diff --git a/statvar_imports/us_newyork/ny_brfss_health_indicators/README.md b/statvar_imports/us_newyork/ny_brfss_health_indicators/README.md
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+# New York BRFSS Health Indicators Data
+
+## 1. Import Overview
+
+This project processes and imports health indicator prevalence rates across all 62 counties in New York State and New York City, provided by the New York State Department of Health. The dataset provides annual county-level estimates across 5 survey releases (2014, 2016, 2018, 2021, and 2024).
+
+*   **Source URL**: [https://health.data.ny.gov/Health/Behavioral-Risk-Factor-Surveillance-System-BRFSS-H/jsy7-eb4n/about_data](https://health.data.ny.gov/Health/Behavioral-Risk-Factor-Surveillance-System-BRFSS-H/jsy7-eb4n/about_data)
+*   **Import Type**: Automated
+*   **Source Data Availability**: Data is available for 2014, 2016, 2018, 2021, and 2024.
+*   **Release Frequency**: Periodic survey releases (biennial / triennial survey waves).
+*   **Notes**: This dataset provides county-level estimates across 75 health indicators spanning chronic disease, mental health, substance use, disability, immunizations, and social determinants of health. The data originates from the Behavioral Risk Factor Surveillance System (BRFSS).
+
+---
+
+## 2. Preprocessing Steps
+
+The import process involves querying the NYSDOH Socrata API and running a processing script on downloaded source data to generate the final artifacts for ingestion.
+
+*   **Input files**:
+    *   `input_files/`: This directory contains the raw unpivoted data file (`ny_brfss_health_indicators_raw.csv`) containing all 17,700 records across all survey years (2014, 2016, 2018, 2021, 2024).
+    *   `ny_brfss_health_indicators_metadata.csv`: Configuration file for the data processing script specifying column mappings, header row offset, and provenance URL.
+    *   `ny_brfss_health_indicators_pv_map.csv`: Property-value mapping file used by the processor to map indicators and county locations to Data Commons entities.
+    *   `validation_config.json`: Configuration defining historical deletion and date freshness validation rules.
+    *   `test_data/`: Sample input data and expected output files for integration testing.
+
+*   **Transformation pipeline**:
+    1.  The raw data is queried from the NYSDOH Socrata API using deterministic pagination (`$order: ':id'`) via `download.py` and placed in the `input_files/` directory.
+    2.  The `stat_var_processor.py` tool is run on the raw data against `ny_brfss_health_indicators_pv_map.csv` and `ny_brfss_health_indicators_metadata.csv`, referencing canonical schema `gs://unresolved_mcf/scripts/statvar/stat_vars.mcf`.
+    3.  The processor filters non-county regional rows, resolves county FIPS DCIDs, maps indicators to canonical or provisional StatVars, and generates the final `ny_brfss_health_indicators_output.csv`, `ny_brfss_health_indicators_output.tmcf`, and supporting StatVar and schema MCF files in the `output_files/` directory.
+    4.  Processor statistics and metrics are recorded in `counters/ny_brfss_health_indicators_counters.csv`.
+
+*   **Data Quality Checks**:
+    *   The `dc_generated/` directory contains `report.json` and `summary_report.csv`, which provide validation and summary statistics for the generated data.
+    *   Automated validation via `validator.py` evaluates the output against `validation_config.json` enforcing the historical deletion threshold (<= 0.1%) and date freshness (`CAST(MaxDate AS INTEGER) >= (EXTRACT(YEAR FROM CURRENT_DATE) - 3)`).
+
+---
+
+## 3. Automated Import
+
+This import is designed to be fully automated and autorefreshed. Future survey releases are automatically queried, processed, and validated.
+
+### Automated Steps
+1. The automated job triggers annually based on cron schedule `0 0 1 8 *` configured in `manifest.json`.
+2. `download.py` queries the NYSDOH Socrata API endpoint with deterministic pagination (`$order: ':id'`) and updates `input_files/ny_brfss_health_indicators_raw.csv`.
+3. `stat_var_processor.py` executes to regenerate the output CSV, TMCF, and MCF artifacts.
+4. `validator.py` enforces validation rules from `validation_config.json` before publication.
+
+---
+
+## 4. Script Execution Details
+
+To run the import pipeline, execute the processing scripts as detailed below.
+
+### Download the Data
+
+This script downloads the multi-year health indicators dataset from the NYSDOH Socrata API into `input_files/`:
+
+**Usage**:
+```bash
+python3 download.py
+```
+
+### Process the Data
+
+This script processes the raw input file to generate the final `ny_brfss_health_indicators_output.csv` file, `ny_brfss_health_indicators_output.tmcf` template, and supporting MCF files.
+
+**Usage**:
+```bash
+python3 ../../../tools/statvar_importer/stat_var_processor.py \
+  --input_data="input_files/ny_brfss_health_indicators_raw.csv" \
+  --pv_map=ny_brfss_health_indicators_pv_map.csv \
+  --config_file=ny_brfss_health_indicators_metadata.csv \
+  --existing_statvar_mcf=gs://unresolved_mcf/scripts/statvar/stat_vars.mcf \
+  --output_path=output_files/ny_brfss_health_indicators_output \
+  --output_counters=counters/ny_brfss_health_indicators_counters.csv
+```
+
+### Run Sample Integration Test
+
+This script verifies property-value mapping against the test data fixtures:
+
+**Usage**:
+```bash
+python3 ../../../tools/statvar_importer/stat_var_processor.py \
+  --input_data="test_data/sample_input.csv" \
+  --pv_map=ny_brfss_health_indicators_pv_map.csv \
+  --config_file=ny_brfss_health_indicators_metadata.csv \
+  --existing_statvar_mcf=gs://unresolved_mcf/scripts/statvar/stat_vars.mcf \
+  --output_path=test_data/sample_expected_output
+```
diff --git a/statvar_imports/us_newyork/ny_brfss_health_indicators/download.py b/statvar_imports/us_newyork/ny_brfss_health_indicators/download.py
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+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Automated Multi-Year Downloader for NYS BRFSS Health Indicators by County and Region.
