`cap_max_tests`	integer - max number of daily tests. Only use if testing != "none"
`prop.asym`	proportion of asymptomatic cases (must be 0 <= x <= 1)

data.frame of weekly cases, isolations, quarantines and tests for each simulation

Joel Hellewell

Lewis Spurgin

## Not run: 
res <- scenario_sim(n.sim = 5,
net = haslemere,
prop.ascertain = 0.8,
cap_max_days = 69,
R = 6.5,
presymrate = 0.4,
delay_shape = 1,
delay_scale = 1.4,
num.initial.cases = 1,
prop.asym = 0.4,
scenario = "nothing",
outside = 0.001,
sensitivity = "high",
testing = "none")

## End(Not run)