diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index d4ab5a48..7bf26f02 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -26,7 +26,7 @@ repos:
   #####
   # R
   - repo: https://github.com/lorenzwalthert/precommit
-    rev: v0.4.3.9001
+    rev: v0.4.3
     hooks:
       - id: style-files
       - id: lintr
diff --git a/hewr/R/to_epiweekly_quantile_table.R b/hewr/R/to_epiweekly_quantile_table.R
index a08353ea..b3285c94 100644
--- a/hewr/R/to_epiweekly_quantile_table.R
+++ b/hewr/R/to_epiweekly_quantile_table.R
@@ -65,7 +65,8 @@ to_epiweekly_quantiles <- function(model_run_dir,
       value_col = ".value"
     ) |>
     dplyr::mutate(
-      "location" = !!location
+      "location" = !!location,
+      "source_samples" = !!draws_file_name
     )
   message(glue::glue("Done processing {model_run_dir}"))
   return(epiweekly_quantiles)
@@ -98,7 +99,7 @@ to_epiweekly_quantile_table <- function(model_batch_dir,
                                         epiweekly_other_locations = c()) {
   model_runs_path <- fs::path(model_batch_dir, "model_runs")
 
-  locations_to_process <- fs::dir_ls(model_runs_path,
+  model_run_dirs_to_process <- fs::dir_ls(model_runs_path,
     type = "directory"
   ) |>
     purrr::discard(~ fs::path_file(.x) %in% exclude)
@@ -122,15 +123,25 @@ to_epiweekly_quantile_table <- function(model_batch_dir,
     day_of_week = 7
   )
 
-  get_location_table <- \(loc) {
-    epiweekly_other <- loc %in% epiweekly_other_locations
+  get_location_table <- \(model_run_dir) {
+    loc <- fs::path_file(model_run_dir)
+    use_epiweekly_other <- loc %in% epiweekly_other_locations
+    which_forecast <- ifelse(use_epiweekly_other,
+      "explicitly epiweekly",
+      "aggregated daily"
+    )
+    glue::glue(
+      "Using {which_forecast} non-target ED visit forecast ",
+      "for location {loc}"
+    )
+
     draws_file <- ifelse(
-      epiweekly_other,
+      use_epiweekly_other,
       "epiweekly_with_epiweekly_other_samples",
       "epiweekly_samples"
     )
     return(to_epiweekly_quantiles(
-      loc,
+      model_run_dir,
       report_date = report_date,
       max_lookback_days = 15,
       draws_file_name = draws_file,
@@ -138,16 +149,24 @@ to_epiweekly_quantile_table <- function(model_batch_dir,
     ))
   }
 
-  hubverse_table <- purrr::map(
-    locations_to_process,
+  quant_table <- purrr::map(
+    model_run_dirs_to_process,
     get_location_table
   ) |>
-    dplyr::bind_rows() |>
+    dplyr::bind_rows()
+
+  loc_sources <- quant_table |>
+    dplyr::distinct(.data$location, .data$source_samples)
+
+  hubverse_table <- quant_table |>
     forecasttools::get_hubverse_table(
       report_epiweek_end,
       target_name =
         glue::glue("wk inc {disease_abbr} prop ed visits")
     ) |>
+    dplyr::inner_join(loc_sources,
+      by = "location"
+    ) |>
     dplyr::arrange(
       .data$target,
       .data$output_type,
@@ -155,12 +174,6 @@ to_epiweekly_quantile_table <- function(model_batch_dir,
       .data$reference_date,
       .data$horizon,
       .data$output_type_id
-    ) |>
-    dplyr::mutate(other_ed_visit_forecast = ifelse(
-      .data$location %in% !!epiweekly_other_locations,
-      "direct_epiweekly_fit",
-      "aggregated_daily_fit"
-    ))
-
+    )
   return(hubverse_table)
 }
diff --git a/hewr/tests/testthat/test_to_epiweekly_quantile_table.R b/hewr/tests/testthat/test_to_epiweekly_quantile_table.R
index 15a6942b..b4600223 100644
--- a/hewr/tests/testthat/test_to_epiweekly_quantile_table.R
+++ b/hewr/tests/testthat/test_to_epiweekly_quantile_table.R
@@ -39,9 +39,20 @@ test_that("to_epiweekly_quantiles works as expected", {
     ) |> suppressMessages()
 