+
+Downloads live county and region level health outcome indicators for New York State
+from the NYSDOH Socrata Open Data API (jsy7-eb4n) across all survey years (2014, 2016,
+2018, 2021, 2024), covering all 62 counties, 11 DSRIP regions, NYC, Rest of State,
+and Statewide.
+"""
+
+import os
+from absl import app
+from absl import flags
+from absl import logging
+import pandas as pd
+import requests
+from requests.adapters import HTTPAdapter
+from urllib3.util.retry import Retry
+
+FLAGS = flags.FLAGS
+
+flags.DEFINE_string(
+    'output_dir',
+    'input_files',
+    'Directory where downloaded input CSV files will be saved.',
+)
+flags.DEFINE_string(
+    'endpoint',
+    'https://health.data.ny.gov/resource/jsy7-eb4n.json',
+    'Health Data NY BRFSS Socrata API endpoint.',
+)
+
+
+def create_session() -> requests.Session:
+    """Creates a requests session configured with retries and connection pooling."""
+    session = requests.Session()
+    retries = Retry(
+        total=5,
+        backoff_factor=1.5,
+        status_forcelist=[429, 500, 502, 503, 504],
+        raise_on_status=False,
+    )
+    adapter = HTTPAdapter(max_retries=retries)
+    session.mount('https://', adapter)
+    session.mount('http://', adapter)
+    session.headers.update({
+        'User-Agent':
+            'Mozilla/5.0 (DataCommons Ingestion; +https://datacommons.org)',
+        'Accept':
+            'application/json, text/csv, */*',
+    })
+    return session
+
+
+def atomic_to_csv(df: pd.DataFrame, target_path: str) -> None:
+    """Writes a DataFrame to a CSV file atomically via a temporary file."""
+    temp_path = f'{target_path}.tmp'
+    df.to_csv(temp_path, index=False)
+    if not (os.path.exists(temp_path) and os.path.getsize(temp_path) > 0):
+        raise RuntimeError(
+            f'Atomic write failed: {temp_path} is empty or missing.'
+        )
+    os.replace(temp_path, target_path)
+
+
+def download_health_indicators(endpoint: str,
+                               output_dir: str) -> tuple[int, list[str]]:
+    """Downloads all health indicators for all NY counties and regions."""
+    os.makedirs(output_dir, exist_ok=True)
+
+    records = []
+    offset = 0
+    limit = 50000
+
+    with create_session() as session:
+        while True:
+            params = {
+                '$limit': limit,
+                '$offset': offset,
+                '$order': ':id',
+            }
+            logging.info('GET %s with params %s', endpoint, params)
+            resp = session.get(endpoint, params=params, timeout=60)
+            if resp.status_code != 200:
+                logging.error('Health Data NY API returned HTTP %d: %s',
+                              resp.status_code, resp.text[:200])
+                raise RuntimeError(
+                    f'Health Data NY API returned HTTP {resp.status_code}: {resp.text[:200]}'
+                )
+
+            chunk = resp.json()
+            if not chunk:
+                break
+            records.extend(chunk)
+            logging.info('Fetched %d records (offset %d).', len(chunk), offset)
+            offset += len(chunk)
+
+    if not records:
+        logging.error('Health Data NY API returned 0 records.')
+        raise RuntimeError('Health Data NY API returned 0 records.')
+
+    logging.info('Received %d total raw records from Health Data NY API.',
+                 len(records))
+    raw_df = pd.DataFrame(records)
+
+    # Save complete raw unpivoted dataset (all 17,000+ API records)
+    raw_file = os.path.join(output_dir, 'ny_brfss_health_indicators_raw.csv')
+    atomic_to_csv(raw_df, raw_file)
+    saved_files = [raw_file]
+    logging.info('Wrote raw unpivoted dataset (%d records) -> %s', len(raw_df),
+                 raw_file)
+
+    return len(raw_df), saved_files
+
+
+def main(_):
+    script_dir = os.path.dirname(os.path.abspath(__file__))
+    output_dir = (FLAGS.output_dir if os.path.isabs(FLAGS.output_dir) else
+                  os.path.join(script_dir, FLAGS.output_dir))
+    download_health_indicators(FLAGS.endpoint, output_dir)
+
+
+if __name__ == '__main__':
+    app.run(main)
diff --git a/statvar_imports/us_newyork/ny_brfss_health_indicators/manifest.json b/statvar_imports/us_newyork/ny_brfss_health_indicators/manifest.json
new file mode 100644
index 0000000000..54b5ae876f
--- /dev/null
+++ b/statvar_imports/us_newyork/ny_brfss_health_indicators/manifest.json
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+{
+    "import_specifications": [
+        {
+            "import_name": "NewYork_BRFSS_Health_Indicators",
+            "curator_emails": [
+                "support@datacommons.org"
+            ],
+            "provenance_url": "https://health.data.ny.gov/Health/Behavioral-Risk-Factor-Surveillance-System-BRFSS-H/jsy7-eb4n/about_data",
+            "provenance_description": "The Behavioral Risk Factor Surveillance System (BRFSS) Health Indicators dataset from the New York State Department of Health provides annual estimates of chronic disease prevalence across all counties in New York.",
