diff --git a/changelog.d/harden-pregnancy-takeup.fixed.md b/changelog.d/harden-pregnancy-takeup.fixed.md
new file mode 100644
index 000000000..83b67f2d5
--- /dev/null
+++ b/changelog.d/harden-pregnancy-takeup.fixed.md
@@ -0,0 +1 @@
+Harden CPS pregnancy take-up rates to use the build year and fall back across nearby CDC and ACS vintages.
diff --git a/policyengine_us_data/datasets/cps/cps.py b/policyengine_us_data/datasets/cps/cps.py
index 03830647b..baee98234 100644
--- a/policyengine_us_data/datasets/cps/cps.py
+++ b/policyengine_us_data/datasets/cps/cps.py
@@ -587,7 +587,10 @@ def add_takeup(self):
         get_state_pregnancy_rates,
     )
 
-    pregnancy_rates = get_state_pregnancy_rates()
+    pregnancy_rates = get_state_pregnancy_rates(
+        cdc_year=self.time_period,
+        acs_year=self.time_period,
+    )
     national_rate = 0.041  # fallback
     pregnancy_rate_by_person = np.array(
         [pregnancy_rates.get(s, national_rate) for s in person_states]
diff --git a/policyengine_us_data/db/etl_pregnancy.py b/policyengine_us_data/db/etl_pregnancy.py
index 3e4326184..2ef05e177 100644
--- a/policyengine_us_data/db/etl_pregnancy.py
+++ b/policyengine_us_data/db/etl_pregnancy.py
@@ -30,6 +30,7 @@
 )
 from policyengine_us_data.utils.census import STATE_ABBREV_TO_FIPS
 from policyengine_us_data.utils.db import (
+    DEFAULT_YEAR,
     get_geographic_strata,
     etl_argparser,
 )
@@ -395,8 +396,8 @@ def load_pregnancy_data(
 
 
 def get_state_pregnancy_rates(
-    cdc_year: int = 2023,
-    acs_year: int = 2023,
+    cdc_year: int = DEFAULT_YEAR,
+    acs_year: int = DEFAULT_YEAR,
 ) -> dict:
     """Return {state_abbrev: pregnancy_rate} for use by cps.py.
 
@@ -413,8 +414,39 @@ def get_state_pregnancy_rates(
         rate (probability that a woman aged 15-44 is currently
         pregnant).
     """
-    births_df = extract_cdc_births(cdc_year)
-    pop_df = extract_female_population(acs_year)
+    births_df = None
+    birth_errors = []
+    for candidate_cdc_year in [cdc_year, cdc_year - 1]:
+        try:
+            births_df = extract_cdc_births(candidate_cdc_year)
+            break
+        except Exception as e:
+            birth_errors.append(f"{candidate_cdc_year}: {e}")
+            logger.warning(
+                f"CDC VSRR {candidate_cdc_year} not available for take-up: {e}"
+            )
+    if births_df is None:
+        raise RuntimeError(
+            "No CDC VSRR birth data for pregnancy take-up rates. "
+            f"Tried {cdc_year} and {cdc_year - 1}: {'; '.join(birth_errors)}"
+        )
+
+    pop_df = None
+    population_errors = []
+    for candidate_acs_year in [acs_year, acs_year - 1, acs_year - 2]:
+        try:
+            pop_df = extract_female_population(candidate_acs_year)
+            break
+        except Exception as e:
+            population_errors.append(f"{candidate_acs_year}: {e}")
+            logger.warning(f"ACS {candidate_acs_year} not available for take-up: {e}")
+    if pop_df is None:
+        raise RuntimeError(
+            "No ACS female population data for pregnancy take-up rates. "
+            f"Tried {acs_year}, {acs_year - 1}, and {acs_year - 2}: "
+            f"{'; '.join(population_errors)}"
+        )
+
     df = transform_pregnancy_data(births_df, pop_df)
     return dict(zip(df["state_abbrev"], df["pregnancy_rate"]))
 
diff --git a/tests/unit/db/test_etl_pregnancy.py b/tests/unit/db/test_etl_pregnancy.py
index 1f61492a7..69651177b 100644
--- a/tests/unit/db/test_etl_pregnancy.py
+++ b/tests/unit/db/test_etl_pregnancy.py
@@ -1,3 +1,5 @@
+import pandas as pd
+
 from policyengine_us_data.db import etl_pregnancy
 
 
@@ -124,3 +126,37 @@ def fake_get(url, **kwargs):
         ),
     ]
     assert saved == [("census_b01001_female_15_44_2023.json", b01001_payload())]
+
+
+def test_get_state_pregnancy_rates_falls_back_to_available_years(monkeypatch):
+    calls = []
+
+    def fake_extract_cdc_births(year):
+        calls.append(("births", year))
+        if year == 2024:
+            raise RuntimeError("CDC unavailable")
+        return pd.DataFrame({"state_abbrev": ["AL"], "births": [52_000]})
+
+    def fake_extract_female_population(year):
+        calls.append(("population", year))
+        if year in (2024, 2023):
+            raise RuntimeError("ACS unavailable")
+        return pd.DataFrame({"state_abbrev": ["AL"], "female_15_44": [1_000_000]})
+
+    monkeypatch.setattr(etl_pregnancy, "extract_cdc_births", fake_extract_cdc_births)
+    monkeypatch.setattr(
+        etl_pregnancy,
+        "extract_female_population",
+        fake_extract_female_population,
+    )
+
+    rates = etl_pregnancy.get_state_pregnancy_rates(cdc_year=2024, acs_year=2024)
+
+    assert calls == [
+        ("births", 2024),
+        ("births", 2023),
+        ("population", 2024),
+        ("population", 2023),
+        ("population", 2022),
+    ]
+    assert rates == {"AL": 0.039}