diff --git a/notebooks/process/CompileGeoData.ipynb b/notebooks/process/CompileGeoData.ipynb
index 3dda43ed347452924e5303026ac08b110f098aa1..1159904841af4fe128899ba5907e71c319cd34eb 100644
--- a/notebooks/process/CompileGeoData.ipynb
+++ b/notebooks/process/CompileGeoData.ipynb
@@ -26,7 +26,7 @@
    "outputs": [],
    "source": [
     "ts_folder = \"../../data/covid-19_jhu-csse/\"\n",
-    "worldmap_path = \"../../data/worldmap/country_centroids.csv\"\n",
+    "worldmap_path = \"../../data/atlas/worldmap/country_centroids.csv\"\n",
     "out_folder = None\n",
     "PAPERMILL_OUTPUT_PATH = None"
    ]
@@ -80,10 +80,19 @@
    "outputs": [],
    "source": [
     "country_centroids_df = pd.read_csv(worldmap_path)\n",
-    "country_centroids_df = country_centroids_df[['name', 'name_long', 'region_un', 'subregion', 'region_wb', 'pop_est', 'gdp_md_est', 'income_grp', 'Longitude', 'Latitude']]\n",
+    "country_centroids_df = country_centroids_df[['name', 'name_long', 'sov_a3', 'region_un', 'subregion', 'region_wb', 'pop_est', 'gdp_md_est', 'income_grp', 'Longitude', 'Latitude']]\n",
     "country_centroids_df['name_jhu'] = country_centroids_df['name_long'] "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "country_centroids_df.head()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/notebooks/process/ToRates.ipynb b/notebooks/process/ToRates.ipynb
index 9aa7f046fe4b8acf11cd2229297397af98c71853..5db50b0b975700aeb1bca81f2be02c12c5d99bfd 100644
--- a/notebooks/process/ToRates.ipynb
+++ b/notebooks/process/ToRates.ipynb
@@ -28,7 +28,7 @@
    "outputs": [],
    "source": [
     "ts_folder = \"../../data/covid-19_jhu-csse/\"\n",
-    "wb_path = \"../../data/worldbank/SP.POP.TOTL.zip\"\n",
+    "wb_path = \"../../data/atlas/worldbank/SP.POP.TOTL.zip\"\n",
     "geodata_path = \"../../data/geodata/geo_data.csv\"\n",
     "out_folder = None\n",
     "PAPERMILL_OUTPUT_PATH = None"
@@ -167,6 +167,16 @@
     "].iloc[:,-2:]"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "country_centroids_df = pd.read_csv(worldmap_path)\n",
+    "country_centroids_df = country_centroids_df[['name', 'name_long', 'sov_a3', 'region_un', 'subregion', 'region_wb', 'pop_est', 'gdp_md_est', 'income_grp', 'Longitude', 'Latitude']]"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},