+            "scripts": [
+                "download.py",
+                "../../../tools/statvar_importer/stat_var_processor.py --input_data=input_files/ny_brfss_health_indicators_raw.csv --pv_map=ny_brfss_health_indicators_pv_map.csv --config_file=ny_brfss_health_indicators_metadata.csv --existing_statvar_mcf=gs://unresolved_mcf/scripts/statvar/stat_vars.mcf --output_path=output_files/ny_brfss_health_indicators_output --output_counters=counters/ny_brfss_health_indicators_counters.csv"
+            ],
+            "import_inputs": [
+                {
+                    "template_mcf": "output_files/ny_brfss_health_indicators_output.tmcf",
+                    "cleaned_csv": "output_files/ny_brfss_health_indicators_output.csv",
+                    "node_mcf": "output_files/*.mcf"
+                }
+            ],
+            "source_files": [
+                "input_files/*.csv",
+                "counters/*.csv",
+                "validation_config.json"
+            ],
+            "cron_schedule": "0 0 1 * *",
+            "validation_config_file": "validation_config.json"
+        }
+    ]
+}
diff --git a/statvar_imports/us_newyork/ny_brfss_health_indicators/ny_brfss_health_indicators_metadata.csv b/statvar_imports/us_newyork/ny_brfss_health_indicators/ny_brfss_health_indicators_metadata.csv
new file mode 100644
index 0000000000..9158c3e7f2
--- /dev/null
+++ b/statvar_imports/us_newyork/ny_brfss_health_indicators/ny_brfss_health_indicators_metadata.csv
@@ -0,0 +1,5 @@
+parameter,value
+url,https://health.data.ny.gov/Health/Behavioral-Risk-Factor-Surveillance-System-BRFSS-H/jsy7-eb4n/about_data
+output_columns,"observationAbout,observationDate,value,variableMeasured"
+header_rows,1
+mapped_columns,4
diff --git a/statvar_imports/us_newyork/ny_brfss_health_indicators/ny_brfss_health_indicators_pv_map.csv b/statvar_imports/us_newyork/ny_brfss_health_indicators/ny_brfss_health_indicators_pv_map.csv
new file mode 100644
index 0000000000..bba03dfce7
--- /dev/null
+++ b/statvar_imports/us_newyork/ny_brfss_health_indicators/ny_brfss_health_indicators_pv_map.csv
@@ -0,0 +1,183 @@
+key,p1,v1,p2,v2,p3,v3,p4,v4,p5,v5,p6,v6,p7,v7,p8,v8,p9,v9,p10,v10,p11,v11,p12,v12,p13,v13
+years,observationDate,{@Data}
+2013-14,observationDate,2014
+region_county,observationAbout,{@Data}
+unadjusted_rate,value,{Number}
+NYS Exclusive of NYC,#IgnoreRow,True,#ignore,non-county regional aggregate
+Statewide,#IgnoreRow,True,#ignore,statewide aggregate
+REGION: Capital Region,#IgnoreRow,True,#ignore,non-county regional aggregate
+REGION: Central NY,#IgnoreRow,True,#ignore,non-county regional aggregate
+REGION: Finger Lakes,#IgnoreRow,True,#ignore,non-county regional aggregate
+REGION: Long Island,#IgnoreRow,True,#ignore,non-county regional aggregate
+REGION: Mid-Hudson,#IgnoreRow,True,#ignore,non-county regional aggregate
+REGION: Mohawk Valley,#IgnoreRow,True,#ignore,non-county regional aggregate
+REGION: New York City,#IgnoreRow,True,#ignore,non-county regional aggregate
+REGION: North Country,#IgnoreRow,True,#ignore,non-county regional aggregate
+REGION: Southern Tier,#IgnoreRow,True,#ignore,non-county regional aggregate
+REGION: Tug Hill Seaway,#IgnoreRow,True,#ignore,non-county regional aggregate
+REGION: Western NY,#IgnoreRow,True,#ignore,non-county regional aggregate
+sample_size_n,#ignore,survey sample size not a target health indicator,value,{@Data}
+est_count,#ignore,weighted population estimate count,value,{@Data}
+est_denominator,#ignore,weighted denominator population,value,{@Data}
+cl_95_lower_unadjusted,#ignore,95% confidence interval lower bound,value,{@Data}
+cl_95_upper_unadjusted,#ignore,95% confidence interval upper bound,value,{@Data}
+adjusted_rate,#ignore,age-adjusted rate omitted in favor of unadjusted rate,value,{@Data}
+cl_95_lower_adjusted,#ignore,95% confidence interval lower bound for adjusted rate,value,{@Data}
+cl_95_upper_adjusted,#ignore,95% confidence interval upper bound for adjusted rate,value,{@Data}
+geography,#ignore,redundant geography level label,value,{@Data}
+health_domain,#ignore,category label redundant with StatVar,value,{@Data}
+health_indicator,#ignore,verbose description redundant with short name,value,{@Data}
+prevention_agenda_pa,#ignore,NYSDOH program tracking flag,value,{@Data}
+ship,#ignore,NYSDOH program tracking flag,value,{@Data}
+dsrip,#ignore,NYSDOH program tracking flag,value,{@Data}
+chirs,#ignore,NYSDOH program tracking flag,value,{@Data}
+fips,#ignore,redundant with region_county mapping,value,{@Data}
+health_indicator_sort_key,#ignore,internal display sort key,value,{@Data}
+dsrip_region_sort_key,#ignore,internal display sort key,value,{@Data}
+county_sort_key,#ignore,internal display sort key,value,{@Data}
+location,#ignore,WKT centroid coordinate redundant with place DCID,value,{@Data}
+notes,#ignore,data suppression note,value,{@Data}
+pa_rate_type,#ignore,rate type metadata,value,{@Data}
