calc_dist: Calculate the Steady-State Joint Distribution for a...

In jesse-smith/covidscreen: COVID-19 Asymtomatic Screening Strategy Assessment

Calculate the Steady-State Joint Distribution for a Population

Description

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

Usage

calc_dist(
  vac = list(p_comm = 0.5, p_org = 0.5, eff = 0.5),
  inf = list(p_incid = 0.001, 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 = 1/7, 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 Proportion of vaccinated infections who are symptomatic p_inf_unvac Proportion of unvaccinated infections who are symptomatic p_uninf 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

Value

A 'data.table'

jesse-smith/covidscreen documentation built on June 15, 2022, 7:46 p.m.