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Understanding human mobility and migration patterns caused by economic distress or a career move, escape from political turmoil or violence, natural disasters, or tourism require access to timely and reliable data for an adequate policy response. Most recently, the COVID-19 pandemic has exacerbated the need for timely mobility data to predict the spread of the virus, design efficient containment policies, and evaluate the effects of lockdowns and other measures. Under these pressing circumstances, governments and statistical communities have turned their attention towards mobile phone data.  

Mobile phone data come in several forms, such as signaling data and call detail records (CDR). These data are generated automatically, collected by mobile network operators (MNOs) and commonly referred to as mobile positioning data (MPD). While signaling data provide updates about a mobile phone’s location, CDR provide information on each transaction, be it a telephone call or a text message, such as time, duration, source number, destination number, and approximate location of communications. Location and mobility data can also be harvested from mobile applications that collect users’ geolocation for their services, such as contact tracing apps. But this information is usually collected and held, with users’ consent, by the Internet companies and not the mobile network operators.  

For several years, the statistical community in Asia and the Pacific has been exploring the use of MPD for tourism, migration, and commuting statistics. For example, Statistics Indonesia partnered with Telkomsel, the country’s largest telecom operator with more than 170 million subscribers, and Positium, an Estonian company specializing in mobile positioning data analysis. Through this partnership, Statistics Indonesia developed algorithms that are applied to Telkomsel’s data within its premises to generate insights into commuting, tourism, metropolitan statistical areas (MSA), and migration. In 2018, it also analyzed mobile positioning data to measure visitors at the ASIAN Games and the WB-IMF Meeting. As a member of the UNCEBD Task Team on Mobile Phone Data, Statistics Indonesia also contributed to the Handbook on the Use of Mobile Phone Data for Official Statistics.

The COVID-19 pandemic put increased focus on the need for timely mobility data. Statistics Indonesia and other statistical offices with access to mobile positioning data, such as Statistics Korea or Data Ventures of Statistics New Zealand, leveraged their partnerships with the MNOs to respond to the pandemic. KOSTAT conducted population movement analysis before and after COVID-19, and Data Ventures developed the Report of COVID-19 impact on Local Council’s central business districts (CBD) Population. The a2i (Access to Information) team of the ICT Ministry of Bangladesh negotiated access to mobile phone data from several telecom operators at the onset of the pandemic to track the spread of COVID-19 in near real-time.

Despite the growing appetite from governments and statistical offices for mobile phone data and their benefits for estimating human mobility, access to this type of data brings challenges too. Personal data protection and data sharing consent remain a top priority for the national statistical offices as declared in the Principle 6 in the “Fundamental Principles of Official Statistics”, adopted by the UN Statistical Commission in 2013. In the absence of regulation guiding access to private sector data, governments need to consider data privacy and security issues, data acquisition costs, data supply continuity, and technical capacity for analyzing this data type.

Building partnerships with mobile network operators could help address these challenges. Data partnerships can take different forms depending on the country, mobile network operators’ openness for collaboration, and the national regulatory frameworks. Some statistical offices, such as Statistics Indonesia, partnered directly with the telecom operator and established the data exchange procedures and quality assurance frameworks. Others, such as Geostat, work closely with the national regulatory authority. While access to data comes at a cost, Statistics Indonesia found it cost-effective by requiring only one-eighth of the traditional survey budget. However, with the use of mobile phone data, the power dynamics and the production of mobility statistics are changing. Statistical offices are not the ones collecting and analyzing raw data, but rather algorithm developers receiving data services from the mobile network operators. Therefore, new data sources are calling for new partnership models.    

To address the growing interest in mobile phone data in the region, and showcase successful examples of accessing and using these data for official statistics, ESCAP is organizing a Stats Café on Mobile phone data for official statistics – addressing data accessibility, privacy, and regulatory issues on Monday 5 April 2021. ESCAP has also recently documented the use cases of mobile phone data and other big data sources in theStats Briefs on Big data for economic statistics .

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Irina Bernal
Consultant, ESCAP Statistics Division
Tanja Sejersen
Statistician
Titi Kanti Lestari
Director of Finance, IT and Tourism Statistics, BPS Statistics Indonesia
Karoly Kovacs
Data Innovation and Capacity Development Branch, UN Statistics Division
Statistics +66 2 288-1234 stat.unescap@un.org
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