+ship_rate_type,#ignore,rate type metadata,value,{@Data}
+dsrip_rate_type,#ignore,rate type metadata,value,{@Data}
+chirs_rate_type,#ignore,rate type metadata,value,{@Data}
+upstate_downstate_sort_key,#ignore,internal display sort key,value,{@Data}
+Diabetes,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,Diabetes,unit,Percent
+Prediabetes,populationType,Person,measuredProperty,percent,healthOutcome,Prediabetes,unit,Percent
+Asthma,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,Asthma,unit,Percent
+Arthritis,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,Arthritis,unit,Percent
+Cardiovascular Disease,populationType,Person,measuredProperty,percent,healthOutcome,CardiovascularDisease,unit,Percent
+COPD,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,ChronicObstructivePulmonaryDisease,unit,Percent
+High Blood Pressure,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,HighBloodPressure,unit,Percent
+Elevated Cholesterol,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,HighCholesterol,unit,Percent
+Obesity,dcid,Percent_Person_Obesity,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthBehavior,Obesity,unit,Percent
+Overweight or Obese,populationType,Person,measuredProperty,percent,healthOutcome,OverweightOrObese,unit,Percent
+Depressive Disorder,dcid,Percent_Person_18OrMoreYears_WithDepression,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,Depression,unit,Percent
+2+ Adverse Childhood Experiences,populationType,Person,measuredProperty,percent,healthStatus,TwoOrMoreAdverseChildhoodExperiences,unit,Percent
+Active Transportation,populationType,Person,measuredProperty,percent,healthBehavior,ActiveTransportation,unit,Percent
+Asthma Ever,populationType,Person,measuredProperty,percent,healthOutcome,AsthmaEver,unit,Percent
+Binge Drinking,dcid,Percent_Person_BingeDrinking,populationType,Person,measuredProperty,percent,healthBehavior,BingeDrinking,unit,Percent
+Binge or Heavy Drinking,populationType,Person,measuredProperty,percent,healthBehavior,BingeOrHeavyDrinking,unit,Percent
+Breast Cancer Screening,dcid,Percent_Person_50To74Years_Female_ReceivedMammography,populationType,Person,gender,Female,age,Years50To74,measuredProperty,percent,healthPrevention,Mammography,unit,Percent
+Breast Cancer Screening Low Income 50-74,populationType,Person,gender,Female,age,Years50To74,income,[USDollar 0 24999],measuredProperty,percent,healthPrevention,Mammography,unit,Percent
+Cardiovascular Disease Disability,populationType,Person,disabilityStatus,AnyDisability,measuredProperty,percent,healthOutcome,CardiovascularDisease,unit,Percent
+Cervical Cancer Screening,dcid,Percent_Person_21To65Years_Female_ReceivedCervicalCancerScreening,populationType,Person,gender,Female,age,Years21To65,measuredProperty,percent,healthPrevention,CervicalCancerScreening,unit,Percent
+Cervical Cancer Screening (2012 guidelines),populationType,Person,gender,Female,age,Years21To65,measuredProperty,percent,healthPrevention,CervicalCancerScreening2012Guidelines,unit,Percent
+Cervical Cancer Screening (2012 guidelines) 21-29,populationType,Person,gender,Female,age,Years21To29,measuredProperty,percent,healthPrevention,CervicalCancerScreening2012Guidelines,unit,Percent
+Cervical Cancer Screening (pre-2012 guidelines),populationType,Person,gender,Female,age,Years21To65,measuredProperty,percent,healthPrevention,CervicalCancerScreeningPre2012Guidelines,unit,Percent
+Cervical Cancer Screening (pre-2012 guidelines) Low Income,populationType,Person,gender,Female,age,Years21To65,income,[USDollar 0 24999],measuredProperty,percent,healthPrevention,CervicalCancerScreeningPre2012Guidelines,unit,Percent
+Cholesterol Checked,dcid,Percent_Person_ReceivedCholesterolScreening,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthPrevention,CholesterolScreening,unit,Percent
+Chronic Disease Self-Management,populationType,Person,measuredProperty,percent,healthBehavior,ChronicDiseaseSelfManagement,unit,Percent
+Colorectal Cancer Screening,dcid,Percent_Person_50To75Years_ReceivedColorectalCancerScreening,populationType,Person,age,Years50To75,measuredProperty,percent,healthPrevention,ColorectalCancerScreening,unit,Percent
+Colorectal Cancer Screening 50-64,populationType,Person,age,Years50To64,measuredProperty,percent,healthPrevention,ColorectalCancerScreening,unit,Percent
+Colorectal Cancer Screening Low Income,populationType,Person,age,Years50To75,income,[USDollar 0 24999],measuredProperty,percent,healthPrevention,ColorectalCancerScreening,unit,Percent
+Current Cannabis Use,populationType,Person,measuredProperty,percent,healthBehavior,CannabisUse,unit,Percent
+Current Medical Cannabis Use,populationType,Person,measuredProperty,percent,healthBehavior,MedicalCannabisUse,unit,Percent
+Current Smoking,dcid,Percent_Person_Smoking,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthBehavior,Smoking,unit,Percent
+Current Smoking 18-24,populationType,Person,age,Years18To24,measuredProperty,percent,healthBehavior,Smoking,unit,Percent
