How does smartphone data work in controlling Coronavirus?

Arlene Zhang

Israel just authorised the country’s internal security agency to tap into a vast secret trove of cellphone data to retrace the movements of people who have contracted the coronavirus.

Israel just authorised the country’s internal security agency to tap into a vast secret trove of cellphone data to retrace the movements of people who have contracted the coronavirus. They intend to use it to identify people who have crossed paths with known cases of corona virus infections.

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The U.S. government and tech industry are discussing ways to use smartphone location data to combat coronavirus.

China has used smartphone data to effectively track, control and isolate infectious sources.

Smartphone data is restricted, with protections that vary from country to country, but the decision to access this private data for the sake of the public interest is made far easier during times of emergency.

Who controls the smartphone data?

In every country, telecom companies operate huge networks. Data centres combined with millions of base station resources and hundreds of millions of users, generating and collecting Petabytes of data daily. This data flows through and between networks to facilitate high speed communications all over the world.

How can telecom companies know us?

Technically, telecom companies can use Deep Packet Inspection (DPI) technology to see the sender, the receiver and the content of each data packet flowing though their networks, like opening an envelope and reading its contents. This data can be collected by telecom companies by monitoring our traffic and can be sold to other companies for such things as specialized and targeted advertising.

Telecom companies can use phone numbers or IP addresses as unique IDs to integrate various types of data, form dynamic tags for each user, and depict people’s daily lives in many dimensions. They have a considerable social responsibility.

In China to operate a telecom business, the companies must have state-owned equity with shares not less than 51 percent. These companies know almost everything about us, who are we, where are we, what we are doing and when we are doing it.

Some of the things they can do:

User profiling:

  •  Gender: analysing gender-related interests
  • Age: differentiate the age groups
  •  Consumption: assessing income and purchasing power

Social circle analysis:

  •  Phone Contact: available from voice calls
  • SMS contacts: details available via SMS
  • IM contacts: WeChat, QQ and other APPs
  •  Work place: explore the commonalities of people in the same work place
  • Community: features of neighbourhood, group profiling

User preference:

  • APP / website preferences: on which apps / websites have more clicks and long dwell time
  • Search / post preferences: extract keywords to summarise user interests and develop potential customers
  • Time preference: in what time to use related services
  •  Geolocation: in where to use the related services

In fact, big international operators such as AT&T, Verizon, Telefonica and DoCoMo are actively commercialising data and conducting in-depth cooperation with enterprises and institutions in the fields of finance, retail, tourism, and public management.

How smartphone data has been used to control the coronavirus in China?

Smartphone data plays an important role in monitoring population movements and supporting the prevention of coronavirus. The Ministry of Industry and Information Technology of China has officially deployed telecom operators’ big data to support the prediction and prevention of coronavirus from 24th January, 2020.

The coronavirus is very contagious and spreads fast. With an incubation period of up to 24 days it has brought great challenges to epidemic prevention.

Through operators’ big data, the authorities have obtained complete location data on user’s communications via base stations, from countries, provinces, cities, to streets, and buildings. Based on such data, the following functions can be implemented:

  1. Trace population migration data across provinces and cities, and obtain inflow / outflow population data;
  2. Screen out residents in the community or building where the epidemic has occurred;
  3. Based on time and location two-dimensional data, trace back diagnosed patients’ location trajectory, and then find people who have taken the same transportations or have been in close contact with infected patients;
  4. Build a platform where individuals can search whether they have been same location with the diagnosed patients. Specifically, the public places that they have visited in the past 14 days, buses, restaurants, cinemas, etc.;
  5. Based on the long-term resident and roaming data of the telecom companies’ data systems, large-scale population migration can be predicted, and it can provide a reference for the advance layout of the epidemic prevention battle before the crowd migration wave arrives.

Telecom companies’ data can help us find those who were exposed to coronavirus. For example, in Beijing, where the risk of an outbreak is high, people can be filtered based on location information:

  • Category 1: People returning to Beijing from a severely affected area within 14 days;
  • Category 2: People returning to Beijing within 14 days and passing through a severely infected area on their way back to Beijing;
  •  Category 3: People who live in the community or building where the coronavirus was found;
  • Category 4: People have been in close contact for a long time or people who took the same transport with diagnosed patients.

There is a high probability that there are reservoirs of infection in the above groups. Finding them as fast as possible can help to manage and investigate potential sources of infection.

Let’s see an example:

Tom is the 30th confirmed patient in Beijing. He had a business trip in Wuhan. Before he was diagnosed, he took a flight from Wuhan to Tianjin, and then returned to Beijing from Tianjin. The next day he hailed an online car to go to a shopping mall in Beijing, and then took an elevator to watch a movie. After watching a movie, he walked to a restaurant for dinner, then went to his friends for coffee, then to the supermarket to buy groceries, and finally took a taxi home.

A lot data can be collected and analysed:

  • The specific flights, trains, taxis, carriages and seats he used.
  • The time of using online car-hailing, shopping, e-payment and eating.
  • The locations of his home, shopping mall, café and supermarket.

This data can be submitted for analysis and authorities can send notices to anybody who may have been exposed to the coronavirus, or the public can check to see if their paths crossed and take quarantine action if needed.

Compared with the SARS epidemic prevention and control 17 years ago, the rapid development of the Internet and big data has made a huge contribution to the screening, tracking, control and isolation of infectious sources during this epidemic.

An upgraded version of the Baidu Migration Map platform has been launched. As of now, more than 300 cities have been opened to query, including source, destination, migration scale index, and migration scale trend maps, which directly shows population migration in various places.

Privacy and human right concern

This does bring up a big problem.

Technology can save lives, but these implementations can also threaten individual rights.

In the Coronavirus case, the question is to what extent they can use these data? The current answer is under the premise of de-identifying or anonymising the personal data ,modelling and analysis can be performed.

However, the authorities should make it clear what information they collect, how that data is safeguarded, whether or when any of it is destroyed or deleted, who has access to it and under what conditions, and how it is used.

Arlene Zhang works at the Data Law Research Center in Shangha, China

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