fiphde 2.1.0
New features
Extended time series and augumented data
As of this release, the package now includes internal package datasets for an extended and augmented NHSN flu hospitalization time series (fiphde:::nhsn_imputed and fiphde:::nhsn_floom). The extended time series was created using methods published in Benefield et al. (2024). The augmentation stitches together the extended time series (prior to 2020) and NHSN reporting (2020-2024), with weeks between April and November 2024 filled using an imputation approach due to limited reporting in this window. The script to create the final dataset is available in the package source at data-raw/floom.R.
Functionality to retrieve data from new NHSN API
In November 2024, the NHSN weekly respiratory hospitalization metrics began being reported via a new API. The "preliminary" and "final" data are now aggregated to the week and reported at distinct endpoints. We have included the get_nhsn_weekly() and prep_nhsn_weekly() functions to retrieve and format data from these endpoints.
Updated categorical rate trend thresholds for 2024-25 flu season
The FluSight challenge updated the thresholds for categorical rate changes in the 2024-25 season (see https://github.com/cdcepi/Flusight-forecast-data/blob/master/data-experimental/README.md for more details). This release brings in a new crosswalk file to apply cutoffs for categorical thresholds and implements corresponding logic in the forecast_categorical() function.
More options for FluSurv-NET data retrieval
The get_cdc_hosp() function now includes an option to either retrieve FluSurv-NET reporting from the the RESP-NET API or the FluView API.
Bug fixes
Incorrect column names for hospitalization retrival function output
Previously, the get_cdc_hosp() reversed the names of the columns containing the dates for the start and end of the given epiweek. This release addresses that issue, ensuring that all columns in the get_cdc_hosp() output are named correctly.
Miscellaneous fixes for documentation and examples
We addressed multiple instances of unclear or misspelled documentation and examples that were failing, all of which were marked as "not run" and therefore were not flagged by R CMD CHECK.