local_prevalence: Estimate local prevalence using both targeted and randomised...

In alan-turing-institute/prevdebiasr: Estimate Local Prevalence Using Targeted And Randomised Testing Data

Description

Estimate local prevalence using both targeted and randomised testing data

Usage

local_prevalence(
  test_df,
  control = get_control_parameters(),
  imperfect = TRUE,
  type = "PCR_positive"
)

Arguments

test_df	A data.frame with the following columns Nt: Total number of targeted tests nt: Number of targeted tests returning positive Nr: Total number of randomised tests nr: Number of randomised tests returning positive M: Population of local area delta_prior_mean: Prior mean of bias parameter delta_prior_sd: Prior standard deviation of bias parameter alpha: Alpha parameter of beta-binomial prior on probability of infectious given PCR positive beta: Beta parameter of beta-binomial prior on probability of infectious given PCR positive
control	A list of control parameters defined via get_control_parameters
imperfect	Logical, whether to account for imperfect testing
type	One of PCR_positive or Infectious

alan-turing-institute/prevdebiasr documentation built on Dec. 19, 2021, 12:22 a.m.