     expect_s3_class(result, "tbl_df")
-    expect_setequal(c(
-      "epiweek", "epiyear", "quantile_value", "quantile_level", "location"
-    ), colnames(result))
+    checkmate::expect_names(
+      colnames(result),
+      identical.to = c(
+        "epiweek",
+        "epiyear",
+        "quantile_value",
+        "quantile_level",
+        "location",
+        "source_samples"
+      )
+    )
+
+    expect_equal(draws_file_name, unique(result$source_samples))
+
     expect_gt(nrow(result), 0)
   }
 
@@ -127,7 +138,11 @@ test_that("to_epiweekly_quantiles handles missing forecast files", {
 
 
 # tests for `to_epiweekly_quantile_table`
-test_that("to_epiweekly_quantile_table handles multiple locations", {
+test_that(paste0(
+  "to_epiweekly_quantile_table ",
+  "handles multiple locations ",
+  "and multiple source files"
+), {
   batch_dir_name <- "covid-19_r_2024-12-14_f_2024-12-08_t_2024-12-14"
   tempdir <- withr::local_tempdir()
 
@@ -142,6 +157,17 @@ test_that("to_epiweekly_quantile_table handles multiple locations", {
     if (loc != "loc3") {
       disease_cols <- c(disease_cols, "prop_disease_ed_visits")
     }
+    create_tidy_forecast_data(
+      directory = loc_dir,
+      filename = "epiweekly_with_epiweekly_other_samples.parquet",
+      date_cols = seq(
+        lubridate::ymd("2024-12-08"), lubridate::ymd("2024-12-14"),
+        by = "week"
+      ),
+      disease_cols = disease_cols,
+      n_draw = 25,
+      with_epiweek = TRUE
+    )
 
     create_tidy_forecast_data(
       directory = loc_dir,
@@ -157,7 +183,10 @@ test_that("to_epiweekly_quantile_table handles multiple locations", {
   })
 
   ## should succeed despite loc3 not having valid draws with strict = FALSE
-  result_w_both_locations <- to_epiweekly_quantile_table(temp_batch_dir) |>
+  result_w_both_locations <-
+    to_epiweekly_quantile_table(temp_batch_dir,
+      epiweekly_other_locations = "loc1"
+    ) |>
     suppressMessages()
 
   ## should error if strict = TRUE because loc3 does not have
@@ -168,6 +197,44 @@ test_that("to_epiweekly_quantile_table handles multiple locations", {
     "did not find valid draws"
   )
 
+  ## should succeed with strict = TRUE if loc3 is excluded
+  alt_result_w_both_locations <- (
+    to_epiweekly_quantile_table(temp_batch_dir,
+      strict = TRUE,
+      exclude = "loc3"
+  )) |>
+    suppressMessages()
+
+  ## results should be equivalent for loc2,
+  ## but not for loc1
+  expect_equal(
+    result_w_both_locations |>
+      dplyr::filter(location == "loc2"),
+    alt_result_w_both_locations |>
+      dplyr::filter(location == "loc2")
+  )
+
+  ## check that one used epiweekly
+  ## other for loc1 while other used
+  ## default, resulting in different values
+  loc1_a <- result_w_both_locations |>
+    dplyr::filter(location == "loc1") |>
+    dplyr::pull(.data$value)
+  loc1_b <- alt_result_w_both_locations |>
+    dplyr::filter(location == "loc1") |>
+    dplyr::pull(.data$value)
+
+  ## length checks ensure that the
+  ## number of allowed equalities _could_
+  ## be reached if the vectors were mostly
+  ## or entirely identical
+  expect_gt(length(loc1_a), 10)
+  expect_gt(length(loc1_b), 10)
+  expect_lt(
+    sum(loc1_a == loc1_b),
+    5
+  )
+
   expect_s3_class(result_w_both_locations, "tbl_df")
   expect_gt(nrow(result_w_both_locations), 0)
   checkmate::expect_names(
@@ -181,20 +248,32 @@ test_that("to_epiweekly_quantile_table handles multiple locations", {
       "output_type",
       "output_type_id",
       "value",
-      "other_ed_visit_forecast"
+      "source_samples"
     )
   )
   expect_setequal(
-    c("loc1", "loc2"),
-    result_w_both_locations$location
+    result_w_both_locations$location,
+    c("loc1", "loc2")
+  )
+  expect_setequal(
+    alt_result_w_both_locations$location,
+    c("loc1", "loc2")
   )
-  expect_false("loc3" %in% result_w_both_locations$location)
 
