calculate_posterior_no_infections: Negative analysis probability

In smidm: Statistical Modelling for Infectious Disease Management

Negative analysis probability

Description

Calculates the probability that nobody is infected given the negative tests.

Usage

calculate_posterior_no_infections(
  negative_persons,
  infected_persons,
  event,
  test_infos,
  test_types,
  subgroup_size,
  distribution = NULL,
  info
)

Arguments

negative_persons	Number of people without the infectious persons.
infected_persons	Number of infectious persons.
event	Characters, the name of the event, currently: "school" or "day_care_center".
test_infos	Matrix with testing information; each row gives the number of tests (1. column) and each test date (following columns) for each test group
test_types	Matrix with test day (columns) of each group (rows) and the informations about test types.
subgroup_size	Array with the number of persons per test group.
distribution	Vector, this is a placeholder
info	Dataframe, this is a placeholder

Details

The probability is based on Bayes' theorem.

Value

The probability p.

See Also

calculate_prior_infections, generate_data_extended, get_test_sensitivities and calculate_likelihood_negative_tests.

Examples

test_infos <- matrix(nrow = 2, ncol = 3)
test_infos[1,] <- c(1, 2, NA)
test_infos[2,] <- c(2, 4, 6)

test_types <- matrix(nrow = 2, ncol = 2)
test_types[1,] <- c("PCR", NA)
test_types[2,] <- c("PCR", "Antigen")

calculate_posterior_no_infections(negative_persons = 23,
                                  infected_persons = 2,
                                  event = "school",
                                  test_infos = test_infos,
                                  test_types = test_types,
                                  subgroup_size = c(3, 5))

smidm documentation built on Aug. 27, 2022, 9:06 a.m.