Google Global Mobility Data provides anonymized, aggregated trends in human movement across geographic regions. The dataset originates from Google's analysis of location history data from users who enabled this setting. It was published to inform public health responses during the COVID-19 pandemic.
Use Cases
- Model the correlation between retail_and_recreation_percent_change_from_baseline mobility metrics and regional COVID-19 case growth rates.
- Analyze the effectiveness of lockdowns by tracking residential_percent_change_from_baseline trends over time.
- Compare workplace_percent_change_from_baseline and transit_stations_percent_change_from_baseline across countries to assess economic activity recovery.
- Forecast grocery_and_pharmacy_percent_change_from_baseline demand using time-series models on the mobility data.
- Cluster regions using parks_percent_change_from_baseline and other mobility categories to identify similar public behavior patterns.
Strengths
- Data is aggregated from a large, global user base, providing broad coverage.
- Provides consistent, daily percentage change metrics relative to a pre-pandemic baseline.
Limitations
- Data represents a sample of Google users, which may not be demographically representative of entire populations.
- Aggregation and anonymization processes limit granularity, preventing individual-level analysis.
- Temporal coverage is primarily focused on the COVID-19 pandemic period, limiting long-term trend analysis.
Provenance
- Source
- Google LLC
- Collection Method
- Aggregated and anonymized from location history data of users who opted-in.
- Time Range
- Primarily 2020 onward, focused on the COVID-19 pandemic period.
- Freshness
- null
- Geography
- Global, with data reported at country and sub-region levels where statistically significant.