Authorities around the world are working hard to understand how people are altering their behavior as rules around social distancing begin to change. Gathering data on where people are congregating is a valuable measure for understanding risks and calculating the likelihood of a second wave of infections. To help provide these insights, we developed our Hotspots map. We define a Hotspot as a city block in which more than 50 people are gathered at the same time for more than 15 minutes - excluding homes and other residences.

Cellphone geolocation data has proven to be an invaluable tool in helping us understand how COVID-19 is evolving, and to support our recovery. We have been working closely with clients and other partners to help track the evolution of the pandemic and how it is impacting different sectors, among the most important of which is hospitals. To help visualize the environment that hospitals are operating under, as well as to provide a measure of hospital bed utilization which is an important metric of the available capacity of the hospitals, we generated a detailed analysis of hospital traffic, filtering out doctors, staff, and visits that did not result in long-term admissions, in order to estimate the actual hospital bed utilization during the pandemic.

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The biggest mall operator in the US, Simon Group, announced this week that it will open dozens of locations across the US. With Macy’s and other retailers following suit in states where restrictions have been relaxed, investors, consumers and retailers will be watching with interest to see how soon visitor numbers begin to recover. One indicator of customer appetite for returning to stores in the US is to look at how foot traffic to malls in China has fared since restrictions began to be lifted in late February and early March.

When we launched Advan 5 years ago, we were really excited at the prospect of developing a new type of dataset. One that would give investors an alternative view into the companies and markets that they care about. We are data geeks at heart and we spent years agonizing over how to make our data more precise; manually drawing geofences around millions of locations, for thousands of companies. Normalizing data became almost an obsession.