# OSHA Severe Injury Reports Scraper (`automation-lab/osha-severe-injury-reports-scraper`) Actor Export OSHA severe workplace injury reports by state, date, NAICS, employer, city, and injury type from the official public SIR dataset. - **URL**: https://apify.com/automation-lab/osha-severe-injury-reports-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## OSHA Severe Injury Reports Scraper Extract OSHA Severe Injury Reports from the official public SIR dataset. Filter by event date, state, NAICS industry, employer, city, and injury type, then export normalized incident records with narratives, counts, geocodes, and dataset provenance. ### What does OSHA Severe Injury Reports Scraper do? OSHA Severe Injury Reports Scraper downloads the public OSHA Severe Injury Reports ZIP file, streams the CSV inside it, applies your filters, and saves matching severe workplace injury incidents to an Apify dataset. Use it when you need structured access to OSHA SIR records without manually downloading a large CSV and filtering it in a spreadsheet. The actor is designed for: - ๐Ÿš‘ severe injury monitoring - ๐Ÿญ employer and facility risk research - ๐Ÿงฐ industrial safety market intelligence - ๐Ÿ“ state and city incident analysis - ๐Ÿงพ compliance and insurance workflows ### Who is it for? Safety and compliance consultants can monitor recent hospitalizations, amputations, and loss-of-eye incidents by employer, region, or industry. Insurance analysts can identify employers and industries with recent severe injury events for risk review. Industrial suppliers and remediation vendors can discover companies with recent safety incidents that may need training, PPE, guarding, or corrective-action support. Journalists and researchers can export filtered OSHA incident narratives for regional or industry reporting. Legal and expert-witness teams can search public injury narratives by company, state, city, and NAICS sector. ### Why use this scraper instead of the OSHA dashboard? The OSHA dashboard is useful for interactive browsing, but repeat workflows usually need automation. This actor lets you: - schedule repeat checks - export JSON, CSV, Excel, RSS, or API data - filter before export - keep dataset provenance with each record - integrate with CRMs, BI tools, notebooks, and alerts - avoid repeatedly handling the full raw CSV manually ### What data can you extract? Each output item represents one OSHA Severe Injury Report row. | Field | Description | | --- | --- | | `reportId` | OSHA severe injury report ID | | `eventDate` | Incident date in ISO format | | `employer` | Employer name from OSHA | | `address`, `city`, `state`, `zip` | Incident location fields | | `latitude`, `longitude` | OSHA geocode coordinates where available | | `primaryNaics` | Primary NAICS code | | `hospitalizedCount` | Number of hospitalizations | | `amputationCount` | Number of amputations | | `lossOfEyeCount` | Number of eye-loss events | | `inspectionId` | OSHA inspection ID where present | | `finalNarrative` | OSHA narrative description | | `natureTitle` | Injury nature description | | `partOfBodyTitle` | Body part affected | | `eventTitle` | Event/exposure description | | `sourceTitle` | Source of injury | | `datasetFilename` | OSHA ZIP filename used | | `datasetUrl` | Source ZIP URL | | `scrapedAt` | Actor run timestamp | ### How much does it cost to extract OSHA injury reports? This actor uses pay-per-event pricing. - Start fee: $0.005 per run - Per saved report: formula-derived tiered pricing from $0.000039236 down to $0.00001 depending on your Apify plan tier The actor does not use proxies. Costs are mainly compute time for downloading and scanning the public OSHA CSV plus the per-item charge for records saved. Use a small `maxItems` value for tests. Increase it for production exports or scheduled monitoring. ### Input options | Input | Purpose | | --- | --- | | `maxItems` | Maximum matching reports to save | | `startDate` | Include reports on or after a date | | `endDate` | Include reports on or before a date | | `states` | State names or USPS abbreviations | | `naicsPrefixes` | Match Primary NAICS code prefixes | | `employerQuery` | Case-insensitive employer substring | | `cityQuery` | Case-insensitive city substring | | `hospitalizedOnly` | Require hospitalization count greater than zero | | `amputationOnly` | Require amputation count greater than zero | | `lossOfEyeOnly` | Require loss-of-eye count greater than zero | | `datasetUrl` | Optional direct OSHA ZIP URL | | `includeRawRecord` | Include the original CSV row for audit workflows | ### Example input ```json { "maxItems": 100, "startDate": "2024-01-01", "states": ["TX"], "hospitalizedOnly": true } ```` ### Industry monitoring example Use NAICS prefixes to monitor a sector. ```json { "maxItems": 500, "startDate": "2023-01-01", "states": ["CA", "NV", "AZ"], "naicsPrefixes": ["23"], "amputationOnly": true } ``` This exports severe injury reports in construction-related NAICS codes for selected states. ### Employer watchlist example ```json { "maxItems": 50, "startDate": "2024-01-01", "employerQuery": "Academy", "includeRawRecord": true } ``` Use this for company-specific compliance research or lead qualification. ### Output example ```json { "reportId": "2024010001", "eventDate": "2024-01-01", "employer": "Academy Sports and Outdoors", "city": "FORT WORTH", "state": "TEXAS", "primaryNaics": "424330", "hospitalizedCount": 1, "amputationCount": 0, "lossOfEyeCount": 0, "inspectionId": "1720720", "finalNarrative": "An employee was testing a bike...", "datasetFilename": "January2015toOctober2025.zip", "sourcePageUrl": "https://www.osha.gov/severe-injury-reports" } ``` ### How to run the actor 1. Open the actor on Apify. 