Given an initial pretest probability, and assuming symptoms never arise, with each passing day the pretest probability will be lower, given the person did not experience symptoms. This returns a vector of posttest probabilities which takes all of the above into account, assuming a negative test on each day. Note this is not a time series, and does not reflect if serial testing were done each day and assumes testing was only done once.

posttest_series(pre0, asympt, days = 14, mu = 1.63, sigma = 0.5, sens, spec)

Arguments

pre0 The pretest probability on day 0 (at exposure) The proportion of infected patients expected to remain asymptomatic throughout the course of infection Days since exposure for calculation range The mean of a lognormal distribution that approximates the incubation period for COVID-19. E.g. 1.63 (see reference). The standard deviation of a lognormal distribution that approximates the incubation period for COVID-19. E.g. 0.5 (see reference). A vector of sensitivities by day since exposure The test specificity

Value

A vector of posttest probabilities