vartrack_prob_detect {phylosamp}

Calculate the probability of detecting a variant given a sample size

Description

This function calculates the probability of detecting the presence of a variant given a sample size and sampling strategy.

Usage

vartrack_prob_detect(
  n,
  t = NA,
  p_v1 = NA,
  omega,
  p0_v1 = NA,
  r_v1 = NA,
  c_ratio = 1,
  sampling_freq
)

Arguments

n

sample size (either of cross-section or per timestep)

t

time step number (e.g., days) at which variant should be detected by. Default = NA (either 't' or 'p_v1' should be provided, not both)

p_v1

the desired prevalence to detect a variant by. Default = NA (either 't' or 'p_v1' should be provided, not both)

omega

probability of sequencing (or other characterization) success

p0_v1

initial variant prevalence (# introductions / infected population size)

r_v1

logistic growth rate

c_ratio

coefficient of detection ratio, calculated as the ratio of the coefficients of variant 1 to variant 2. Default = 1 (no bias)

sampling_freq

the sampling frequency (must be either 'xsect' or 'cont')

Value

scalar of detection probability

Author(s)

Shirlee Wohl, Elizabeth C. Lee, Bethany L. DiPrete, and Justin Lessler

See Also

Other variant detection functions: vartrack_prob_detect_cont(), vartrack_prob_detect_xsect(), vartrack_samplesize_detect_cont(), vartrack_samplesize_detect_xsect(), vartrack_samplesize_detect()

Other variant tracking functions: vartrack_cod_ratio(), vartrack_prob_detect_cont(), vartrack_prob_detect_xsect(), vartrack_prob_prev_xsect(), vartrack_prob_prev(), vartrack_samplesize_detect_cont(), vartrack_samplesize_detect_xsect(), vartrack_samplesize_detect(), vartrack_samplesize_prev_xsect(), vartrack_samplesize_prev()

Examples

# Cross-sectional sampling
vartrack_prob_detect(p_v1 = 0.02, n = 100, omega = 0.8, c_ratio = 1, sampling_freq = 'xsect')

# Periodic sampling
vartrack_prob_detect(n = 158, t = 30, omega = 0.8, p0_v1 = 1/10000, 
r_v1 = 0.1, c_ratio = 1, sampling_freq = 'cont')