+Current Smoking Disability,populationType,Person,disabilityStatus,AnyDisability,measuredProperty,percent,healthBehavior,Smoking,unit,Percent
+Current Smoking Low Income,populationType,Person,income,[USDollar 0 24999],measuredProperty,percent,healthBehavior,Smoking,unit,Percent
+Current Smoking Poor Mental Health,populationType,Person,healthStatus,PoorMentalHealth,measuredProperty,percent,healthBehavior,Smoking,unit,Percent
+DWI,populationType,Person,measuredProperty,percent,healthBehavior,DrivingWhileIntoxicated,unit,Percent
+Diabetes and Prediabetes Testing,populationType,Person,measuredProperty,percent,healthCareUtilization,DiabetesOrPrediabetesTesting,unit,Percent
+Disability,dcid,Percent_Person_18OrMoreYears_WithAnyDisability,populationType,Person,age,Years18Onwards,measuredProperty,percent,disabilityStatus,AnyDisability,unit,Percent
+Fall within Past Year 65+,populationType,Person,age,Years65Onwards,measuredProperty,percent,healthOutcome,FallPastYear,unit,Percent
+Falls Resulting in Injury 65+,populationType,Person,age,Years65Onwards,measuredProperty,percent,healthOutcome,FallWithInjuryPastYear,unit,Percent
+Fast Food Consumption,populationType,Person,measuredProperty,percent,healthBehavior,FastFoodConsumption3OrMoreTimesPerWeek,unit,Percent
+Flu-Shot,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthCareUtilization,InfluenzaVaccinePastYear,unit,Percent
+Flu-Shot 65+,populationType,Person,age,Years65Onwards,measuredProperty,percent,healthCareUtilization,InfluenzaVaccinePastYear,unit,Percent
+Food Insecurity,populationType,Person,measuredProperty,percent,socialSecurityStatus,FoodInsecurityPast12Months,unit,Percent
+Food Security,populationType,Person,measuredProperty,percent,socialSecurityStatus,FoodSecurityPast12Months,unit,Percent
+HCV Ever Tested,populationType,Person,measuredProperty,percent,healthCareUtilization,HepatitisCTestingEver,unit,Percent
+HCV Ever Tested 47-68,populationType,Person,age,Years47To68,measuredProperty,percent,healthCareUtilization,HepatitisCTestingEver,unit,Percent
+Health Care Coverage,populationType,Person,age,Years18To64,measuredProperty,percent,healthInsurance,WithHealthInsurance,unit,Percent
+Health Care Coverage Female 18-64,populationType,Person,gender,Female,age,Years18To64,measuredProperty,percent,healthInsurance,WithHealthInsurance,unit,Percent
+Health Care Provider,populationType,Person,measuredProperty,percent,healthCareProviderStatus,HasPersonalHealthCareProvider,unit,Percent
+High Blood Pressure Taking Medication,dcid,Percent_Person_18OrMoreYears_WithHighBloodPressure_ReceivedTakingBloodPressureMedication,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,HighBloodPressure,healthPrevention,TakingBloodPressureMedication,unit,Percent
+Housing Insecurity,populationType,Person,measuredProperty,percent,socialSecurityStatus,HousingInsecurityPast12Months,unit,Percent
+Housing or Utility Insecurity,populationType,Person,measuredProperty,percent,socialSecurityStatus,HousingOrUtilityInsecurityPast12Months,unit,Percent
+Leisure-Time Physical Activity,populationType,Person,measuredProperty,percent,healthBehavior,LeisureTimePhysicalActivity,unit,Percent
+Limitation Status,populationType,Person,measuredProperty,percent,healthStatus,WithLimitation,unit,Percent
+No Fruits or Vegetables,populationType,Person,measuredProperty,percent,healthBehavior,ConsumesNoFruitsOrVegetables,unit,Percent
+No Medical Care Due to Cost,populationType,Person,measuredProperty,percent,healthCareAccessStatus,DidNotReceiveCareDueToCost,unit,Percent
+Obesity Disability,populationType,Person,disabilityStatus,AnyDisability,measuredProperty,percent,healthBehavior,Obesity,unit,Percent
+Obesity Limitation Status,populationType,Person,healthStatus,WithLimitation,measuredProperty,percent,healthBehavior,Obesity,unit,Percent
+Obesity Low Income,populationType,Person,income,[USDollar 0 24999],measuredProperty,percent,healthBehavior,Obesity,unit,Percent
+PSA Screening,populationType,Person,gender,Male,age,Years55To69,measuredProperty,percent,healthCareUtilization,ProstateSpecificAntigenScreeningSharedDecision,unit,Percent
+Pneumonia Shot 65+,populationType,Person,age,Years65Onwards,measuredProperty,percent,healthCareUtilization,PneumococcalVaccineEver,unit,Percent
+Poor General Health,dcid,Percent_Person_18OrMoreYears_WithPoorGeneralHealth,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,PoorGeneralHealth,unit,Percent
+Poor Mental Health,dcid,Percent_Person_WithMentalHealthNotGood,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,MentalHealthNotGood,unit,Percent
+Poor Physical Health,dcid,Percent_Person_WithPhysicalHealthNotGood,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthOutcome,PhysicalHealthNotGood,unit,Percent
+Provider Discussed Healthy Pregnancy,populationType,Person,gender,Female,age,Years18To44,measuredProperty,percent,healthCareUtilization,ProviderDiscussedHealthyPregnancy,unit,Percent
+Recent Checkup,populationType,Person,age,Years18To64,measuredProperty,percent,healthCareUtilization,RoutineCheckupWithinPastYear,unit,Percent
