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Data sharing and collaborations with Telco data during the COVID-19 pandemic: A Vodafone case study.

ABSTRACT: With the outbreak of COVID-19 across Europe, anonymized telecommunications data provides a key insight into population level mobility and assessing the impact and effectiveness of containment measures. Vodafone's response across its global footprint was fast and delivered key new metrics for the pandemic that have proven to be useful for a number of external entities. Cooperation with national governments and supra-national entities to help fight the COVID-19 pandemic was a key part of Vodafone's response, and in this article the different methodologies developed are analyzed, as well as the key collaborations established in this context. In this article we also analyze the regulatory challenges found, and how these can pose a risk of the full benefits of these insights not being harnessed, despite clear and efficient Privacy and Ethics assessments to ensure individual safety and data privacy.

SUBMITTER: Lourenco PR

PROVIDER: S-EPMC8649407 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe SARS-CoV-2 (COVID-19) pandemic has catalysed a widespread humanitarian crisis in many low- and middle-income countries around the world, with many African nations significantly impacted. The aim of this study was to quantify the impact of the COVID-19 pandemic on the planning and provision of international reconstructive collaborations in Africa.MethodsAn anonymous, 14-question, multiple choice questionnaire was sent to 27 non-governmental organisations who regularly perform reconstructive surgery in Africa. The survey was open to responses for four weeks, closing on the 7th of March 2021. A single reminder was sent out at 2 weeks. The survey covered four key domains: (1) NGO demographics; (2) the impact of COVID-19 on patient follow-up; (3) barriers to the safe provision of international surgical collaborations during COVID-19; (4) the impact of COVID-19 on NGO funding.ResultsA total of ten reconstructive NGOs completed the survey (response rate, 37%). Ethiopia (n = 5) and Tanzania (n = 4) were the countries where most collaborations took place. Plastic, reconstructive and burns surgery was the most common sub-speciality (n = 7). For NGOs that did not have a year-round presence in country (n = 8), only one NGO was able to perform reconstructive surgery in Africa during the pandemic. The most common barrier identified was travel restrictions (within country, n = 8 or country entry-exit, n = 7). Pre-pandemic, 1547 to ≥ 1800 patients received reconstructive surgery on international surgical collaborations. After the outbreak, 70% of NGOs surveyed had treated no patients, with approximately 1405 to ≥ 1640 patients left untreated over the last year.ConclusionsThe COVID-19 pandemic has placed huge pressures on health services and their delivery across the globe. This theme has extended into international surgical collaborations leading to increased unmet surgical needs in low- and middle-income countries.Level of evidence: Not gradable.Supplementary informationThe online version contains supplementary material available at 10.1007/s00238-021-01892-4.

Project description:BackgroundA considerable amount of various types of data have been collected during the COVID-19 pandemic, the analysis and understanding of which have been indispensable for curbing the spread of the disease. As the pandemic moves to an endemic state, the data collected during the pandemic will continue to be rich sources for further studying and understanding the impacts of the pandemic on various aspects of our society. On the other hand, naïve release and sharing of the information can be associated with serious privacy concerns.MethodsWe use three common but distinct data types collected during the pandemic (case surveillance tabular data, case location data, and contact tracing networks) to illustrate the publication and sharing of granular information and individual-level pandemic data in a privacy-preserving manner. We leverage and build upon the concept of differential privacy to generate and release privacy-preserving data for each data type. We investigate the inferential utility of privacy-preserving information through simulation studies at different levels of privacy guarantees and demonstrate the approaches in real-life data. All the approaches employed in the study are straightforward to apply.ResultsThe empirical studies in all three data cases suggest that privacy-preserving results based on the differentially privately sanitized data can be similar to the original results at a reasonably small privacy loss ([Formula: see text]). Statistical inferences based on sanitized data using the multiple synthesis technique also appear valid, with nominal coverage of 95% confidence intervals when there is no noticeable bias in point estimation. When [Formula: see text] and the sample size is not large enough, some privacy-preserving results are subject to bias, partially due to the bounding applied to sanitized data as a post-processing step to satisfy practical data constraints.ConclusionsOur study generates statistical evidence on the practical feasibility of sharing pandemic data with privacy guarantees and on how to balance the statistical utility of released information during this process.

Project description:BackgroundThe COVID-19 pandemic is still undergoing complicated developments in Vietnam and around the world. There is a lot of information about the COVID-19 pandemic, especially on the internet where people can create and share information quickly. This can lead to an infodemic, which is a challenge every government might face in the fight against pandemics.ObjectiveThis study aims to understand public attention toward the pandemic (from December 2019 to November 2020) through 7 types of sources: Facebook, Instagram, YouTube, blogs, news sites, forums, and e-commerce sites.MethodsWe collected and analyzed nearly 38 million pieces of text data from the aforementioned sources via SocialHeat, a social listening (infoveillance) platform developed by YouNet Group. We described not only public attention volume trends, discussion sentiments, top sources, top posts that gained the most public attention, and hot keyword frequency but also hot keywords' co-occurrence as visualized by the VOSviewer software tool.ResultsIn this study, we reached four main conclusions. First, based on changing discussion trends regarding the COVID-19 subject, 7 periods were identified based on events that can be aggregated into two pandemic waves in Vietnam. Second, community pages on Facebook were the source of the most engagement from the public. However, the sources with the highest average interaction efficiency per article were government sources. Third, people's attitudes when discussing the pandemic have changed from negative to positive emotions. Fourth, the type of content that attracts the most interactions from people varies from time to time. Besides that, the issue-attention cycle theory occurred not only once but four times during the COVID-19 pandemic in Vietnam.ConclusionsOur study shows that online resources can help the government quickly identify public attention to public health messages during times of crisis. We also determined the hot spots that most interested the public and public attention communication patterns, which can help the government get practical information to make more effective policy reactions to help prevent the spread of the pandemic.

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Data sharing and collaborations with Telco data during the COVID-19 pandemic: A Vodafone case study.

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