-  result_w_one_location <- to_epiweekly_quantile_table(
-    model_batch_dir = temp_batch_dir,
-    exclude = "loc1"
-  ) |>
-    suppressMessages()
-  expect_true("loc2" %in% result_w_one_location$location)
-  expect_false("loc1" %in% result_w_one_location$location)
+  expect_setequal(
+    result_w_both_locations$source_samples,
+    c(
+      "epiweekly_samples",
+      "epiweekly_with_epiweekly_other_samples"
+    )
+  )
+
+  expect_setequal(
+    alt_result_w_both_locations$source_samples,
+    "epiweekly_samples"
+  )
+
+
+  expect_false("loc3" %in% result_w_both_locations$location)
+  expect_false("loc3" %in% alt_result_w_both_locations$location)
 })
diff --git a/pipelines/postprocess_forecast_batches.py b/pipelines/postprocess_forecast_batches.py
index f46fa6a2..a5690ce7 100644
--- a/pipelines/postprocess_forecast_batches.py
+++ b/pipelines/postprocess_forecast_batches.py
@@ -15,6 +15,7 @@
 from pathlib import Path
 
 import collate_plots as cp
+from forecasttools.utils import ensure_listlike
 
 from pipelines.hubverse_create_observed_data_tables import (
     save_observed_data_tables,
@@ -28,7 +29,16 @@ def _hubverse_table_filename(
     return f"{report_date}-" f"{disease.lower()}-" "hubverse-table.tsv"
 
 
-def create_hubverse_table(model_batch_dir_path: str | Path) -> None:
+def create_hubverse_table(
+    model_batch_dir_path: str | Path,
+    locations_exclude: str | list[str] = "",
+    epiweekly_other_locations: str | list[str] = "",
+) -> None:
+    logger = logging.getLogger(__name__)
+
+    locations_exclude = ensure_listlike(locations_exclude)
+    epiweekly_other_locations = ensure_listlike(epiweekly_other_locations)
+
     model_batch_dir_path = Path(model_batch_dir_path)
     model_batch_dir_name = model_batch_dir_path.name
     batch_info = parse_model_batch_dir_name(model_batch_dir_name)
@@ -45,13 +55,18 @@ def create_hubverse_table(model_batch_dir_path: str | Path) -> None:
             "pipelines/hubverse_create_table.R",
             f"{model_batch_dir_path}",
             f"{output_path}",
+            "--exclude",
+            f"{' '.join(locations_exclude)}",
+            "--epiweekly-other-locations",
+            f"{' '.join(epiweekly_other_locations)}",
         ],
         capture_output=True,
     )
     if result.returncode != 0:
         raise RuntimeError(
-            "create_hubverse_table: " f"{result.stdout}\n" f"{result.stderr}"
+            f"create_hubverse_table: {result.stdout}\n {result.stderr}"
         )
+
     return None
 
