Compare Refugee Origin and Asylum Countries

Analyze where forcibly displaced populations originate and where they are hosted using official UNHCR data. The UNHCR Refugee Data Scraper provides a bounded connector to the authoritative publisher while preserving stable identifiers and source URLs on every row.

Start with a small, reviewable query

{"mode":"population","yearFrom":2020,"yearTo":2025,"maxResults":500}

Run a small sample before expanding the result limit. Inspect identifiers, dates, null values, units, qualifiers, and source fields in the Apify Dataset. Export as JSON for nested fields or CSV and Excel for review. For recurring ingestion, upsert on the publisher stable record dimensions instead of assuming every run is append-only.

Build a reliable data pipeline

The Actor uses direct HTTP requests, bounded inputs, transient-error retries, and explicit empty-result failures. It does not require a browser or paid proxy, so scheduled runs remain inexpensive. Keep the input in an Apify Task, send completion through a webhook, and load the dataset into a warehouse or dashboard. Store collection time downstream so source revisions can be distinguished from newly published records.

Interpret the source responsibly

Official publication does not remove the need for context. Preserve footnotes, status fields, dataset type, reporting period, and source attribution. A missing value is not zero, and a revised record is not necessarily a new event. For legal, medical, financial, safety, protection, or public-policy decisions, confirm material findings with the publisher and a qualified specialist.

This workflow is designed for humanitarian analysts, journalists, and policy researchers. It is an independent integration and is not affiliated with or endorsed by the source institution.

Build a defensible country comparison

Start with one reporting year and one population category. Grouping all displacement categories together can produce a ranking that looks precise but answers no clear question. For origin analysis, aggregate by country of origin and preserve asylum-country detail for drill-down. For host analysis, compare both absolute totals and a contextual denominator such as host population, while sourcing that denominator separately. Sort ties deterministically and label regional aggregates so they are not mistaken for countries. Before publishing a league table, inspect the largest year-over-year changes against UNHCR notes; border changes, methodology revisions, and late reporting can otherwise look like sudden migration events.