2. Enter your filters. 3. Set `maxItems` to a small number for a first run. 4. Start the actor. 5. Download results from the Dataset tab. 6. Schedule the actor if you need repeat monitoring. ### Tips for better results - Use state filters to keep exports focused. - Use NAICS prefixes rather than full NAICS codes when researching broad industries. - Leave `endDate` empty to include the newest OSHA dataset month. - Use `includeRawRecord` only when you need audit-grade raw CSV fields. - Combine `startDate` with scheduled runs for recent-incident monitoring. ### Integrations You can connect the output dataset to: - Google Sheets for analyst review - Slack alerts for new severe incidents - Airtable or HubSpot for outreach workflows - Power BI or Tableau for safety dashboards - Python notebooks for injury trend analysis - Apify webhooks for automated incident monitoring ### API usage with Node.js ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('automation-lab/osha-severe-injury-reports-scraper').call({ maxItems: 100, startDate: '2024-01-01', states: ['TX'], hospitalizedOnly: true, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### API usage with Python ```python from apify_client import ApifyClient client = ApifyClient('MY-APIFY-TOKEN') run = client.actor('automation-lab/osha-severe-injury-reports-scraper').call(run_input={ 'maxItems': 100, 'startDate': '2024-01-01', 'states': ['TX'], 'hospitalizedOnly': True, }) items = client.dataset(run['defaultDatasetId']).list_items().items print(items) ``` ### API usage with cURL ```bash curl -X POST 'https://api.apify.com/v2/acts/automation-lab~osha-severe-injury-reports-scraper/runs?token=MY-APIFY-TOKEN' \ -H 'Content-Type: application/json' \ -d '{"maxItems":20,"startDate":"2024-01-01","states":["TX"],"hospitalizedOnly":true}' ``` ### MCP usage Use this actor from Claude through Apify MCP: ```text https://mcp.apify.com/?tools=automation-lab/osha-severe-injury-reports-scraper ``` Add the Apify MCP server in Claude Code: ```bash claude mcp add apify --url "https://mcp.apify.com/?tools=automation-lab/osha-severe-injury-reports-scraper" ``` Or configure an MCP client with JSON: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com/?tools=automation-lab/osha-severe-injury-reports-scraper" } } } ``` Example prompts: - "Run the OSHA Severe Injury Reports Scraper for Texas hospitalizations since 2024 and summarize the top injury narratives." - "Find recent OSHA severe injury reports for construction NAICS code 23 in California." - "Export employer names and cities from OSHA amputation reports in the Midwest." ### Scheduling and monitoring For monitoring, schedule the actor weekly or monthly with a recent `startDate`. A common workflow: 1. Run monthly for selected states and NAICS sectors. 2. Store the dataset in Apify. 3. Send new records to Slack or email. 4. Review narratives and employer names. 5. Route high-priority incidents to sales, safety, or compliance teams. ### Data source notes The actor uses OSHA's public Severe Injury Reports dataset. The dataset is a federal OSHA public data source and may exclude or represent state-plan jurisdiction data according to OSHA's own publication rules. Always verify regulatory conclusions with the original OSHA source. OSHA updates the downloadable file periodically. The actor records the dataset filename and URL used for each item so exports remain traceable. ### Legality and responsible use This actor reads a public government dataset. It does not bypass authentication, captchas, or private systems. You are responsible for using the data lawfully, respecting privacy and employment-law obligations, and verifying facts before taking legal, employment, insurance, or safety actions. ### FAQ and troubleshooting #### Why did I get zero results? Your filters may be too narrow. Remove employer or city filters first, then widen date range, state, or NAICS filters. #### Why does a small run scan many rows? The OSHA ZIP contains a large historical CSV. The actor streams it and stops when it finds enough matching rows, but rare filters may require scanning the full file. #### Why are some inspections missing? Not every severe injury report has an inspection ID in the public CSV. ### Related scrapers Explore related Automation Lab actors: - https://apify.com/automation-lab/osha-inspections-violations-scraper - https://apify.com/automation-lab/cpsc-recalls-scraper - https://apify.com/automation-lab/fda-recalls-scraper ### Changelog - 0.1.0: Initial release with OSHA SIR ZIP discovery, CSV streaming, filters, normalized output, and dataset provenance. ### Support If you need a new filter or output field, open an issue on the actor page and include a sample OSHA report or workflow. # Actor input Schema ## `maxItems` (type: `integer`): Maximum number of matching OSHA severe injury reports to save. Use a low number for tests and increase for monitoring or exports. ## `startDate` (type: `string`): Include reports on or after this event date (YYYY-MM-DD). Leave empty to start from January 2015. ## `endDate` (type: `string`): Include reports on or before this event date (YYYY-MM-DD). Leave empty for the newest OSHA dataset month. ## `states` (type: `array`): State names or USPS abbreviations to include, e.g. TX, California, New York. Leave empty for all states in the OSHA SIR dataset. ## `naicsPrefixes` (type: `array`): Filter by Primary NAICS code prefix. Examples: 23 for construction, 336 for transportation equipment manufacturing, 48 for transportation. ## `employerQuery` (type: `string`): Case-insensitive substring to match in the Employer field, such as a company name or brand. ## `cityQuery` (type: `string`): Case-insensitive substring to match in the City field. ## `hospitalizedOnly` (type: `boolean`): Only include reports where OSHA recorded one or more hospitalizations. ## `amputationOnly` (type: `boolean`): Only include reports where OSHA recorded one or more amputations. ## `lossOfEyeOnly` (type: `boolean`): Only include reports where OSHA recorded one or more losses of an eye. ## `datasetUrl` (type: `string`): Optional direct URL to an OSHA Severe Injury Reports ZIP file. Leave empty to auto-discover the latest ZIP from the OSHA dashboard. ## `includeRawRecord` (type: `boolean`): Attach the original CSV row to each output item for audit/debug workflows. This increases export size. ## Actor input object example ```json { "maxItems": 20, "startDate": "2024-01-01", "states": [ "TX" ], "hospitalizedOnly": false, "amputationOnly": false, "lossOfEyeOnly": false, "includeRawRecord": false } ``` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "maxItems": 20, "startDate": "2024-01-01", "states": [ "TX" ] }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/osha-severe-injury-reports-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "maxItems": 20, "startDate": "2024-01-01", "states": ["TX"], } # Run the Actor and wait for it to finish run = client.actor("automation-lab/osha-severe-injury-reports-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 20, "startDate": "2024-01-01", "states": [ "TX" ] }' | apify call automation-lab/osha-severe-injury-reports-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/osha-severe-injury-reports-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "OSHA Severe Injury Reports Scraper", "description": "Export OSHA severe workplace injury reports by state, date, NAICS, employer, city, and injury type from the official public SIR dataset.", "version": "0.1", "x-build-id": "sFct1Ok7piHLCKjeQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~osha-severe-injury-reports-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-osha-severe-injury-reports-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~osha-severe-injury-reports-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-osha-severe-injury-reports-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~osha-severe-injury-reports-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-osha-severe-injury-reports-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "maxItems": { "title": "Maximum reports", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Maximum number of matching OSHA severe injury reports to save. Use a low number for tests and increase for monitoring or exports.", "default": 20 }, "startDate": { "title": "Start date", "type": "string", "description": "Include reports on or after this event date (YYYY-MM-DD). Leave empty to start from January 2015." }, "endDate": { "title": "End date", "type": "string", "description": "Include reports on or before this event date (YYYY-MM-DD). Leave empty for the newest OSHA dataset month." }, "states": { "title": "States", "type": "array", "description": "State names or USPS abbreviations to include, e.g. TX, California, New York. Leave empty for all states in the OSHA SIR dataset.", "items": { "type": "string" } }, "naicsPrefixes": { "title": "NAICS code prefixes", "type": "array", "description": "Filter by Primary NAICS code prefix. Examples: 23 for construction, 336 for transportation equipment manufacturing, 48 for transportation.", "items": { "type": "string" } }, "employerQuery": { "title": "Employer contains", "type": "string", "description": "Case-insensitive substring to match in the Employer field, such as a company name or brand." }, "cityQuery": { "title": "City contains", "type": "string", "description": "Case-insensitive substring to match in the City field." }, "hospitalizedOnly": { "title": "Hospitalizations only", "type": "boolean", "description": "Only include reports where OSHA recorded one or more hospitalizations.", "default": false }, "amputationOnly": { "title": "Amputations only", "type": "boolean", "description": "Only include reports where OSHA recorded one or more amputations.", "default": false }, "lossOfEyeOnly": { "title": "Loss-of-eye reports only", "type": "boolean", "description": "Only include reports where OSHA recorded one or more losses of an eye.", "default": false }, "datasetUrl": { "title": "Custom OSHA dataset ZIP URL", "type": "string", "description": "Optional direct URL to an OSHA Severe Injury Reports ZIP file. Leave empty to auto-discover the latest ZIP from the OSHA dashboard." }, "includeRawRecord": { "title": "Include raw OSHA CSV row", "type": "boolean", "description": "Attach the original CSV row to each output item for audit/debug workflows. This increases export size.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```