Mobility Australia

The Challenge

Despite the abundance of high-quality public human population mobility data, the current outbreak of COVID-19 has demonstrated that data is a key ingredient in modelling the spread of infectious diseases across populations.

The challenge for Australia is to develop a comprehensive human population mobility dataset needed for further research in the health domain to prevent and control future disease outbreaks without overwhelming local health systems.

The Response

This project addresses the challenge of transforming available mobility data into a consistent format suitable for analysis in a range of research areas such as public health, transport analytics, emergency and disaster management, and border security. Bringing these datasets together will improve the quality and coverage of existing datasets. 

The final data asset will be hosted and made publicly available on the Australian Urban Research Infrastructure Network (AURIN), enabling data downloads at different spatial and temporal resolutions.

Who Will Benefit

This project supports research requiring an understanding of the patterns of human movement across Australia, such as in the health domain to model and predict the spread of infectious diseases. The data asset will also be useful in other areas of research such as transport analytics, emergency and disaster management, and border security.

Urban planners, engineers, and government agencies requiring an understanding of the patterns of human movement across Australia will benefit from access to the Mobility Australia data asset.

The Partners

Our partners are:

• CSIRO
• QUT
• University of Melbourne
• AURIN.

Target Outcomes

This project addresses the challenge of transforming available mobility data into a consistent format that is suitable for analysis in a broad range of research areas. Merging the various individual datasets into Australia’s first comprehensive, national-scale human mobility data asset drastically improves the quality and coverage of those existing datasets.