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The value of network data confirmed by the Covid-19 epidemic and its expanded usages

Published online by Cambridge University Press:  19 January 2022

Pascal Chambreuil*
Affiliation:
Orange Group, Orange Business Services Paris, France
Ju Y. Jeon
Affiliation:
Orange Group, Orange Business Services Paris, France
Thierry Barba
Affiliation:
Orange Group, Orange Business Services Paris, France
*
*Corresponding author. E-mail: pascal.chambreuil@orange.com

Abstract

Data driven analysis is proven to create a competitive advantage to business. Governments and nonprofit organizations also turn to Big Data to harness its benefits and use it for social good. Among different types of data sources, location data collected from mobile networks is especially valuable for its representativeness, real-time observation, and versatility. There is a distinction between mobile positioning data (MPD) generated by the exchanges between mobile devices and the core network; versus over-the-top or system-level location data collecting individual GPS location. MPD is composed of all mobile network events regardless of the mobile phone brand, operating system, app usage, frequency bands or mobile generation; it is uniform and ubiquitous. Getting the best out of MPD relies on the knowledge of how to create an advanced algorithm for homogeneously processing this massive, complex data into insightful indicators. Anonymized and aggregated MPD enables the testing of multiple combinations with other data sources, fully abiding by GDPR, to arrive at innovative solutions. These unique insights can help tackle societal challenges (the state of mobile data for social good June 2017 GSMA, UN Global pulse). It can help to establish accurate statistics about population movements, density, location, social patterns, finances, and ambient environmental conditions. This article demonstrates how MPD has been used to help combat Covid-19 in Europe, the Middle East, and Africa. Furthermore, depending on the future direction, MPD and data analysis can serve powering economic development as well as working toward the Sustainable Development Goals, whilst respecting data privacy.

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Translational Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press
Figure 0

Figure 1. Movement evolution in France. Data from weekly movements in microzones (1,400 zones), grouping municipalities of France metropolitan over the whole of France and with a mobility time >1 hr. In late February, the number of journeys was reduced by more than two thirds and remained lower through to the beginning of October. Copyright: Orange. This figure has been reproduced with the permission of the copyright holder, and is not included in the Creative Commons license applied to this article.

Figure 1

Figure 2. Observations of daily movements in and out of the Gombe region, Democratic Republic of Congo. The reference period (shown in gray) is from February to March 2020. The event period, when the pandemic struck (shown in blue) is from mid-March to July 2020. Orange Flux Vision continued to provide insights through to early October 2020, when levels of movements were still slightly below the reference period. Copyright: Orange. This figure has been reproduced with the permission of the copyright holder, and is not included in the Creative Common license applied to this article.

Figure 2

Figure 3. Observations of distances traveled in Gombe, Democratic Republic of Congo, over reference period from February to March 2020 and event period mid-March to July 2020. The numbers of journeys of all distances are drastically reduced. Copyright: Orange. This figure has been reproduced with the permission of the copyright holder, and is not included in the Creative Common license applied to this article.

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Author comment: The value of network data confirmed by the Covid-19 epidemic and its expanded usages — R0/PR1

Comments

No requirement to enter a cover letter, given that this is an invited paper. But please feel free to add anything if you wish to address the editors specifically.

Review: The value of network data confirmed by the Covid-19 epidemic and its expanded usages — R0/PR2

Conflict of interest statement

No Conflicts of Interest.

Comments

Comments to Author: This article aims to demonstrate how Mobile Big Data is being used to help

combat COVID-19 in various countries.

However it lacks general overview of existing methods and various publications on this topic (literature is lacking, which

is crucial for peer-reviewed article and essential for any good article).

Moreover article contains numerous orthographic mistakes, which should be corrected (for example, in the abstract, first line, section 2, third paragraph, etc.). Some sentences are not connected to other paragraphs,

such as in section 4 and should be more integrated in the flow.

In Fig.1 where the movements are shown it is necessary to

- put links to data sources

- explain which mobility index is exactly shown on the figure (from which origin, since mobility data is

too general category).

The same is related to Figs.2. It would require more information about the type of mobility (or explain what "total

mobility" is).

Review: The value of network data confirmed by the Covid-19 epidemic and its expanded usages — R0/PR3

Conflict of interest statement

No Conflicts of Interest.

Comments

Comments to Author: The paper covers its main objective, which is to show the value enclosed in Network Event Data gathered by Mobile Network Operators, and the opportunities associated with these data sharing with governments to enable an enhanced decision-taking process for multiple purposes, from mobility analysis to support new infrastructures design, to crisis management, as it was the case of COVID-19 lockdowns monitoring and effectiveness.

In my humble opinion the paper will be suitable for its publication once its authors develop some clarifications, such as the following aspects.

Minor grammatical and spelling revision should be carried out. Some examples: “For many years, Orange have been providing anonymous population movement analyses” should be “For many years, Orange has been providing anonymous population movement analyses”, or “the availability of local technical & IT resources might be a challenge to take the fill advantage of Flux Vision in the short term”, I understand that should be “the availability of local technical & IT resources might be a challenge to take the full advantage of Flux Vision in the short term”. I guess some words are missing in this sentence: “The Spanish economy ministry asked for Orange’s help, which provided data its with national institute for statistics.”

Further detail could be provided about the statistical adjustment tools used to extrapolate the observations recorded by Orange network, regarding the regional variation on this company market share throughout the territory.

Further explanations about some government’s reluctance to use telecommunications data could be provided. Privacy issues are mentioned, but, were the only reasons? Have additional barriers, such as perhaps lack of confidence in the statistical representativeness of the data, been identified?

It is mentioned that in Spain and Belgium, national task forces combined Orange’s inputs with other operators’ inputs to construct a global national observation tour. Did this aim drive to the implementation of some data aggregation standards in order to enable the combination of data from different providers? what kind of adaptations had to be made?

A great demonstration of the initial hypothesis, that this datasource is useful to enhance public management in a context of crisis and urgent need for data, could be sustained by examples of specific public management decisions that were improved thanks to this high resolution vision on mobility flows.

Recommendation: The value of network data confirmed by the Covid-19 epidemic and its expanded usages — R0/PR4

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Decision: The value of network data confirmed by the Covid-19 epidemic and its expanded usages — R0/PR5

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