+Recent Checkup Female 18-44,populationType,Person,gender,Female,age,Years18To44,measuredProperty,percent,healthCareUtilization,RoutineCheckupWithinPastYear,unit,Percent
+Recent Checkup Female 18-64,populationType,Person,gender,Female,age,Years18To64,measuredProperty,percent,healthCareUtilization,RoutineCheckupWithinPastYear,unit,Percent
+Recent Dental Visit,dcid,Percent_Person_ReceivedDentalVisit,populationType,Person,age,Years18Onwards,measuredProperty,percent,healthPrevention,DentalVisit,unit,Percent
+Recent Dental Visit Female 18-44,populationType,Person,gender,Female,age,Years18To44,measuredProperty,percent,healthPrevention,DentalVisit,unit,Percent
+Sugar-Sweetened Beverages,populationType,Person,measuredProperty,percent,healthBehavior,DailySugarSweetenedBeverages,unit,Percent
+Walkable Neighborhood,populationType,Person,measuredProperty,percent,environmentStatus,WalkableNeighborhood,unit,Percent
+e-Cigarettes,populationType,Person,measuredProperty,percent,healthBehavior,ElectronicCigaretteUse,unit,Percent
+Albany,observationAbout,geoId/36001
+Allegany,observationAbout,geoId/36003
+Bronx,observationAbout,geoId/36005
+Broome,observationAbout,geoId/36007
+Cattaraugus,observationAbout,geoId/36009
+Cayuga,observationAbout,geoId/36011
+Chautauqua,observationAbout,geoId/36013
+Chemung,observationAbout,geoId/36015
+Chenango,observationAbout,geoId/36017
+Clinton,observationAbout,geoId/36019
+Columbia,observationAbout,geoId/36021
+Cortland,observationAbout,geoId/36023
+Delaware,observationAbout,geoId/36025
+Dutchess,observationAbout,geoId/36027
+Erie,observationAbout,geoId/36029
+Essex,observationAbout,geoId/36031
+Franklin,observationAbout,geoId/36033
+Fulton,observationAbout,geoId/36035
+Genesee,observationAbout,geoId/36037
+Greene,observationAbout,geoId/36039
+Hamilton,observationAbout,geoId/36041
+Herkimer,observationAbout,geoId/36043
+Jefferson,observationAbout,geoId/36045
+Kings,observationAbout,geoId/36047
+Lewis,observationAbout,geoId/36049
+Livingston,observationAbout,geoId/36051
+Madison,observationAbout,geoId/36053
+Monroe,observationAbout,geoId/36055
+Montgomery,observationAbout,geoId/36057
+Nassau,observationAbout,geoId/36059
+New York City,observationAbout,geoId/3651000
+New York,observationAbout,geoId/36061
+Niagara,observationAbout,geoId/36063
+Oneida,observationAbout,geoId/36065
+Onondaga,observationAbout,geoId/36067
+Ontario,observationAbout,geoId/36069
+Orange,observationAbout,geoId/36071
+Orleans,observationAbout,geoId/36073
+Oswego,observationAbout,geoId/36075
+Otsego,observationAbout,geoId/36077
+Putnam,observationAbout,geoId/36079
+Queens,observationAbout,geoId/36081
+Rensselaer,observationAbout,geoId/36083
+Richmond,observationAbout,geoId/36085
+Rockland,observationAbout,geoId/36087
+Saratoga,observationAbout,geoId/36091
+Schenectady,observationAbout,geoId/36093
+Schoharie,observationAbout,geoId/36095
+Schuyler,observationAbout,geoId/36097
+Seneca,observationAbout,geoId/36099
+St Lawrence,observationAbout,geoId/36089
+St. Lawrence,observationAbout,geoId/36089
+Steuben,observationAbout,geoId/36101
+Suffolk,observationAbout,geoId/36103
+Sullivan,observationAbout,geoId/36105
+Tioga,observationAbout,geoId/36107
+Tompkins,observationAbout,geoId/36109
+Ulster,observationAbout,geoId/36111
+Warren,observationAbout,geoId/36113
+Washington,observationAbout,geoId/36115
+Wayne,observationAbout,geoId/36117
+Westchester,observationAbout,geoId/36119
+Wyoming,observationAbout,geoId/36121
+Yates,observationAbout,geoId/36123
diff --git a/statvar_imports/us_newyork/ny_brfss_health_indicators/test_data/sample_expected_output.csv b/statvar_imports/us_newyork/ny_brfss_health_indicators/test_data/sample_expected_output.csv
new file mode 100644
index 0000000000..a1f1d7d3ef
--- /dev/null
+++ b/statvar_imports/us_newyork/ny_brfss_health_indicators/test_data/sample_expected_output.csv
@@ -0,0 +1,18 @@
+observationAbout,observationDate,value,variableMeasured
+geoId/36001,2021,11.7,dcid:Percent_Person_WithPrediabetes
+geoId/36001,2021,9.2,dcid:Percent_Person_WithDiabetes
+geoId/36001,2021,7.4,dcid:Percent_Person_WithCardiovascularDisease
+geoId/36001,2021,21.2,dcid:Percent_Person_18OrMoreYears_WithDepression
+geoId/36001,2021,30.1,dcid:Percent_Person_Obesity
+geoId/36001,2021,11.3,dcid:Percent_Person_WithAsthma
+geoId/36005,2021,15.2,dcid:Percent_Person_WithPrediabetes
+geoId/36005,2021,12.4,dcid:Percent_Person_WithAsthma
+geoId/36005,2021,13.6,dcid:Percent_Person_WithDiabetes
+geoId/36005,2021,6.6,dcid:Percent_Person_WithCardiovascularDisease
+geoId/36005,2021,16.7,dcid:Percent_Person_18OrMoreYears_WithDepression
+geoId/36005,2021,34.5,dcid:Percent_Person_Obesity
+geoId/3651000,2021,9.1,dcid:Percent_Person_WithAsthma
+geoId/3651000,2021,12.9,dcid:Percent_Person_WithPrediabetes
+geoId/3651000,2021,12,dcid:Percent_Person_WithDiabetes
+geoId/3651000,2021,25.7,dcid:Percent_Person_Obesity
+geoId/36001,2014,9.4,dcid:Percent_Person_WithDiabetes