 
@@ -86,10 +101,16 @@ def create_pointinterval_plot(model_batch_dir_path: Path | str) -> None:
 
 
 def process_model_batch_dir(
-    model_batch_dir_path: Path, plot_ext: str = "pdf"
+    model_batch_dir_path: Path,
+    locations_exclude: str | list[str] = "",
+    epiweekly_other_locations: str | list[str] = "",
+    plot_ext: str = "pdf",
 ) -> None:
+    locations_exclude = ensure_listlike(locations_exclude)
+    epiweekly_other_locations = ensure_listlike(epiweekly_other_locations)
+
     plot_types = ["Disease", "Other", "prop_disease_ed_visits"]
-    plot_timescales = ["daily", "epiweekly", "epiweekly_other"]
+    plot_timescales = ["daily", "epiweekly", "epiweekly_with_epiweekly_other"]
     plot_yscales = ["", "log_"]
 
     plots_to_collate = [
@@ -97,14 +118,24 @@ def process_model_batch_dir(
         for p_type, p_yscale, p_timescale in itertools.product(
             plot_types, plot_yscales, plot_timescales
         )
-        if not (p_type == "Disease" and p_timescale == "epiweekly_other")
+        if not (
+            p_type == "Disease"
+            and p_timescale == "epiweekly_with_epiweekly_other"
+        )
     ]
 
     logger = logging.getLogger(__name__)
     logger.info("Collating plots...")
     cp.process_dir(model_batch_dir_path, target_filenames=plots_to_collate)
     logger.info("Creating hubverse table...")
-    create_hubverse_table(model_batch_dir_path)
+    logger.info(
+        "Using epiweekly other forecast for " f"{epiweekly_other_locations}..."
+    )
+    create_hubverse_table(
+        model_batch_dir_path,
+        locations_exclude=locations_exclude,
+        epiweekly_other_locations=epiweekly_other_locations,
+    )
     logger.info("Creating pointinterval plot...")
     create_pointinterval_plot(model_batch_dir_path)
 
@@ -112,15 +143,27 @@ def process_model_batch_dir(
 def main(
     base_forecast_dir: Path | str,
     path_to_latest_data: Path | str,
-    diseases: list[str] = ["COVID-19", "Influenza"],
+    diseases: list[str] = None,
+    locations_exclude: str | list[str] = "",
+    epiweekly_other_locations: str | list[str] = "",
 ) -> None:
+    if diseases is None:
+        diseases = ["COVID-19", "Influenza"]
+    diseases = ensure_listlike(diseases)
+    locations_exclude = ensure_listlike(locations_exclude)
+    epiweekly_other_locations = ensure_listlike(epiweekly_other_locations)
+
     logging.basicConfig(level=logging.INFO)
     logger = logging.getLogger(__name__)
     to_process = get_all_forecast_dirs(base_forecast_dir, diseases)
     for batch_dir in to_process:
         logger.info(f"Processing {batch_dir}...")
         model_batch_dir_path = Path(base_forecast_dir, batch_dir)
-        process_model_batch_dir(model_batch_dir_path)
+        process_model_batch_dir(
+            model_batch_dir_path,
+            locations_exclude=locations_exclude,
+            epiweekly_other_locations=epiweekly_other_locations,
+        )
         logger.info(f"Finished processing {batch_dir}")
     logger.info("Created observed data tables for visualization...")
     save_observed_data_tables(
@@ -157,7 +200,30 @@ def main(
             "Default 'COVID-19 Influenza' (i.e. postprocess both)."
         ),
     )
+    parser.add_argument(
+        "--locations-exclude",
+        type=str,
+        default="",
+        help=(
+            "Name(s) of locations to exclude from the hubverse table, "
+            "as a whitespace-separated string of two-letter location "
+            "codes."
+        ),
+    )
+    parser.add_argument(
+        "--epiweekly-other-locations",
+        type=str,
+        default="",
+        help=(
+            "Name(s) of locations for which to use an explicitly epiweekly "
+            "forecast of other (non-target) ED visits, as opposed to a "
+            "daily forecast aggregated to epiweekly. Locations should be "
+            "specified as a whitespace-separated string of two-letter codes."
+        ),
+    )
 
     args = parser.parse_args()
     args.diseases = args.diseases.split()
+    args.locations_exclude = args.locations_exclude.split()
+    args.epiweekly_other_locations = args.epiweekly_other_locations.split()
     main(**vars(args))