Random MIC Values/Disk Zones/SIR Generation

These functions can be used for generating random MIC values and disk diffusion diameters, for AMR data analysis practice. By providing a microorganism and antimicrobial drug, the generated results will reflect reality as much as possible.

Usage

random_mic(
  size = NULL,
  mo = NULL,
  ab = NULL,
  skew = "right",
  severity = 1,
  ...
)

random_disk(
  size = NULL,
  mo = NULL,
  ab = NULL,
  skew = "left",
  severity = 1,
  ...
)

random_sir(size = NULL, prob_SIR = c(0.33, 0.33, 0.33), ...)

Arguments

size:

Desired size of the returned vector. If used in a data.frame call or dplyr verb, will get the current (group) size if left blank.
mo:

Any character that can be coerced to a valid microorganism code with as.mo(). Can be the same length as size.
ab:

Any character that can be coerced to a valid antimicrobial drug code with as.ab().
skew:

Direction of skew for MIC or disk values, either "right" or "left". A left-skewed distribution has the majority of the data on the right.
severity:

Skew severity; higher values will increase the skewedness. Default is 2; use 0 to prevent skewedness.
...:

Ignored, only in place to allow future extensions.
prob_SIR:

A vector of length 3: the probabilities for "S" (1st value), "I" (2nd value) and "R" (3rd value).

Value

class mic for random_mic() (see as.mic()) and class disk for random_disk() (see as.disk())

Details

Internally, MIC and disk zone values are sampled based on clinical breakpoints defined in the clinical_breakpoints data set. To create specific generated values per bug or drug, set the mo and/or ab argument. The MICs are sampled on a log2 scale and disks linearly, using weighted probabilities. The weights are based on the skew and severity arguments:

skew = "right" places more emphasis on lower MIC or higher disk values.
skew = "left" places more emphasis on higher MIC or lower disk values.
severity controls the exponential bias applied.

Examples

random_mic(25)
#> Class <mic>
#>  [1] 1      0.032  0.064  1      0.25   0.125  >=128  0.0002 32     0.25  
#> [11] 0.008  0.125  0.001  0.032  8      >=128  0.032  0.008  8      >=128 
#> [21] 0.125  0.0001 0.5    64     1     
random_disk(25)
#> Class <disk>
#>  [1] 49 39 29 30 16 23 44 50 25 28 29 14 44 34  8 33 33 34 38 42 10 42 43 11 46
random_sir(25)
#> Class <sir>
#>  [1] I S S S R R S R I I I I S R S I S S S R R I R S I

# add more skewedness, make more realistic by setting a bug and/or drug:
disks <- random_disk(100, severity = 2, mo = "Escherichia coli", ab = "CIP")
plot(disks)

# `plot()` and `ggplot2::autoplot()` allow for coloured bars if `mo` and `ab` are set
plot(disks, mo = "Escherichia coli", ab = "CIP", guideline = "CLSI 2025")


# \donttest{
random_mic(25, "Klebsiella pneumoniae") # range 0.0625-64
#> Class <mic>
#>  [1] 256      <=0.0001 <=0.0001 0.016    1        0.016    2        8       
#>  [9] 0.5      0.004    0.032    0.004    0.001    0.001    0.064    0.002   
#> [17] 0.032    0.004    0.008    16       0.125    <=0.0001 0.001    0.008   
#> [25] 0.001   
random_mic(25, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
#> Class <mic>
#>  [1] 0.5    <=0.25 0.5    4      1      1      0.5    0.5    0.5    <=0.25
#> [11] 0.5    0.5    2      1      <=0.25 <=0.25 8      <=0.25 1      1     
#> [21] <=0.25 0.5    16     2      0.5   
random_mic(25, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
#> Class <mic>
#>  [1] 0.125  0.125  0.125  0.125  0.125  >=0.25 0.125  0.125  0.125  0.125 
#> [11] >=0.25 0.125  >=0.25 0.125  0.125  0.125  >=0.25 0.125  >=0.25 >=0.25
#> [21] >=0.25 0.125  0.125  0.125  >=0.25

random_disk(25, "Klebsiella pneumoniae") # range 8-50
#> Class <disk>
#>  [1] 18 32 21 19 23 10 30 18 22 34 19 32 28 18 25  7 27 23 28 17 29 18 22 28 23
random_disk(25, "Klebsiella pneumoniae", "ampicillin") # range 11-17
#> Class <disk>
#>  [1] 22 18 13 22 17 12 20 20 16 20 22 22 18 20 20 22 22 16 13 17 15 17 16 22 15
random_disk(25, "Streptococcus pneumoniae", "ampicillin") # range 12-27
#> Class <disk>
#>  [1] 31 30 30 28 24 35 28 34 28 29 27 29 24 21 13 16 34 19 26 20 27 32 32 24 26
# }

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