diff --git a/statvar_imports/us_newyork/ny_brfss_health_indicators/test_data/sample_input.csv b/statvar_imports/us_newyork/ny_brfss_health_indicators/test_data/sample_input.csv
new file mode 100644
index 0000000000..fa31755460
--- /dev/null
+++ b/statvar_imports/us_newyork/ny_brfss_health_indicators/test_data/sample_input.csv
@@ -0,0 +1,22 @@
+years,health_indicator_short_name,geography,region_county,sample_size_n,est_count,est_denominator,unadjusted_rate,cl_95_lower_unadjusted,cl_95_upper_unadjusted,adjusted_rate,cl_95_lower_adjusted,cl_95_upper_adjusted,health_domain,health_indicator,prevention_agenda_pa,ship,dsrip,chirs,fips,health_indicator_sort_key,dsrip_region_sort_key,county_sort_key,location,:@computed_region_43an_4dx5,:@computed_region_9yqb_tdyd,:@computed_region_assa_msit,:@computed_region_5edz_4hdv,chirs_rate_type,:@computed_region_8ire_itmf,pa_rate_type,notes,upstate_downstate_sort_key,ship_rate_type,dsrip_rate_type
+2021,Prediabetes,County,Albany,681.0,18171.0,155370.0,11.7,8.4,15.0,11.9,8.6,15.2,Prevent Chronic Diseases,Percentage of adults with health care provider diagnosed prediabetes,no,Not Applicable,Not Applicable,no,1.0,59,104.0,1.0,"{'latitude': '42.678066', 'longitude': '-73.814233', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",40.0,2030.0,34.0,573.0,,1.0,,,,,
+2021,Diabetes,County,Albany,1174.0,23847.0,258799.0,9.2,7.3,11.1,8.7,6.9,10.5,Prevent Chronic Diseases,Percentage of adults with health care provider diagnosed diabetes,no,Not Applicable,Not Applicable,yes,1.0,35,104.0,1.0,"{'latitude': '42.678066', 'longitude': '-73.814233', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",40.0,2030.0,34.0,573.0,age-adjusted,1.0,,,,,
+2021,Cardiovascular Disease,County,Albany,1175.0,19067.0,258878.0,7.4,5.5,9.3,6.3,4.7,8.0,Prevent Chronic Diseases,"Percentage of adults with cardiovascular disease (heart attack, coronary heart disease, or stroke)",no,Not Applicable,Not Applicable,yes,1.0,65,104.0,1.0,"{'latitude': '42.678066', 'longitude': '-73.814233', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",40.0,2030.0,34.0,573.0,age-adjusted,1.0,,,,,
+2021,Depressive Disorder,County,Albany,1160.0,53767.0,253778.0,21.2,17.9,24.5,21.1,17.8,24.3,Promote Mental Health and Prevention Substance Abuse,Pecentage of adults reporting a depressive disorder,no,Not Applicable,Not Applicable,no,1.0,100,104.0,1.0,"{'latitude': '42.678066', 'longitude': '-73.814233', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",40.0,2030.0,34.0,573.0,,1.0,,,,,
+2021,Obesity,County,Albany,974.0,64268.0,213476.0,30.1,26.0,34.2,32.4,28.5,36.4,Prevent Chronic Diseases,Percentage of adults who are obese,yes,Not Applicable,Not Applicable,yes,1.0,21,104.0,1.0,"{'latitude': '42.678066', 'longitude': '-73.814233', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",40.0,2030.0,34.0,573.0,age-adjusted,1.0,crude,,,,
+2021,Asthma,County,Albany,1161.0,28964.0,256532.0,11.3,8.6,13.9,12.0,9.1,14.8,Prevent Chronic Diseases,Percentage of adults with current asthma,no,Not Applicable,Not Applicable,yes,1.0,68,104.0,1.0,"{'latitude': '42.678066', 'longitude': '-73.814233', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",40.0,2030.0,34.0,573.0,age-adjusted,1.0,,,,,
+2021,Prediabetes,County,Bronx,618.0,89452.0,586929.0,15.2,12.0,18.5,15.6,12.3,18.8,Prevent Chronic Diseases,Percentage of adults with health care provider diagnosed prediabetes,no,Not Applicable,Not Applicable,no,5.0,59,102.0,3.0,"{'latitude': '40.8448', 'longitude': '-73.8648', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",675.0,2032.0,51.0,176.0,,37.0,,,,,
+2021,Asthma,County,Bronx,1180.0,135984.0,1096419.0,12.4,10.2,14.6,12.5,10.2,14.7,Prevent Chronic Diseases,Percentage of adults with current asthma,no,Not Applicable,Not Applicable,yes,5.0,68,102.0,3.0,"{'latitude': '40.8448', 'longitude': '-73.8648', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",675.0,2032.0,51.0,176.0,age-adjusted,37.0,,,,,
+2021,Diabetes,County,Bronx,1183.0,149452.0,1099809.0,13.6,11.4,15.7,13.4,11.3,15.5,Prevent Chronic Diseases,Percentage of adults with health care provider diagnosed diabetes,no,Not Applicable,Not Applicable,yes,5.0,35,102.0,3.0,"{'latitude': '40.8448', 'longitude': '-73.8648', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",675.0,2032.0,51.0,176.0,age-adjusted,37.0,,,,,
+2021,Cardiovascular Disease,County,Bronx,1186.0,73001.0,1102413.0,6.6,5.1,8.2,6.6,5.0,8.1,Prevent Chronic Diseases,"Percentage of adults with cardiovascular disease (heart attack, coronary heart disease, or stroke)",no,Not Applicable,Not Applicable,yes,5.0,65,102.0,3.0,"{'latitude': '40.8448', 'longitude': '-73.8648', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",675.0,2032.0,51.0,176.0,age-adjusted,37.0,,,,,
+2021,Depressive Disorder,County,Bronx,1174.0,181734.0,1090697.0,16.7,14.2,19.1,16.9,14.5,19.4,Promote Mental Health and Prevention Substance Abuse,Pecentage of adults reporting a depressive disorder,no,Not Applicable,Not Applicable,no,5.0,100,102.0,3.0,"{'latitude': '40.8448', 'longitude': '-73.8648', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",675.0,2032.0,51.0,176.0,,37.0,,,,,
