SMILE main function — smile

This function encompasses the original functions and assumptions. It outputs a time series for each of the compartments given a set of parameters.

Usage

smile_main(
  b0,
  b1,
  period,
  theta,
  tau,
  years,
  alpha = 1/52,
  zeta_novax = 0.88,
  gamma = 0.9868,
  sigmaa = 1,
  psi = 1,
  N1 = 5000,
  K = 5000,
  vax = NULL,
  beta_0 = NULL,
  beta_1 = NULL,
  b_fixed = NULL,
  age_struc = TRUE,
  stochastic = FALSE,
  LIZ_init = 1,
  rho_pop = NULL,
  output_df = FALSE
)

Arguments

b0: strength of seasonality parameter
b1: strength of seasonality parameter
period: periodicity of the infection in weeks
theta: dispersion effort parameter
tau: dispersion effort parameter
years: number of years to run the simulation
alpha: probability of transitioning from immune to susceptible in one week timestep
zeta_novax: probability of becoming immune after infection (fixed when no vaccination)
gamma: spore persistence rate
sigmaa: rate of death by other causes than disease
psi: number of spores per carcass
N1: starting population size
K: carrying capacity for population dynamics
vax: vaccination rates for each year
beta_0: survival parameter
beta_1: vaccine survival parameter
b_fixed: Number of infections caused by one LIZ when dispersion effort is zero and assume no seasonality
age_struc: default is TRUE, if set to false, no population dynamics are considered
stochastic: default is FALSE, so the simulations are deterministic
LIZ_init: Initial number of carcasses, set to default 1
rho_pop: average reproduction rate to be used when simulating with population dynamics
output_df: if set to TRUE, will return a dataframe instead of a list

Value

description

Examples

head(SMILE::smile_main(-30, 0.85, 3*52, 10, 10, 10, output_df = TRUE))
#>   week    S M I L        E
#> 1    1 5000 0 0 1 1.000000
#> 2    2 5000 0 0 0 1.986800
#> 3    3 5000 0 0 0 1.960574
#> 4    4 5000 0 0 0 1.934695
#> 5    5 5000 0 0 0 1.909157
#> 6    6 5000 0 0 0 1.883956