Beyond Mobility Metrics | Part One

Jackie Barbieri • July 1, 2020

Part One | Part Two | Part Three

Better Forecasts of COVID-19 Transmission Using Potential Contact Analytics

While “mobility metrics” can help policymakers understand the extent to which the public is in compliance with mandated movement restrictions[i], they do not provide insight into the frequency of close interactions between individuals outside of the home: a key driver of disease transmission. Understanding where and when close contact events are occurring, where high-contact populations reside, and which regions are most connected via close contacts is critically important to leaders weighing decisions about when to lift or ease policies, or when it is safe to re-open businesses during the COVID-19 pandemic. Whitespace Solutions, in partnership with Dr. Forrest W. Crawford (Associate Professor of Biostatistics, Statistics & Data Science, Operations, and Ecology & Evolutionary Biology), has developed analytics that measure the rate of potential contacts using mobility data. Our potential contact analytics offer critical epidemiological intelligence that the noisy landscape of social distancing metrics cannot: reliable indicators of infection risk by region, even as conditions and guidelines change.

In this three part series, we will explain how our analytics provide a unique and reliable indicator of transmission. Close contact is the driving force for disease transmission. In part two, we explore this key driving force and how we derive our metrics from this principle.

[i] Buckee et al., “Aggregated Mobility Data Could Help Fight COVID-19.”

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