Using Location Data to Map People’s Movements, Social Distancing Efforts, and the Spread of COVID-19

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When the COVID-19 pandemic hit China and east Asia, mobility data were utilized as part of government’s efforts to combat the virus and limit social contact. This helped enforce lockdown measures and monitor public health. Some criticized this as an invasion of privacy, as sometimes embarrassing information regarding a person’s whereabout became public. Now, in Western states experiencing the onslaught of the COVID-19 pandemic, mobility data is being utilized to gain insights into the economy and social distancing measures. 

Using Location Data to Visualize Social Distancing Compliance

Google might have the largest repository of location data for individuals of any entity. Google has even made a point of publishing this data, although in aggregated and in an anonymous fashion, as Community Mobility Reports. These reports show changes in foot traffic since the transmission of coronavirus reach global proportions. Data until April 2 show foot traffic to retail, grocery, parks, transit, workplace, and residential areas. These data, according to Google, are obtained through users opting in to provide their location timeline to Google. The data are broken down by country and regions within countries. In general, the results reveal large declines in foot traffic to all locations except residential areas, which have increased activity as people stay near or within their homes. The data represent median values of foot traffic and if deviations from known information about users was not easily obtainable, then that data were not included in the reports produced by Google. The data is available for many of the countries that use the popular Android platform for phones or use Google platforms.[1]

Google has released aggreagated location data by country and region to highlight how different areas are responding to social distancing guidelines related to COVID-19.
Google has released aggreagated location data by country and region to highlight how different areas are responding to social distancing guidelines related to COVID-19.

Facebook has also made available location data that can be used to track individual movements. Already, researchers have taken advantage of this released data by conducting modeling and assessment of where hot spots and areas where the coronavirus is likely to spread. Data effectively supplement what Google has provided and can be used to determine the effectiveness of social distancing and mobility in public health. Initial results show that Facebook location data could be used to model the spread of the disease and, therefore, forecast where areas should take given policies of social distancing, including how it might mitigate infections.[2]

Gridded mobility map showing the Boulder / Denver area in Colorado.  The red areas contain few people than normal and the blue areas contain more people than normal. Map: Daniel Larremore and the COVID-19 Mobility Data Network.
Gridded mobility map showing the Boulder / Denver area in Colorado. The red areas contain few people than normal and the blue areas contain more people than normal. Map: Daniel Larremore and the COVID-19 Mobility Data Network.

Using Mobility Data to Model the Spread of COVID-19

Mobility data are not only critical in assessing foot traffic but also are used to model the evolution of COVID-19 as it spreads across populations. Such data can illustrate the rate and spread of COVID-19 based on how well people practice social distancing, how frequently people venture outside, and how effective people are in following official guidelines. On the one hand, governments are beginning to bend in the utilization of data, but in Europe there is a realization that such data are important but need to be protected. Recently, the European Commission (EC) set out rules as to how to make anonymous mobility data can be used in virus spread models and other publicly released data.[3]

Much of the mobility data that utilizes popular social media and Google data are now being used, but this mirrors what was done in China using popular platforms such as WeChat, owned by Tencent, and Baidu’s powerful machine learning and big-data analytics. Many of the developments that helped China respond to the pandemic were based on what was learned from the Haiti Earthquake crisis in 2010 and the Ebola crisis in 2014-2016. In those cases, big data and mobility data from devices helped to track and create a response to the crises, but there were limitations as countries were less connected with such devices that enabled tracking of individuals. However, they did show the potential public health benefit by having such data. In fact, what has recently happened is that social media and geolocation mobile phone data are now used together with other sensor data, including live-stream CCTV and digital measures for temperature. Researchers have called these analytical tools as potentially highly effective in lowering the typical exponential growth curve of the virus spread, but have also voiced that such data have to be not only anonymously given but should be protected so that others cannot use them in the future for other purposes that do not benefit public health.[4]

Big data being collected by large companies, at first in China and now in the West, have a potentially great benefit in combating the spread of COVID-19. However, there are many concerns with how such data are not only used now but they could be used in the future, particularly if these data are not used for public health reasons. For now, the presence of mobility data in particular is helping to demonstrate the economic impact of the coronavirus and helping to mitigate its impact on public health.

References

[1]    For more on Google’s data and methodology on how it was collected and analyzed, see: https://www.google.com/covid19/mobility/.


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[2]    For a discussion on this recent work, see:  https://techxplore.com/news/2020-04-mathematician-facebook-covid-.html.

[3]    For more on recent changes to EC guidelines on mobility data, see:  https://www.mobileworldlive.com/featured-content/top-three/ec-sets-out-rules-for-covid-19-mobility-tracking/.

[4]    For more on the benefits of big data in public health but also the concerns, see:  Ienca M and Vayena E (2020) On the responsible use of digital data to tackle the COVID-19 pandemic. Nature Medicine. DOI: 10.1038/s41591-020-0832-5.

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