TNL R3 – Modeling Movement in a Pandemic

TNL RAND Researcher Residency – Tim Gulden

This project is exploring the use of “volunteered” mobile device data to better understand the network of human contact over which Covid-19 (and much of human culture) spreads within an American city. Specifically, we are looking at a set of 2.2 billion “pings” in the Portland, Ore. Metropolitan region between January and April 2020. These data were obtained from UberMedia – a company that aggregates, analyzes, and resells position information from over 150,000 smart phone apps where the user has agreed to share their position with the app developer and its partners.

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Mobile device “pings” in Portland, OR

We have applied big-data methods (primarily PySpark on RAND’s internal cluster) to process these points and explore several approaches to building a contact network. We find that the data are sparser than anticipated, making a simple transmission network unworkable. In light of this limitation, we are developing a method relying on some basic behavioral assumptions and composing data over time to produce a network that has many of the properties of the full contact network.

TNL R3 – Modeling Movement in a Pandemic

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