surv_adjusted_prevalence: Combined design-weighted and delay-adjusted prevalence

In survinger: Design-Adjusted Inference for Pathogen Lineage Surveillance

Combined design-weighted and delay-adjusted prevalence

Description

Simultaneously corrects for unequal sequencing rates and right-truncation from reporting delays.

Usage

## S3 method for class 'surv_adjusted'
print(x, ...)

## S3 method for class 'surv_adjusted'
as.data.frame(x, ...)

surv_adjusted_prevalence(
  design,
  delay_fit,
  lineage,
  time = "epiweek",
  prevalence_method = "hajek",
  nowcast_method = "direct",
  conf_level = 0.95,
  bootstrap_n = 0L
)

Arguments

x	Object to print.
...	Additional arguments (unused).
design	A surv_design object.
delay_fit	A surv_delay_fit object.
lineage	Character. Target lineage.
time	Character. Default "epiweek".
prevalence_method	Character. Default "hajek".
nowcast_method	Character. Default "direct".
conf_level	Numeric. Default 0.95.
bootstrap_n	Integer. 0 for delta method, >0 for bootstrap. Default 0.

Value

Invisibly returns the input object.

A surv_adjusted object.

Examples

sim <- surv_simulate(n_regions = 3, n_weeks = 12, seed = 1)
d <- surv_design(sim$sequences, ~ region,
                 sim$population[c("region", "seq_rate")], sim$population)
delay <- surv_estimate_delay(d)
adj <- surv_adjusted_prevalence(d, delay, "BA.2.86")
print(adj)

survinger documentation built on April 27, 2026, 9:10 a.m.