simulate_serosurvey_general: Simulate serosurvey data based on general serocatalytic...

In serofoi: Bayesian Estimation of the Force of Infection from Serological Data

Simulate serosurvey data based on general serocatalytic model.

Description

This simulation method assumes only that the model system can be written as a piecewise-linear ordinary differential equation system.

Usage

simulate_serosurvey_general(
  construct_A_fun,
  calculate_seroprev_fun,
  initial_conditions,
  survey_features,
  ...
)

Arguments

construct_A_fun	A function that constructs a matrix that defines the multiplier term in the linear ODE system.
calculate_seroprev_fun	A function which takes the state vector and returns the seropositive fraction.
initial_conditions	The initial state vector proportions for each birth cohort.
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 ⁠)⁠.
...	Additional parameters for construct_A_fun

Value

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

Examples

foi_df_time <- data.frame(
  year = seq(1946, 2025, 1),
  foi = c(rep(0, 40), rep(1, 40))
)

foi_df_age <- data.frame(
  age = 1:80,
  foi = 2 * dlnorm(1:80, meanlog = 3.5, sdlog = 0.5)
)

# generate age and time dependent FoI from multipliers
foi_age_time <- expand.grid(
  year = foi_df_time$year,
  age = foi_df_age$age
) |>
  dplyr::left_join(foi_df_age, by = "age") |>
  dplyr::rename(foi_age = foi) |>
  dplyr::left_join(foi_df_time, by = "year") |>
  dplyr::rename(foi_time = foi) |>
  dplyr::mutate(foi = foi_age * foi_time) |>
  dplyr::select(-c("foi_age", "foi_time"))

# create survey features for simulating
max_age <- 80
n_sample <- 50
survey_features <- data.frame(
  age_min = seq(1, max_age, 5),
  age_max = seq(5, max_age, 5)) |>
  dplyr::mutate(n_sample = rep(n_sample, length(age_min))
  )

# simulate survey from age and time FoI
serosurvey <- simulate_serosurvey(
  model = "age-time",
  foi = foi_age_time,
  survey_features = survey_features
)

serofoi documentation built on April 3, 2025, 11:40 p.m.