diff --git a/pygadm/__init__.py b/pygadm/__init__.py
index 193927f..0bd3c74 100644
--- a/pygadm/__init__.py
+++ b/pygadm/__init__.py
@@ -229,18 +229,32 @@ def _items(self, name: str = "", admin: str = "", content_level: int = -1) -> gp
             )
 
         level_gdf = gpd.GeoDataFrame.from_features(data)
-        level_gdf.rename(columns={"COUNTRY": "NAME_0"}, inplace=True)
+        level_gdf = level_gdf.rename(columns={"COUNTRY": "NAME_0"})
+
+        # countries can embed multiple iso codes as some places are disputed so we need to gather them
+        # from the geojson file
+        isos = level_gdf.GID_0.dropna().unique()
 
         # workaround for the wrong naming convention in the geojson files
         # https://gis.stackexchange.com/questions/467848/how-to-get-back-spaces-in-administrative-names-in-gadm-4-1
         # it should disappear in the next version of GADM
         # we are forced to retrieve all the names from the df (sourced from.gpkg) to replace the one from
-        # the geojson that are all in camelCase
-        complete_df = Names(admin=iso_3, content_level=content_level, complete=True)
+        # the geojson that are all in camelCase.
+        df_list = [Names(admin=iso, content_level=content_level, complete=True) for iso in isos]
+        complete_df = pd.concat(df_list)
         for i in range(int(content_level) + 1):
             level_gdf.loc[:, f"NAME_{i}"] = complete_df[f"NAME_{i}"].values
 
-        gdf = level_gdf[level_gdf[column.format(level)].str.fullmatch(id, case=False)]
+        df_list = [Names(admin=iso, content_level=content_level, complete=True) for iso in isos]
+        complete_df = pd.concat(df_list)
+        # GID columns to merge on; they (should) match exactly
+        shared_cols = [f"GID_{i}" for i in range(int(content_level) + 1)]
+        # Camel-case columns to drop
+        drop_cols = [f"NAME_{i}" for i in range(int(content_level) + 1)]
+        gdf = pd.merge(level_gdf.drop(drop_cols, axis=1), complete_df, how="inner", on=shared_cols)
+
+        # now we can filter this dataframe with the appropriate name or admin code
+        gdf = gdf[gdf[column.format(level)].str.fullmatch(id, case=False)]
 
         return gdf