CDC FluSurv flu hospitalizations — pub

API docs: https://cmu-delphi.github.io/delphi-epidata/api/flusurv.html.

Obtain information on influenza hospitalization rates from the Center of Disease Control.

Usage

pub_flusurv(
  locations,
  epiweeks = "*",
  ...,
  issues = NULL,
  lag = NULL,
  fetch_args = fetch_args_list()
)

Arguments

locations: character. List of locations to fetch. See geographic codes for details.
epiweeks: timeset. Epiweeks to fetch. Supports epirange() and defaults to all ("*") dates. Format as epirange(startweek, endweek), where startweek and endweek are of the form YYYYWW (string or numeric).
...: not used for values, forces later arguments to bind by name
issues: timeset. Optionally, the issue(s) of the data to fetch. See the "Data Versioning" section for details.
lag: integer. Optionally, the lag of the issues to fetch. See the "Data Versioning" section for details.
fetch_args: fetch_args. Additional arguments to pass to fetch(). See fetch_args_list() for details.

Value

tibble::tibble

Details

The list of location argument can be found in https://github.com/cmu-delphi/delphi-epidata/blob/main/labels/flusurv_locations.txt.

Data Versioning

Several endpoints support retrieving historical versions of the data. The following parameters control this and are mutually exclusive (only one can be provided at a time).

as_of: (Date) Retrieve the data as it was on this date.
issues: timeset Retrieve data from a specific issue date or range of dates.
lag: (integer) Retrieve data with a specific lag from its issue date.

If none of these is specified, the most recent version of the data is returned.

See vignette("versioned-data") for details and more ways to specify versioned data.

Examples


pub_flusurv(locations = "ca", epiweeks = epirange(201701, 201801))
#> # A tibble: 31 × 34
#>    release_date location season  issue      epiweek      lag rate_age_0
#>    <date>       <chr>    <chr>   <date>     <date>     <dbl>      <dbl>
#>  1 2025-11-03   CA       2016-17 2025-09-14 2017-01-01   454        3.4
#>  2 2025-11-03   CA       2016-17 2025-09-14 2017-01-08   453        2.9
#>  3 2025-11-03   CA       2016-17 2025-09-14 2017-01-15   452        3.4
#>  4 2025-11-03   CA       2016-17 2025-09-14 2017-01-22   451        2  
#>  5 2025-11-03   CA       2016-17 2025-09-14 2017-01-29   450        2  
#>  6 2025-11-03   CA       2016-17 2025-09-14 2017-02-05   449        2  
#>  7 2025-11-03   CA       2016-17 2025-09-14 2017-02-12   448        2  
#>  8 2025-11-03   CA       2016-17 2025-09-14 2017-02-19   447        0.5
#>  9 2025-11-03   CA       2016-17 2025-09-14 2017-02-26   446        2  
#> 10 2025-11-03   CA       2016-17 2025-09-14 2017-03-05   445        0.5
#> # ℹ 21 more rows
#> # ℹ 27 more variables: rate_age_1 <dbl>, rate_age_2 <dbl>, rate_age_3 <dbl>,
#> #   rate_age_4 <dbl>, rate_overall <dbl>, rate_age_5 <dbl>, rate_age_6 <dbl>,
#> #   rate_age_7 <dbl>, rate_age_18t29 <dbl>, rate_age_30t39 <dbl>,
#> #   rate_age_40t49 <dbl>, rate_age_5t11 <dbl>, rate_age_12t17 <dbl>,
#> #   rate_age_lt18 <dbl>, rate_age_gte18 <dbl>, rate_age_1t4 <dbl>,
#> #   rate_age_gte75 <dbl>, rate_age_0tlt1 <dbl>, rate_race_white <dbl>, …