diff --git a/data/data-pipeline/data_pipeline/etl/score/constants.py b/data/data-pipeline/data_pipeline/etl/score/constants.py
index 75f98bbe..0987be46 100644
--- a/data/data-pipeline/data_pipeline/etl/score/constants.py
+++ b/data/data-pipeline/data_pipeline/etl/score/constants.py
@@ -63,6 +63,9 @@ SCORE_DOWNLOADABLE_ZIP_FILE_PATH = (
 # Column subsets
 CENSUS_COUNTIES_COLUMNS = ["USPS", "GEOID", "NAME"]
 
+# Drop FIPS codes from map
+DROP_FIPS_CODES = ["66", "78"]
+
 # Percent prefixes for rounding
 PERCENT_PREFIXES_SUFFIXES = [
     "Percent",
diff --git a/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py b/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
index 8f281897..0b11c5e4 100644
--- a/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
+++ b/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
@@ -195,10 +195,11 @@ class PostScoreETL(ExtractTransformLoad):
         return de_duplicated_df
 
     def _create_tile_data(
-        self, score_county_state_merged_df: pd.DataFrame
+        self,
+        score_county_state_merged_df: pd.DataFrame,
     ) -> pd.DataFrame:
-        logger.info("Rounding Decimals")
 
+        logger.info("Rounding Decimals")
         # grab all the keys from tiles score columns
         tiles_score_column_titles = list(constants.TILES_SCORE_COLUMNS.keys())
 
@@ -207,6 +208,22 @@ class PostScoreETL(ExtractTransformLoad):
             tiles_score_column_titles
         ].copy()
 
+        # Currently, we do not want USVI or Guam on the map, so this will drop all
+        # rows with the FIPS codes (first two digits of the census tract)
+        logger.info(
+            f"Dropping specified FIPS codes from tile data: {constants.DROP_FIPS_CODES}"
+        )
+        tracts_to_drop = []
+        for fips_code in constants.DROP_FIPS_CODES:
+            tracts_to_drop += score_tiles[
+                score_tiles[field_names.GEOID_TRACT_FIELD].str.startswith(
+                    fips_code
+                )
+            ][field_names.GEOID_TRACT_FIELD].to_list()
+        score_tiles = score_tiles[
+            ~score_tiles[field_names.GEOID_TRACT_FIELD].isin(tracts_to_drop)
+        ]
+
         score_tiles[constants.TILES_SCORE_FLOAT_COLUMNS] = score_tiles[
             constants.TILES_SCORE_FLOAT_COLUMNS
         ].apply(