serofoi (version 1.0.3)

simulate_serosurvey_time: Simulate serosurvey data based on a time-varying Force-of-Infection (FoI) model.

Description

This function generates binned serosurvey data based on a time-varying FoI model, optionally including 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_time(foi, survey_features, seroreversion_rate = 0)

Value

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

Arguments

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.

Examples

# specify FOIs for each year
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_time(
foi_df, survey_features)