💀 CDC WONDER Mortality Data Scraper

🚀 Export CDC WONDER mortality records in seconds. Pull underlying cause-of-death counts, crude rates, and age-adjusted rates for any U.S. state, year, sex, age group, or ICD-10 chapter - no account required. Download as CSV, Excel, JSON, or XML.

🕒 Last updated: 2026-05-21 · 📊 19 fields per record · Up to 1,000,000 records · United States national coverage (1999-present)

The CDC WONDER Mortality Scraper extracts data directly from the CDC's Wide-ranging ONline Data for Epidemiologic Research (WONDER) public API. Every record contains the number of deaths, crude rate per 100,000 population, and age-adjusted mortality rate as published by the U.S. National Vital Statistics System. No login, no CAPTCHA, no manual exports required.

The dataset covers six CDC WONDER mortality databases including the Underlying Cause of Death (1999-present), Multiple Cause of Death, Infant Deaths, and Provisional Mortality series. Researchers and analysts can group results by year, state, sex, age group, or ICD-10 chapter and apply any combination of filters in a single run.

Coverage: All 50 U.S. states plus D.C. - 1999 through the current provisional year. Over 22 ICD-10 disease chapters, 6 grouping dimensions, and 6 mortality database variants.

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Target Audience / Use Cases

Audience	How they use this data
Epidemiologists	Track mortality trends by cause, geography, and demographic
Public health researchers	Compare age-adjusted rates across states and years
Policy analysts	Identify disease burden shifts for resource allocation
Data journalists	Fact-check mortality statistics for investigative reports
Healthcare consultants	Benchmark regional death rates against national averages
Academic institutions	Build teaching datasets from verified federal sources

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📋 What the CDC WONDER Mortality Scraper does

• Queries any of six CDC WONDER mortality databases via the official public API
• Groups results by year, state, sex, age group, or ICD-10 chapter in one request
• Filters by U.S. state (FIPS code), year range, and ICD-10 chapter simultaneously
• Returns deaths count, population, crude rate per 100,000, and age-adjusted rate with confidence intervals
• Applies maxItems cap so free users get a 10-record preview without wasting API quota
• Exports in any Apify-supported format: JSON, CSV, Excel, XML

💡 Why it matters: The CDC WONDER portal requires manual form submissions for every query. This actor turns any mortality query into an automated pipeline - schedule it weekly to track provisional data updates, or run it on-demand inside a Make or Zapier workflow.

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🎬 Full Demo

🚧 Coming soon

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⚙️ Input

Field	Type	Required	Default	Description
maxItems	integer	No	10	Maximum number of records to return. Free users capped at 10; paid users up to 1,000,000.
database	select	No	D76	Which CDC WONDER mortality database to query (e.g. D76 = Underlying Cause of Death 1999-current).
groupBy	select	No	year-state	Aggregation dimension: year, state, year-state, year-state-sex, year-state-age, year-icd10, state-sex-age.
yearFrom	integer	No	2020	Start year (inclusive, minimum 1999).
yearTo	integer	No	2020	End year (inclusive).
state	select	No	(all states)	Filter to one U.S. state by FIPS code. Leave empty for all 50 states + D.C.
icd10Chapter	select	No	(all causes)	Filter by ICD-10 chapter (e.g. I00-I99 Circulatory, J00-J99 Respiratory). Leave empty for all causes.

Example 1 - All states, year 2020, grouped by Year + State:

{
    "maxItems": 100,
    "database": "D76",
    "groupBy": "year-state",
    "yearFrom": 2020,
    "yearTo": 2020
}

Example 2 - Circulatory disease deaths in California, 2015-2020:

{
    "maxItems": 500,
    "database": "D76",
    "groupBy": "year-state",
    "yearFrom": 2015,
    "yearTo": 2020,
    "state": "06",
    "icd10Chapter": "I00-I99"
}

⚠️ Good to Know: CDC WONDER queries can take 30-60 seconds to complete on the server side - this is normal. The actor retries automatically on transient failures. Suppressed counts (cells with fewer than 10 deaths) are returned as null per CDC data-use restrictions.

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📊 Output

Each record contains the following fields:

Field	Type	Description
database	string	CDC WONDER database code queried (e.g. D76)
groupBy	string	Grouping dimension used (e.g. year-state)
yearFrom	integer	Start year of query
yearTo	integer	End year of query
groupLabels	array	Human-readable labels for each grouping dimension
groupCodes	array	Machine codes for each grouping dimension
year	string	Year label (first grouping dimension)
state	string	State label (second grouping dimension when applicable)
additionalLabel	string	Third grouping label (sex, age group, or ICD-10 chapter)
deaths	number	Number of deaths (null if suppressed by CDC)
population	number	Population estimate for the group
crudeRatePer100k	number	Crude death rate per 100,000 population
ageAdjustedRate	number	Age-adjusted death rate per 100,000 (null if not applicable)
ageAdjustedRateStdErr	number	Standard error of age-adjusted rate
ageAdjustedRateLowerCI	number	Lower 95% confidence interval of age-adjusted rate
ageAdjustedRateUpperCI	number	Upper 95% confidence interval of age-adjusted rate
icd10Filter	string	ICD-10 chapter filter applied (null if all causes)
sourceUrl	string	Direct URL to the CDC WONDER database page
scrapedAt	string	ISO 8601 timestamp of when the record was collected
error	string	Error message if the record could not be fetched; null otherwise

