Simulates multiple cohorts in a cross-sectional framework.

Source: R/simulate_cross_sectional.R

Simulates multiple cohorts in a cross-sectional framework.

simulate_cross_sectional(
  parTab,
  n_indiv,
  buckets = 12,
  strainIsolationTimes,
  samplingTimes,
  antigenicMap,
  ageMin = 5,
  ageMax = 80,
  attackRates,
  group = 1,
  sampleSensoring = 0,
  titreSensoring = 0
)

Arguments

parTab

the full parameter table controlling parameter ranges and values
n_indiv

number of individuals to simulate
strainIsolationTimes

vector of strain circulation times
samplingTimes

possible sampling times for the individuals
antigenicMap

the raw antigenic map with colnames x_coord, y_coord and inf_times
ageMin

minimum age to simulate
ageMax

maximum age to simulate
attackRates

a vector of attackRates to be used in the simulation
group

which group index to give this simulated data
titreSensoring

what proportion of titres are randomly missing?

Value

a list with: 1) the data frame of titre data as returned by simulate_group; 2) a matrix of infection histories as returned by simulate_infection_histories; 3) a vector of ages