library(dplyr)
xs_data <-
sees_pop_data_pk_100
curve <-
typhoid_curves_nostrat_100 %>%
filter(antigen_iso %in% c("HlyE_IgA", "HlyE_IgG"))
noise <-
example_noise_params_pk
# estimate seroincidence
est2 <- est.incidence.by(
strata = c("catchment"),
pop_data = xs_data,
curve_params = curve,
noise_params = noise,
antigen_isos = c("HlyE_IgG", "HlyE_IgA"),
#num_cores = 8 # Allow for parallel processing to decrease run time
)
# calculate summary statistics for the seroincidence object
summary(est2)
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