Probability of transmission assuming multiple-transmission and multiple-linkage

Source: R/prob_trans_mtml.R

[Deprecated] This function calculates the probability that two cases are linked by direct transmission given that they have been linked by phylogenetic criteria. The multiple-transmission and multiple-linkage method assumes the following:

  1. Each case \(i\) is, on average, the infector of R cases in the population (\(N\))

  2. Each case \(i\) is allowed to be linked by the linkage criteria to multiple cases \(j\) in the sampled population (\(M\)).

  3. Linkage events are independent of one another (i.e, linkage of case \(i\) to case \(j\) has no bearing on linkage of case \(i\) to any other sample).

prob_trans_mtml(eta, chi, rho, M, R)

Arguments

eta

scalar or vector giving the sensitivity of the linkage criteria

chi

scalar or vector giving the specificity of the linkage criteria

rho

scalar or vector giving the proportion of the final outbreak size that is sampled

M

scalar or vector giving the number of cases sampled

R

scalar or vector giving the effective reproductive number of the pathogen

Value

scalar or vector giving the probability of transmission between two cases given linkage by phylogenetic criteria

See also

Other prob_trans: prob_trans_mtsl(), prob_trans_stsl()

Author

John Giles, Shirlee Wohl, and Justin Lessler

Examples

# Perfect sensitivity and specificity
prob_trans_mtml(eta=1, chi=1, rho=0.5, M=100, R=1)
#> Warning: `prob_trans_mtml()` was deprecated in phylosamp 1.0.0.
#> ℹ Please use `translink_prob_transmit_mtml()` instead.
#> Warning: The `eta` argument of `prob_trans_mtml()` is deprecated as of phylosamp 1.0.0.
#> ℹ Please use the `sensitivity` argument of `translink_prob_transmit_mtml()`
#>   instead.
#> Warning: The `chi` argument of `prob_trans_mtml()` is deprecated as of phylosamp 1.0.0.
#> ℹ Please use the `specificity` argument of `translink_prob_transmit_mtml()`
#>   instead.
#> [1] 1

prob_trans_mtml(eta=0.99, chi=0.9, rho=1, M=50, R=1)
#> [1] 0.2964072

prob_trans_mtml(eta=0.99, chi=0.9, rho=0.5, M=100, R=1)
#> [1] 0.09175162