simulate_SeroData: Simulate a serological survey

In nathoze/Rsero: Estimate the annual force of infection using serological data

Simulate a serological survey

Description

Simulate a serological survey, based on years of epidemics and force of infection.

Usage

simulate_SeroData(
  number_samples = 500,
  equal_number = FALSE,
  age_class = 1,
  max_age = 70,
  sampling_year = 2019,
  epidemic_years = c(2000, 1987, 1982),
  foi = c(0.3, 0.2, 0.4),
  location = NULL,
  sex = NULL,
  category = "Category 1",
  se = 1,
  sp = 1,
  rho = 0
)

Arguments

number_samples	integer. The number of individuals in the simulated serological survey. Default = 500.
equal_number	boolean. If FALSE, draw random ages with a uniform distribution between 1 and max_age. if TRUE, generates a SeroData object with an equal distribution of the ages. Default = FALSE.
age_class	integer. The length in years of the age classes. Default = 1.
max_age	integer. The maximal age. Default = 70.
sampling_year	integer. Default = 2019.
epidemic_years	numeric. A vector with the years where the force of infection is positive. The force of infection at the non specified years is equal to zero. Default = c(2000,1987,1982).
foi	numeric. The force of infection at the years defined in epidemic_years. It must be the same size as epidemic_years. Default = c(0.3,0.2,0.4).
location	An optional character factor defining the sampling location. It can be a single chain of characters or a vector of the same size as the number of sampled individuals. Default = NULL.
sex	An optional character factor defining the sex of the individuals. It can be a single chain of characters or a vector of the same size as the number of sampled individuals. Default = NULL.
se	numeric, between 0 and 1. Sensitivity of the assay. Default = 1.
sp	numeric, between 0 and 1. Specificity of the assay. Default = 1.
rho	numeric, 0 or positive. Seroreversion rate. Default = 0.

Value

An object of the class SeroData.

Author(s)

Nathanael Hoze [e-mail]

See Also

SeroData Define the format of the serological data.

Examples

## Example 1: Simulates a serological survey taken in a population that experienced
## a series of three outbreaks in 1972, 1988 and 1996. 

data = simulate_SeroData(number_samples = 1000,
age_class = 1,
sampling_year = 2015,
max_age = 50,
epidemic_years = c(1996,1988,1972),
foi = c(0.2,0.1,0.3),
se = 1)

seroprevalence(data)


## Example 2: 500 individuals sampled in 2019, in a population that experienced two epidemics, in 1962
## and 2012.
## The assay has a sensitivity of 0.9. 
years =  seq(1962,2012)
alpha=c(0.25, 0.1)
T=c(1974, 2000)
beta=c(1,0.5)
FOI = alpha[1]*exp(-(years-T[1])^2/beta[1]^2) + alpha[2]*exp(-(years-T[2])^2/beta[2]^2)
data1 <- simulate_SeroData( epidemic_years = years,foi=FOI, se=0.9)
seroprevalence(data1)

## Adding another survey, sampled in 2005, where ages are categorized in 5 year groups: 
data2 <- simulate_SeroData(age_class = 5,
 epidemic_years = years,
 foi=FOI,
 se = 0.9,
 sampling_year = 2005)
data <- combine_surveys(data1,data2)
seroprevalence(data)

nathoze/Rsero documentation built on Oct. 22, 2024, 6:43 p.m.