Mobility data to track risk in re-opening
Data collaboration is critical to inform COVID-19 policy
By: Mikel Maron
Around the world, governments are either easing or continuing movement restrictions right now, entering populations into a massive real-time, real-world test of the connection between mobility and health risk. Stay at home, shelter in place, and lockdowns have dramatically slowed the spread of COVID-19, and public responsiveness to these orders is clearly visible in measurements of mobility. Now, we are facing new questions: Even as many locations continue to see climbing case and death counts, what impact will different degrees of “reopening” have on how people actually move? Can we spot emerging areas of high risk from mobility trends? What can places slower to ease restrictions learn from other locations, before they act?
Mobility data has so quickly become such a key element of monitoring the COVID-19 response, it’s easy to forget that such data was not at the forefront of emergency response just a short time ago. Location data come from the operating systems, applications, and network connections of mobile phones. In best practice, this data is kept highly secure and free from personally identifiable information. To aid the COVID-19 response, we’ve seen new and more sharing and visualization of aggregated mobility data, with efforts from Facebook, SafeGraph, Cuebiq, Google, and ourselves here at Mapbox.
Under well-regulated agreements, academic researchers, non-profits, technologists, and public health experts are getting direct access to anonymized mobility data. But that access is not enough; a protected place to explore and learn together is needed. Mobility data can be hard to work with and interpret. It is available in varying geographic coverage and resolution depending on the provider. And the data can be incomplete and hold bias from different user bases and variations in mobile device usage. We don’t yet fully understand the relationships between the data and actual behavior, policy measures, or disease risk. All of these challenges speak to the need for cooperation. Efforts like the COVID-19 Mobility Data Network and the SafeGraph COVID-19 Data Consortium show that rapid collaboration is possible in a crisis, while keeping data protection in place. The insights from these research efforts are informing communities and policymakers.
This surge of tech and data cooperation in the COVID-19 response makes me cautiously optimistic that we’re rising to the challenge. It reminds me of the emergence of crisis mapping ten years ago following the Haiti earthquake, when Humanitarian OpenStreetMap Team brought together volunteer mappers and commercial satellite imagery to rapidly create accurate and useful data at scale in this novel way. The data became the base map for the response and changed how we’ve responded to disasters since. I hope we are seeing that level of change with mobility data.
Now as re-opening expands, we need to be faster and forward-looking. Can changes in movement be predicted as restrictions are loosened? Can interventions be adjusted with high precision based on location, types of places, demographics, infection rates, and movement patterns? Can movement data be an early-warning system to help health care providers prepare in locations where there might be an emerging high risk of transmission? Data and analysis are needed, and the results need to be presented with clear utility for decision-makers.
Mapbox is digging into how we can contribute our data and help to answer these questions. If you are a researcher who needs movement data, or building impactful reports for policymakers, read about how we can support you and get in touch.
Maps feature data from Mapbox and OpenStreetMap and their data partners.