+2021,Obesity,County,Bronx,950.0,302090.0,874367.0,34.5,31.1,38.0,34.7,31.2,38.2,Prevent Chronic Diseases,Percentage of adults who are obese,yes,Not Applicable,Not Applicable,yes,5.0,21,102.0,3.0,"{'latitude': '40.8448', 'longitude': '-73.8648', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",675.0,2032.0,51.0,176.0,age-adjusted,37.0,crude,,,,
+2021,Asthma,New York City,New York City,6781.0,610365.0,6742877.0,9.1,8.2,9.9,9.2,8.3,10.1,Prevent Chronic Diseases,Percentage of adults with current asthma,no,Not Applicable,Not Applicable,yes,,68,,,,,,,,age-adjusted,,,,1.0,,
+2021,Prediabetes,New York City,New York City,3665.0,642815.0,4980465.0,12.9,11.6,14.3,14.1,12.7,15.5,Prevent Chronic Diseases,Percentage of adults with health care provider diagnosed prediabetes,no,Not Applicable,Not Applicable,no,,59,,,,,,,,,,,,1.0,,
+2021,Diabetes,New York City,New York City,6822.0,817951.0,6795640.0,12.0,11.0,13.1,11.4,10.5,12.4,Prevent Chronic Diseases,Percentage of adults with health care provider diagnosed diabetes,no,Not Applicable,Not Applicable,yes,,35,,,,,,,,age-adjusted,,,,1.0,,
+2021,Obesity,New York City,New York City,5662.0,1433036.0,5579249.0,25.7,24.2,27.1,25.6,24.1,27.1,Prevent Chronic Diseases,Percentage of adults who are obese,yes,Not Applicable,Not Applicable,yes,,21,,,,,,,,age-adjusted,,crude,,1.0,,
+2013-14,Diabetes,County,Albany,1019.0,23281.0,246849.0,9.4,7.0,12.7,8.8,6.6,11.6,Prevent Chronic Diseases,Percentage of adults with physician diagnosed diabetes,no,no,no,no,1.0,35,104.0,1.0,"{'latitude': '42.678066', 'longitude': '-73.814233', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",40.0,2030.0,34.0,573.0,,1.0,,,,,
+2021,Diabetes,DSRIP region,REGION: Capital Region,3432.0,78896.0,806884.0,9.8,8.0,11.6,8.6,6.9,10.3,Prevent Chronic Diseases,Percentage of adults with health care provider diagnosed diabetes,no,Not Applicable,Not Applicable,yes,,35,104.0,,,,,,,age-adjusted,,,,,,
+2021,Diabetes,Statewide,Statewide,38978.0,1827228.0,15988212.0,11.4,10.9,12.0,10.2,9.7,10.7,Prevent Chronic Diseases,Percentage of adults with health care provider diagnosed diabetes,no,Not Applicable,Not Applicable,yes,,35,,,,,,,,age-adjusted,,,,,,
+2024,Provider Discussed Healthy Pregnancy,County,Wyoming,,,,,,,,,,"Promote Healthy Women, Infants, and Children",Percentage of women aged 18-44 years whose health care provider discussed planning a healthy pregnancy,no,Not Applicable,Not Applicable,no,121.0,96,111.0,61.0,"{'latitude': '42.723641', 'longitude': '-78.204473', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",415.0,2186.0,59.0,622.0,,,,rates suppressed due to small sample size,,,
+2024,Provider Discussed Healthy Pregnancy,County,Washington,,,,,,,,,,"Promote Healthy Women, Infants, and Children",Percentage of women aged 18-44 years whose health care provider discussed planning a healthy pregnancy,no,Not Applicable,Not Applicable,no,115.0,96,106.0,58.0,"{'latitude': '43.289513', 'longitude': '-73.454761', 'human_address': '{""address"": """", ""city"": """", ""state"": """", ""zip"": """"}'}",787.0,2184.0,35.0,857.0,,,,rates suppressed due to small sample size,,,
diff --git a/statvar_imports/us_newyork/ny_brfss_health_indicators/validation_config.json b/statvar_imports/us_newyork/ny_brfss_health_indicators/validation_config.json
new file mode 100644
index 0000000000..9916221389
--- /dev/null
+++ b/statvar_imports/us_newyork/ny_brfss_health_indicators/validation_config.json
@@ -0,0 +1,23 @@
+{
+  "schema_version": "1.0",
+  "rules": [
+    {
+      "rule_id": "check_deleted_records_percent",
+      "description": "Strictly enforce historical deletion average threshold of 0.1%",
+      "validator": "DELETED_RECORDS_PERCENT",
+      "params": {
+        "threshold": 0.1
+      }
+    },
+    {
+      "rule_id": "check_max_date_freshness",
+      "description": "Verify MaxDate is within allowable publication lag for recurring health indicators",
+      "validator": "SQL_VALIDATOR",
+      "params": {
+        "query": "SELECT StatVar, MaxDate FROM stats WHERE StatVar IN ('Percent_Person_WithDiabetes', 'Percent_Person_Obesity', 'Percent_Person_Smoking', 'Percent_Person_WithAsthma', 'Percent_Person_WithArthritis', 'Percent_Person_WithHighBloodPressure', 'Percent_Person_WithCardiovascularDisease', 'Percent_Person_WithChronicObstructivePulmonaryDisease', 'Percent_Person_18OrMoreYears_WithDepression', 'Percent_Person_18OrMoreYears_WithPoorGeneralHealth', 'Percent_Person_BingeDrinking', 'Percent_Person_LeisureTimePhysicalActivity', 'Percent_Person_ReceivedDentalVisit', 'Percent_Person_WithPrediabetes', 'Percent_Person_18To64Years_WithHealthInsurance', 'Percent_Person_18OrMoreYears_WithAnyDisability', 'Percent_Person_Years18To64_RoutineCheckupWithinPastYear', 'Percent_Person_50To74Years_Female_ReceivedMammography')",
+        "condition": "CAST(MaxDate AS INTEGER) >= (EXTRACT(YEAR FROM CURRENT_DATE) - 3)"
+      }
+    }
+  ]
+}
+