calculate_prior_infections: A priori probability of further Infections

In smidm: Statistical Modelling for Infectious Disease Management

A priori probability of further Infections

Description

Calculates the a priori probability of how many people are infected in one event.

Usage

calculate_prior_infections(
  negative_persons,
  infected_persons,
  event,
  p_one = NULL,
  infect_average = NULL
)

Arguments

negative_persons	Number of people without the infectious persons.
infected_persons	Number of infected people.
event	Characters, event type given as characters, currently: "school" or "day_care_center".
p_one	Number, this is a placeholder
infect_average	Number, this is a placeholder

Details

The probability is beta-binomial distributed. The values for p1 and infection_average for the events "school" and "day_care_center" are from Schoeps et al. (2021).

Value

The a priori probability y.

References

Schoeps A et al. (2021) "Surveillance of SARS-CoV-2 transmission in educational institutions, August to December 2020, Germany". Epidemiology and Infection 149, E213: 1-9.

Examples

calculate_prior_infections(negative_persons = 23,
                           infected_persons = 2,
                           event = "school")

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