Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle

The coronavirus 2019–2020 pandemic (COVID-19) poses unprecedented challenges for governments and societies around the world (1). Nonpharmaceutical interventions have proven to be critical for delaying and containing the COVID-19 pandemic (2–6). These include testing and tracing, bans on large gatherings, nonessential business and school and university closures, international and domestic mobility restrictions and physical isolation, and total lockdowns of regions and countries. Decision-making and evaluation or such interventions during all stages of the pandemic life cycle require specific, reliable, and timely data not only about infections but also about human behavior, especially mobility and physical copresence. We argue that mobile phone data, when used properly and carefully, represents a critical arsenal of tools for supporting public health actions across early-, middle-, and late-stage phases of the COVID-19 pandemic.

Seminal work on human mobility has shown that aggregate and (pseudo-)anonymized mobile phone data can assist the modeling of the geographical spread of epidemics (7–11). Thus, researchers and governments have started to collaborate with private companies, most notably mobile network operators and location intelligence companies, to estimate the effectiveness of control measures in a number of countries, including Austria, Belgium, Chile, China, Germany, France, Italy, Spain, United Kingdom, and the United States (12–21).

There is, however, little coordination or information exchange between these national or even regional initiatives (22). Although ad hoc mechanisms leveraging mobile phone data can be effectively (but not easily) developed at the local or national level, regional or even global collaborations seem to be much more difficult given the number of actors, the range of interests and priorities, the variety of legislations concerned, and the need to protect civil liberties. The global scale and spread of the COVID-19 pandemic highlight the need for a more harmonized or coordinated approach.

In the following sections, we outline the ways in which different types of mobile phone data can help to better target and design measures to contain and slow the spread of the COVID-19 pandemic. We identify the key reasons why this is not happening on a much broader scale, and we give recommendations on how to make mobile phone data work against the virus.