Add Support For NHSN PRISM Thresholds

[O957]

This PR:

• ...

[O957]

An example for prism_thresholds and get_prism_cutpoints.

pkgload::load_all(".")

str(prism_thresholds, max.level = 1)
lapply(prism_thresholds, dim)

# List of 2
#  $ nssp: num [1:6, 1:4, 1:53, 1:2] 0 0.12 0.158 0.195 0.233 ...
#   ..- attr(*, "dimnames")=List of 4
#  $ nhsn: num [1:6, 1:3, 1:49, 1, 1:2] 0 15 22 40 50.9 ...
#   ..- attr(*, "dimnames")=List of 5

wa_flu_nhsn <- get_prism_cutpoints("WA", "Influenza", signal = "NHSN")
print(wa_flu_nhsn)

# [[1]]
#    very_low         low    moderate        high   very_high upper_bound
#     0.00000    80.49482   184.53374   657.32177   928.29039         Inf

wa_flu_nhsn_rate <- get_prism_cutpoints(
  "WA",
  "Influenza",
  signal = "NHSN",
  unit = "rate"
)
print(wa_flu_nhsn_rate)

# [[1]]
#    very_low         low    moderate        high   very_high upper_bound 
#    0.000000    1.036759    2.376762    8.466189   11.956217         Inf 

wa_flu_nssp <- get_prism_cutpoints("WA", "Influenza", signal = "NSSP")
print(wa_flu_nssp)

# [[1]]
#    prop_very_low         prop_low    prop_moderate        prop_high 
#      0.000000000      0.002766458      0.030385827      0.058005195 
#   prop_very_high prop_upper_bound 
#      0.085624564      1.000000000 

[O957]

Same r example from before but without unit = "rate"

pkgload::load_all(".")

str(prism_thresholds, max.level = 1)
lapply(prism_thresholds, dim)

# List of 2
#  $ nssp: num [1:6, 1:4, 1:53, 1:2] 0 0.12 0.158 0.195 0.233 ...
#   ..- attr(*, "dimnames")=List of 4
#  $ nhsn: num [1:6, 1:3, 1:49, 1] 0 2.11 3.09 5.62 7.15 ...
#   ..- attr(*, "dimnames")=List of 4

wa_flu_nhsn <- get_prism_cutpoints("WA", "Influenza", signal = "NHSN")
print(wa_flu_nhsn)

# [[1]]
#    very_low         low    moderate        high   very_high upper_bound
#     0.00000    80.49482   184.53374   657.32177   928.29039         Inf

wa_flu_nssp <- get_prism_cutpoints("WA", "Influenza", signal = "NSSP")
print(wa_flu_nssp)

# [[1]]
#    prop_very_low         prop_low    prop_moderate        prop_high
#      0.000000000      0.002766458      0.030385827      0.058005195
#   prop_very_high prop_upper_bound
#      0.085624564      1.000000000

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 75.22%. Comparing base (ee77c4a) to head (0cd3719).

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #251      +/-   ##
==========================================
+ Coverage   74.92%   75.22%   +0.30%     
==========================================
  Files          36       36              
  Lines        2042     2067      +25     
==========================================
+ Hits         1530     1555      +25     
  Misses        512      512              

☔ View full report in Codecov by Harness.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

[dylanhmorris]

Flagging that I've added this requirement to the issue @O957

The signal argument should be vectorized, just as the location and disease arguments are.

[dylanhmorris]

Thanks @O957. A few more changes needed but I think this can land today.

[dylanhmorris]

Thanks @O957!

[dylanhmorris]

Caught one thing.

[dylanhmorris]

Thanks @O957!