Sample records (year-state groupBy, database D76, year 2020):

[
  {
    "database": "D76",
    "groupBy": "year-state",
    "yearFrom": 2020,
    "yearTo": 2020,
    "groupLabels": ["2020", "Alabama"],
    "groupCodes": ["2020", "01"],
    "year": "2020",
    "state": "Alabama",
    "additionalLabel": null,
    "deaths": 56943,
    "population": 4921532,
    "crudeRatePer100k": 1157.7,
    "ageAdjustedRate": 1097.4,
    "ageAdjustedRateStdErr": 4.5,
    "ageAdjustedRateLowerCI": 1088.6,
    "ageAdjustedRateUpperCI": 1106.2,
    "icd10Filter": null,
    "sourceUrl": "https://wonder.cdc.gov/ucd-icd10.html",
    "scrapedAt": "2026-05-21T10:00:00.000Z",
    "error": null
  },
  {
    "database": "D76",
    "groupBy": "year-state",
    "yearFrom": 2020,
    "yearTo": 2020,
    "groupLabels": ["2020", "California"],
    "groupCodes": ["2020", "06"],
    "year": "2020",
    "state": "California",
    "additionalLabel": null,
    "deaths": 299214,
    "population": 39368078,
    "crudeRatePer100k": 760.1,
    "ageAdjustedRate": 701.2,
    "ageAdjustedRateStdErr": 1.3,
    "ageAdjustedRateLowerCI": 698.7,
    "ageAdjustedRateUpperCI": 703.7,
    "icd10Filter": null,
    "sourceUrl": "https://wonder.cdc.gov/ucd-icd10.html",
    "scrapedAt": "2026-05-21T10:00:00.000Z",
    "error": null
  },
  {
    "database": "D76",
    "groupBy": "year-state",
    "yearFrom": 2020,
    "yearTo": 2020,
    "groupLabels": ["2020", "Texas"],
    "groupCodes": ["2020", "48"],
    "year": "2020",
    "state": "Texas",
    "additionalLabel": null,
    "deaths": 222547,
    "population": 29360759,
    "crudeRatePer100k": 758.0,
    "ageAdjustedRate": 751.3,
    "ageAdjustedRateStdErr": 1.6,
    "ageAdjustedRateLowerCI": 748.2,
    "ageAdjustedRateUpperCI": 754.4,
    "icd10Filter": null,
    "sourceUrl": "https://wonder.cdc.gov/ucd-icd10.html",
    "scrapedAt": "2026-05-21T10:00:00.000Z",
    "error": null
  }
]

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✨ Why choose this Actor

Feature	Benefit
🔓 No login required	CDC WONDER public API - no account, no credentials
📊 6 grouping dimensions	Year, state, sex, age, ICD-10, cross-dimensional
🗂️ 6 database variants	Underlying, multiple cause, infant, linked birth, provisional
🌎 Full national coverage	All 50 states + D.C., 1999-present
📁 CSV / Excel / JSON / XML	One-click export in any format via Apify dataset
⏱️ Scheduled runs	Auto-sync with CDC provisional data updates
🔒 CDC data-use compliant	Suppressed counts returned as null, not fabricated
🛡️ Retry logic	Automatic retries on transient API failures

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📈 How it compares to alternatives

Method	Speed	Automation	Format options	Filters
This Actor	Fast	Full	CSV/Excel/JSON/XML	Year, state, sex, age, ICD-10
CDC WONDER web portal	Manual	None	Tab-delimited text only	Same filters, manual only
CDC Wonder R package	Moderate	Partial (R only)	Data frames	Limited
Manual data download	Slow	None	Text files	Manual only

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🚀 How to use

1. Create a free account with $5 credit on Apify
2. Open the CDC WONDER Mortality Data Scraper actor page
3. Set your desired database, groupBy, yearFrom, and yearTo
4. Optionally filter by state (FIPS code) and/or icd10Chapter
5. Set maxItems (10 for a free preview, up to 1,000,000 for paid users)
6. Click Start and wait 30-60 seconds for the CDC query to complete
7. Download your dataset as CSV, Excel, JSON, or XML

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💼 Business use cases

Public health surveillance

Track year-over-year mortality trends for any cause of death across all U.S. states. Identify outlier states with elevated age-adjusted rates and build automated alerts when new provisional data is published.

