# FDA Tobacco Problem Reports Scraper — Vape & E-Cig Safety Data (`compute-edge/fda-tobacco-problem-reports-scraper`) Actor Extract consumer-reported tobacco problem reports from the FDA openFDA API. Health and product problems for e-cigarettes, vapes, and tobacco products. Filter by health problem and keyword. JSON or CSV. - **URL**: https://apify.com/compute-edge/fda-tobacco-problem-reports-scraper.md - **Developed by:** [Compute Edge](https://apify.com/compute-edge) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## FDA Tobacco Problem Reports Scraper — Vape & E-Cig Safety Data Extract **consumer-reported tobacco problem reports** from the **FDA openFDA** Tobacco Problem Report database. These are real-world safety signals submitted to the U.S. Food & Drug Administration about **e-cigarettes, vapes, e-liquids, cigarettes, cigars, hookah, and smokeless tobacco** — including the health problems experienced and the product malfunctions reported. This Actor turns the openFDA tobacco endpoint into clean **JSON, CSV, or Excel**, ready for safety-signal analysis, regulatory monitoring, public-health research, or litigation support. ### What you get | Field | Description | |-------|-------------| | `reportId` | Unique FDA tobacco problem report ID | | `dateSubmitted` | Date the report was submitted to FDA | | `tobaccoProducts` | Product category/categories named in the report | | `reportedHealthProblems` | Health problems experienced (e.g. Seizure, Headache, Burn) | | `reportedProductProblems` | Product malfunctions reported (e.g. overheating, leaking) | | `nonuserAffected` | Whether a non-user (bystander) was affected | | `numberHealthProblems` | Count of distinct health problems in the report | | `numberProductProblems` | Count of distinct product problems | | `numberTobaccoProducts` | Count of products named in the report | ### Why this matters Tobacco and vaping safety is a fast-moving regulatory and legal arena. Structured access to FDA problem reports lets you: - **Monitor safety signals** for specific product types (e.g. spikes in e-cigarette seizure reports) - **Support regulatory and policy research** with primary-source FDA data - **Power litigation and product-liability analysis** with verifiable government records - **Feed dashboards and LLM agents** with clean, query-ready safety data ### How to scrape FDA tobacco problem reports 1. Click **Try for free**. 2. Choose your filters: - **Health Problem** — keep only reports mentioning a problem like `Seizure` or `Burn`. - **Search Query (advanced)** — optional raw openFDA Lucene expression, e.g. `tobacco_products:"E-cigarette"`. - **Max Results** — cap the run, or set `0` for everything that matches. 3. Click **Start** and download as JSON, CSV, or Excel. #### Example input ```json { "healthProblem": "Seizure", "maxResults": 500 } ```` #### Example output ```json { "reportId": 822, "dateSubmitted": "04/21/2019", "tobaccoProducts": "Electronic cigarette, electronic nicotine or vaping product", "reportedHealthProblems": "Seizure grand mal", "reportedProductProblems": "Other", "nonuserAffected": "No", "numberHealthProblems": 1, "numberProductProblems": 1, "numberTobaccoProducts": 1 } ``` ### Pricing This Actor uses **pay-per-result** pricing — a few cents per run for hundreds of structured reports, plus standard Apify compute. Far cheaper than building and maintaining your own openFDA integration. ### FAQ **Where does the data come from?** The official openFDA Tobacco Problem Report API (`api.fda.gov/tobacco/problem.json`). Only public, de-identified report data is returned. **How fresh is the data?** Each run queries openFDA live, so reports appear as soon as the FDA publishes them in the dataset. **Do I need an API key?** No. The Actor uses the public, key-free openFDA endpoint and paginates within its limits. **Can I get the whole dataset?** Yes — set `maxResults` to `0` to paginate through all available reports. ### Other Actors Working with FDA data? Combine this with our other FDA drug, device, recall, and openFDA scrapers on the Apify Store. ### Legal This Actor retrieves only **publicly available, de-identified** problem-report data published by the FDA via openFDA. It does not access personal data or bypass authentication. The openFDA data carries the FDA disclaimer that it should not be used as the sole basis for medical or regulatory decisions. You are responsible for compliant use of the output. # Actor input Schema ## `searchQuery` (type: `string`): Optional raw openFDA search expression (Lucene syntax). Example: 'tobacco\_products:"E-cigarette"'. Leave blank to return all reports. ## `healthProblem` (type: `string`): Filter to reports mentioning a specific reported health problem. Examples: 'Seizure', 'Headache', 'Cough'. ## `maxResults` (type: `integer`): Maximum number of problem reports to return. Set to 0 for unlimited (all matching reports). ## Actor input object example ```json { "searchQuery": "", "healthProblem": "", "maxResults": 1000 } ``` # Actor output Schema ## `dataset` (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 = { "searchQuery": "", "healthProblem": "", "maxResults": 1000 }; // Run the Actor and wait for it to finish const run = await client.actor("compute-edge/fda-tobacco-problem-reports-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 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); }); // 📚 Want to learn more 📖? Go to → 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 = { "searchQuery": "", "healthProblem": "", "maxResults": 1000, } # Run the Actor and wait for it to finish run = client.actor("compute-edge/fda-tobacco-problem-reports-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchQuery": "", "healthProblem": "", "maxResults": 1000 }' | apify call compute-edge/fda-tobacco-problem-reports-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=compute-edge/fda-tobacco-problem-reports-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "FDA Tobacco Problem Reports Scraper — Vape & E-Cig Safety Data", "description": "Extract consumer-reported tobacco problem reports from the FDA openFDA API. Health and product problems for e-cigarettes, vapes, and tobacco products. Filter by health problem and keyword. JSON or CSV.", "version": "0.1", "x-build-id": "9SwnHJa9xHqeDHpQq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/compute-edge~fda-tobacco-problem-reports-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-compute-edge-fda-tobacco-problem-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/compute-edge~fda-tobacco-problem-reports-scraper/runs": { "post": { "operationId": "runs-sync-compute-edge-fda-tobacco-problem-reports-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/compute-edge~fda-tobacco-problem-reports-scraper/run-sync": { "post": { "operationId": "run-sync-compute-edge-fda-tobacco-problem-reports-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQuery": { "title": "Search Query (advanced)", "type": "string", "description": "Optional raw openFDA search expression (Lucene syntax). Example: 'tobacco_products:\"E-cigarette\"'. Leave blank to return all reports.", "default": "" }, "healthProblem": { "title": "Health Problem", "type": "string", "description": "Filter to reports mentioning a specific reported health problem. Examples: 'Seizure', 'Headache', 'Cough'.", "default": "" }, "maxResults": { "title": "Max Results", "minimum": 0, "maximum": 50000, "type": "integer", "description": "Maximum number of problem reports to return. Set to 0 for unlimited (all matching reports).", "default": 1000 } } }, "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 } } } } } } } } } } ```