UEFA EURO 2024 contact study

This dataset supports a study of close-range contacts associated with mass gathering events (MGEs), including football matches, concerts, festivals, and fairs, based on anonymized, individual-level GPS location data from roughly 350,000 mobile phone users across Germany, collected between April and August 2024. Potential infectious-disease-relevant contacts were inferred from close spatio-temporal co-location (16 m / 10 min resolution) and linked to contact settings (e.g. public transport, leisure venues, stadiums) using OpenStreetMap data. The study compares contact exposure across mass gathering events of various types, including UEFA EURO 2024 matches in Germany's 10 host cities, major concerts, festivals, and Bundesliga matches, on a unified exposure scale, and examines how contact patterns unfold in time and space around these events. This deposit contains the anonymized subset of the underlying data needed to reproduce every figure and table in the accompanying paper: device IDs are one-way hashed and a handful of internal bookkeeping columns (spatial/temporal tile IDs, raw ping coordinates already folded into aggregated contact records) are dropped; nothing else is altered. It includes: metadata/: panel size, ping-frequency, and stadium/event/vacation metadata for the 10 host cities fig1/: co-location contact counts and sensitivity-analysis data (host city, host venue, and Germany-wide) fig3/: hourly contact dynamics around individual events fig4/: contacts mapped to OpenStreetMap contact settings (host cities) fig5/: device-pair-level contact recurrence and home-to-home distance data ("small-worldness") fig6/: nationwide OpenStreetMap-based contact clustering figs1/: raw ping locations for illustrative city/day examples The full analysis pipeline (one Jupyter notebook per figure/table) and the manuscript are maintained on GitHub at github.com/st-sch/nc-euro24. Unzipping this deposit into that repository's data/ folder is sufficient to reproduce every published figure and table byte-for-byte, without needing access to the original, unredacted dataset or any database connection.