@@ -24,6 +24,9 @@ nssp_col_names <- list(
2424# ' is "2024-11-09".
2525# ' @param legacy_file Logical. Whether to write legacy
2626# ' CSV output (default: FALSE).
27+ # ' @param nssp_update_local Logical. Whether to update NSSP
28+ # ' data from local file `auxiliary-data/latest.csv`
29+ # ' (default: FALSE).
2730# '
2831# ' @return Writes `time-series.parquet` and optionally
2932# ' legacy CSV target data files to the target-data
@@ -35,7 +38,8 @@ update_hub_target_data <- function(
3538 as_of = lubridate :: today(),
3639 nhsn_first_weekending_date = lubridate :: as_date(" 2024-11-09" ),
3740 included_locations = hubhelpr :: included_locations ,
38- legacy_file = FALSE
41+ legacy_file = FALSE ,
42+ nssp_update_local = FALSE
3943) {
4044 if (! disease %in% c(" covid" , " rsv" )) {
4145 stop(" 'disease' must be either 'covid' or 'rsv'" )
@@ -90,11 +94,31 @@ update_hub_target_data <- function(
9094 )
9195 }
9296
93- hubverse_format_nssp_data <- forecasttools :: pull_data_cdc_gov_dataset(
94- dataset = " nssp_prop_ed_visits" ,
95- columns = c(nssp_col_name , " geography" ),
96- locations = " All"
97- ) | >
97+ if (nssp_update_local ) {
98+ raw_nssp_data <- forecasttools :: read_tabular(
99+ fs :: path(
100+ base_hub_path ,
101+ " auxiliary-data" ,
102+ " nssp-raw-data" ,
103+ " latest" ,
104+ ext = " csv"
105+ )
106+ ) | >
107+ dplyr :: filter(county == " All" ) | >
108+ dplyr :: select(
109+ week_end ,
110+ geography ,
111+ dplyr :: all_of(nssp_col_name )
112+ )
113+ } else {
114+ raw_nssp_data <- forecasttools :: pull_data_cdc_gov_dataset(
115+ dataset = " nssp_prop_ed_visits" ,
116+ columns = c(nssp_col_name , " geography" ),
117+ locations = " All"
118+ )
119+ }
120+
121+ hubverse_format_nssp_data <- raw_nssp_data | >
98122 dplyr :: mutate(
99123 date = lubridate :: as_date(.data $ week_end ),
100124 observation = as.numeric(.data [[nssp_col_name ]]) / 100 ,
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