The world is suffering from the COVID-19 pandemic with over a million infected cases and more than 300 thousand casualties as of mid-May 2020. Healthcare systems across the world are under pressure, governments are limiting free movement of populations to control virus propagation and economies are suffering with major social consequences for the near future.

In addition to an infection fatality rate of 1.4%, one of the main problems of COVID-19 is its (estimated) infection factor (R₀@2.5), which means that each infected person on average infects 2.5 other persons with exponential spread as a consequence. Another dangerous aspect of COVID-19 is that it is easy transmissible through respiratory droplets, by direct contact with infected persons, or by contact with contaminated objects and surfaces. All of this makes understanding people mobility and social distancing measures of utmost importance to win the battle against the virus.

Previous experience has shown that mobility insights and decision-support tools generated from anonymized and aggregated telco data can help to fight pandemics, as has been demonstrated for Ebola in Africa (Orange), Zika in Brazil (Telefónica), and Swine flu in Mexico (Telefónica) to name just a few. Despite those previous experiences, governments across the world were not prepared -from a big data perspective- to deal with COVID-19. However, through a steep learning curve, many governments across the world have now reached out to telecoms and are consuming mobility insights to help them manage the crisis as well as the recovery process of economic activities.

We are editing a special collection of articles in Data & Policy, a peer-reviewed open access journal published by Cambridge University Press, in order to bring together a significant amount of concrete experiences of telco-government collaborations across the globe, with the aim to learn from the collective COVID-19 experience and to deeply understand how telco mobile big data analytics can help prepare the world for future pandemics.

We therefore invite telecommunications companies, their partners, governments, policymakers and research institutions to submit papers describing their concrete experiences with governmental or institutional use of big data analytics and decision-support tools from mobile operators in the fight against COVID-19. We encourage authors to submit papers describing the following aspects of the experience:

Setting the scene, for example:

• How did the collaboration start?
• Were the initial requirements or use cases that the data would be used for?
• Was it a philanthropic or business collaboration? Did it evolve?
• Was it a complex (internal) process to frame the collaboration for the telco? For the government?

Approach, for example:

• Did the telco had previous experience in applying mobile big data analytics leveraging anonymized and aggregated data with third parties?
• What were the frequency and latency of the resulting insights being shared?
• What was the delivery mechanism and end-product? Reports, dashboards, insights, answers to specific questions?
• How was the collaboration on a daily basis?
• Were results transparently shared between the stakeholders involved?

• What use cases were finally implemented?
• What decisions have been taken based on the insights?
• How long is/was the collaboration?
• Was the collaboration externally communicated? How was it received?

Lessons learned, for example:

• What were the main challenges (of any nature, technical, cultural, economic, reputational, legal,...)?
• Was privacy or reputation an important obstacle?
• What went well? What could be improved for the future?
• What are the main learnings for the future?
• What needs to happen to strengthen preparedness for future pandemics?

For this special collection, we specifically value the description of the full data value chain from its origin via its processing and analytics, to creating the insights, product or services, and finally to its use for evidence-based policymaking to fight COVID-19. We are not looking for research papers demonstrating the value of mobile big data for pandemics, nor for possible applications of mobile big data for COVID-19. The objective is to learn from real-world best and “worst” practices, and share a collection of experience papers that set the baseline for future pandemics.

Submission Guidelines

Manuscripts should conform to the Data & Policy Instructions for Authors (LaTeX and Word templates are available). Note the following:

We expect most contributions to be in the form of case studies, which Data & Policywelcomes whether they are positive or negative examples of the use of data for policy. The journal doesn’t have a separate case studies category, but these contributions could submitted as Research Articles (up to 8,000 words) if they involve rigorous analysis and new findings or Commentaries (approx. 4,000 words) if they are more an overview. For a full list and description of article types see the Instructions for Authors.

• Submissions should be accompanied by a Policy Significance Statement (120 words summarising the significance of the findings in accessible language for a policy audience).
• A Data Availability Statement is also required, explaining whether data, code and other materials supporting the findings are available, and if so, where readers may access them. In case they are not openly available, also specify that.

Please, check these guidelines carefully before submitting and contact dataandpolicy@cambridge.org with any queries about formatting. Submissions not complying with them will be administratively rejected without review.

All manuscripts to be considered for publication must be submitted by the deadline through Manuscript Central, selecting ‘Telco Big Data for Covid-19’ from the special issue dropdown menu.

This call for papers is accompanied with a corresponding Call for Reviewers, were we invite practitioners, researchers and other relevant experts in the field to review the papers submitted to this special issue. In the interest of transparency, the reviews will not be anonymous and will be published along with the accepted papers with a unique DOI, thereby becoming citable objects in themselves.

Important Dates

Manuscript Submission Deadline: Friday 29 October

Decision Notification: Friday 15 January

Final Manuscript Due: Friday 12 March

Publication Date: May 2021.

Guest Editors

Richard Benjamins: Telefónica, Spain; OdiseIA - Observatory for Social and Ethical Impact of AI, Spain.

Jeanine Vos: GSMA, United Kingdom.

Editor-in-Chief

Stefaan Verhulst: The GovLab, NY University, USA.