Simulate serosurvey data based on various Force-of-Infection (FoI) models.

This function generates binned serosurvey data based on either a time-varying FoI model, an age-varying FoI model, or an age-and-time-varying FoI model. In all cases, it is possible to optionally include seroreversion. This function allows construction of serosurveys with binned age groups, and it generates uncertainty in the distribution of a sample size within an age bin through multinomial sampling.

Usage

simulate_serosurvey(model, foi, survey_features, seroreversion_rate = 0)

Arguments

model

A string specifying the model type which can be either '"age"', '"time"', '"age-time"'.

foi

A dataframe containing the FoI values. For time-varying models the columns should be:

year: Calendar years starting at the birth year of the oldest person and up to the time of the serosurvey
foi: Corresponding values of the FoI by year

For age-varying models the columns should be:.

age: Ages starting at 1 and up to the age of the oldest person in the serosurvey
foi: Corresponding values of the FoI by age

For age-and-time-varying models the columns should be:

age: Ages starting at 1 and up to the age of the oldest person in the serosurvey
time: Calendar years starting at the birth year of the oldest person and up to the time of the serosurvey
foi: Corresponding values of FoI by age and year

survey_features

A dataframe containing information about the binned age groups and sample sizes for each. It should contain columns:

age_min: Left limits of the age groups to be considered in the serosurvey
age_max: Right limits of the age groups to be considered in the serosurvey
n_sample: Number of samples by age group

The resulting age intervals are closed to the left [ and open to the right ).

seroreversion_rate

A non-negative value determining the rate of seroreversion (per year). Default is 0.

Value

A dataframe with simulated serosurvey data, including age group information, overall sample sizes, the number of seropositive individuals, and other survey features.

Examples

# time-varying model
foi_df <- data.frame(
  year = seq(1990, 2009, 1),
  foi = rnorm(20, 0.1, 0.01)
)
survey_features <- data.frame(
  age_min = c(1, 3, 15),
  age_max = c(2, 14, 20),
  n_sample = c(1000, 2000, 1500))
serosurvey <- simulate_serosurvey(
model = "time",
foi = foi_df,
survey_features = survey_features)

# age-varying model
foi_df <- data.frame(
  age = seq(1, 20, 1),
  foi = rnorm(20, 0.1, 0.01)
)
survey_features <- data.frame(
  age_min = c(1, 3, 15),
  age_max = c(2, 14, 20),
  n_sample = c(1000, 2000, 1500))
serosurvey <- simulate_serosurvey(
model = "age",
foi = foi_df,
survey_features = survey_features)

# age-and-time varying model
foi_df <- expand.grid(
  year = seq(1990, 2009, 1),
  age = seq(1, 20, 1)
)
foi_df$foi <- rnorm(20 * 20, 0.1, 0.01)
survey_features <- data.frame(
  age_min = c(1, 3, 15),
  age_max = c(2, 14, 20),
  n_sample = c(1000, 2000, 1500))
serosurvey <- simulate_serosurvey(
model = "age-time",
foi = foi_df,
survey_features = survey_features)