cs_dist: Calculate the Steady-State Joint Distribution for a...
In jesse-smith/covidscreen: COVID-19 Asymtomatic Screening Strategy Assessment

cs_dist

R Documentation

Calculate the Steady-State Joint Distribution for a Population

Description

cs_dist() calculates the discrete joint distribution of vaccination, infection, symptoms, tests, and detections in a population.

Usage

cs_dist(
  vac = list(p_comm = 0.5, p_org = 0.5, eff = 0.5),
  inf = list(p_incid = 0.005, t_symp = 5, t_presymp = 5),
  symp = list(p_inf_vac = 0.5, p_inf_unvac = 0.5, p_uninf = 0),
  test = list(p_symp = 1, p_asymp_vac = 0, p_asymp_unvac = 1/7),
  detect = list(sens = 0.85, spec = 1)
)

Arguments

`vac`	`[list(3)]` A named list containing vaccination parameters: p_comm `[numeric(1)]` Proportion vaccinated in the community p_org `[numeric(1)]` Proportion vaccinated in the organization of interest eff `[numeric(1)]` Vaccine efficacy
`inf`	`[list(3)]` A named list containing infection parameters: p_incid `[numeric(1)]` Proportion of community newly infected each day t_symp `[numeric(1)]` Duration of symptomatic period t_presymp `[numeric(1)]` Duration of presymptomatic period
`symp`	`[list(3)]` A named lust containing symptom parameters: p_inf_vac `[numeric(1)]` Proportion of vaccinated infections who are symptomatic p_inf_unvac `[numeric(1)]` Proportion of unvaccinated infections who are symptomatic p_uninf `[numeric(1)]` Proportion of uninfected people who are symptomatic
`test`	`[list(3)]` A named list containing testing parameters: p_symp `[numeric(1)]` Probability of being tested if symptomatic p_asymp_vac `[numeric(1)]` Probability of being tested if asymptomatic and vaccinated p_asymp_unvac `[numeric(1)]` Probability of being tested if asymptomatic and unvaccinated
`detect`	`[list(2)]` A named list containing detection parameters: sens `[numeric(1)]` Test sensitivity spec `[numeric(1)]` Test specificity