Epidemiological research

Compare crude and age-adjusted death rates by ICD-10 chapter across demographic groups. Use the year-state-sex and year-state-age groupings to feed regression models or longitudinal studies.

Policy and grant applications

Generate state-level mortality benchmarks for grant proposals and policy briefs. The actor's consistent field structure makes it easy to merge CDC data with census or insurance datasets.

Healthcare market analysis

Identify geographic concentrations of specific disease burdens (circulatory, respiratory, neoplasms) to inform hospital network planning, staffing models, and specialty clinic placement.

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🔌 Automating CDC WONDER Mortality Scraper

Connect this actor to your workflow tools using Apify integrations:

• Make (formerly Integromat) - Trigger a run on a schedule, push results to Google Sheets
• Zapier - Auto-export new mortality records to Airtable or Notion
• Slack - Get notified when a new provisional data run completes
• Google Sheets - Sync weekly via the Apify Google Sheets integration
• REST API - Call POST /v2/acts/parseforge~cdc-wonder-mortality-scraper/runs from any application

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🌟 Beyond business use cases

Academic and research

Build longitudinal mortality datasets for peer-reviewed studies. The consistent JSON schema makes it easy to combine multiple years and causes into a single analytical dataset.

Non-profit and advocacy

Document health disparities between states or demographic groups to support public health advocacy campaigns with verified federal data.

Data journalism

Independently verify or expand upon CDC mortality statistics cited in news articles. Cross-reference provisional data with finalized annual counts.

Education

Create teaching datasets for epidemiology, biostatistics, or public health courses. Students can explore real national mortality data without manual portal navigation.

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🤖 Ask an AI assistant about this scraper

"What CDC WONDER fields does this actor return?" "How do I get age-adjusted mortality rates for circulatory disease by state?" "Can I filter by ICD-10 chapter and state at the same time?" "What is the difference between crude rate and age-adjusted rate in the output?"

Paste any of these into an AI assistant along with your dataset to get instant analysis.

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❓ Frequently Asked Questions

What is CDC WONDER? CDC WONDER (Wide-ranging ONline Data for Epidemiologic Research) is a public data system maintained by the U.S. Centers for Disease Control and Prevention. It provides access to the National Vital Statistics System mortality data.

Does this actor require a CDC account or API key? No. CDC WONDER provides a public API that requires no credentials. This actor uses the official XML-based public endpoint.

Why do some death counts come back as null? CDC suppresses cells with fewer than 10 deaths to protect individual privacy. The actor returns null for these values as required by CDC data-use restrictions.

How long does a query take? CDC WONDER queries typically take 30-60 seconds to process on the server side. The actor has a 3-minute timeout and retries twice on transient failures.

What years of data are available? The Underlying Cause of Death database (D76) covers 1999 through the current year. Provisional data for the most recent year may be available through database D176.

Can I get data for a specific state? Yes. Use the state field with the two-digit FIPS code (e.g. "06" for California, "48" for Texas). Leave empty to get all states.

Can I filter by disease type? Yes. Use the icd10Chapter field to filter by any of the 22 ICD-10 chapters (e.g. "I00-I99" for circulatory diseases, "C00-D48" for neoplasms).

What is the age-adjusted rate? The age-adjusted mortality rate standardizes death rates to a reference population age distribution, making it possible to compare rates across states and years without age-composition bias.

How often is CDC WONDER data updated? Final annual data is typically published in the spring of the following year. Provisional data is updated monthly and available via database D159 or D176.

Can I get data broken down by sex or age group? Yes. Use groupBy: "year-state-sex" for sex breakdown or groupBy: "year-state-age" for age group breakdown.

What databases are available? D76 (Underlying Cause of Death 1999-present), D77 (Multiple Cause of Death), D157 (Infant Deaths), D158 (Linked Birth/Infant Death), D159 (Provisional Mortality), D176 (Provisional Underlying Cause).

Is the data free to use? Yes. CDC WONDER data is a U.S. federal government public dataset with no copyright restrictions.

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🔌 Integrate with any app

Connect this actor to thousands of apps via Apify integrations:

Spreadsheets: Google Sheets, Microsoft Excel, Airtable Databases: PostgreSQL, MySQL, MongoDB, BigQuery, Snowflake Automation: Make, Zapier, n8n, Pipedream BI Tools: Tableau, Power BI, Looker, Metabase Storage: Amazon S3, Google Drive, Dropbox Notifications: Slack, Microsoft Teams, Discord, email APIs: Any REST API via webhook trigger

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Disclaimer: This actor is an independent tool built on top of CDC WONDER's publicly available data API. It is not affiliated with, endorsed by, or sponsored by the U.S. Centers for Disease Control and Prevention. All data is sourced from CDC WONDER and subject to its data-use restrictions. Suppressed counts (fewer than 10 deaths) are returned as null in compliance with CDC privacy policies.