The potential of Data Collaboratives for COVID19


Blog post by Stefaan Verhulst: “We live in almost unimaginable times. The spread of COVID-19 is a human tragedy and global crisis that will impact our communities for many years to come. The social and economic costs are huge and mounting, and they are already contributing to a global slowdown. Every day, the emerging pandemic reveals new vulnerabilities in various aspects of our economic, political and social lives. These include our vastly overstretched public health services, our dysfunctional political climate, and our fragile global supply chains and financial markets.

The unfolding crisis is also making shortcomings clear in another area: the way we re-use data responsibly. Although this aspect of the crisis has been less remarked upon than other, more obvious failures, those who work with data—and who have seen its potential to impact the public good—understand that we have failed to create the necessary governance and institutional structures that would allow us to harness data responsibly to halt or at least limit this pandemic. A recent article in Stat, an online journal dedicated to health news, characterized the COVID-19 outbreak as “a once-in-a-century evidence fiasco.” The article continues: 

“At a time when everyone needs better information, […] we lack reliable evidence on how many people have been infected with SARS-CoV-2 or who continue to become infected. Better information is needed to guide decisions and actions of monumental significance and to monitor their impact.” 

It doesn’t have to be this way, and these data challenges are not an excuse for inaction. As we explain in what follows, there is ample evidence that the re-use of data can help mitigate health pandemics. A robust (if somewhat unsystematized) body of knowledge could direct policymakers and others in their efforts. In the second part of this article, we outline eight steps that key stakeholders can and should take to better re-use data in the fight against COVID-19. In particular, we argue that more responsible data stewardship and increased use of data collaboratives are critical….(More)”. 

Mobile phone data and COVID-19: Missing an opportunity?


Paper by Nuria Oliver, et al: “This paper describes how mobile phone data can guide government and public health authorities in determining the best course of action to control the COVID-19 pandemic and in assessing the effectiveness of control measures such as physical distancing. It identifies key gaps and reasons why this kind of data is only scarcely used, although their value in similar epidemics has proven in a number of use cases. It presents ways to overcome these gaps and key recommendations for urgent action, most notably the establishment of mixed expert groups on national and regional level, and the inclusion and support of governments and public authorities early on. It is authored by a group of experienced data scientists, epidemiologists, demographers and representatives of mobile network operators who jointly put their work at the service of the global effort to combat the COVID-19 pandemic….(More)”.

Data Protection under SARS-CoV-2


GDPR Hub: “The sudden outbreak of cases of COVID-19-afflictions (“Corona-Virus”), which was declared a pandemic by the WHO affects data protection in various ways. Different data protection authorities published guidelines for employers and other parties involved in the processing of data related to the Corona-Virus (read more below).

The Corona-Virus has also given cause to the use of different technologies based on data collection and other data processing activities by the EU/EEA member states and private companies. These processing activities mostly focus on preventing and slowing the further spreading of the Corona-Virus and on monitoring the citizens’ abidance with governmental measures such as quarantine. Some of them are based on anonymous or anonymized data (like for statistics or movement patterns), but some proposals also revolved around personalized tracking.

At the moment, it is not easy to figure out, which processing activities are actually supposed to be conducted and which are only rumors. This page will therefore be adapted once certain processing activities have been confirmed. For now, this article does not assess the lawfulness of particular processing activities, but rather outlines the general conditions for data processing in connection with the Corona-Virus.

It must be noted that several activities – such as monitoring, if citizens comply with quarantine and stay indoors by watching at mobile phone locations – can be done without having to use personal data under Article 4(1) GDPR, if all necessary information can be derived from anonymised data. The GDPR does not apply to activities that only rely on anonymised data….(More)”.

Deliberative Mini-Publics as a Response to Populist Democratic Backsliding


Chapter by Oran Doyle and Rachael Walsh: “Populisms come in different forms, but all involve a political rhetoric that invokes the will of a unitary people to combat perceived constraints, whether economic, legal, or technocratic. In this chapter, our focus is democratic backsliding aided by populist rhetoric. Some have suggested deliberative democracy as a means to combat this form of populism. Deliberative democracy encourages and facilitates both consultation and contestation, emphasizing plurality of voices, the legitimacy of disagreement, and the imperative of reasoned persuasion. Its participatory and inclusive character has the potential to undermine the credibility of populists’ claims to speak for a unitary people. Ireland has been widely referenced in constitutionalism’s deliberative turn, given its recent integration of deliberative mini-publics into the constitutional amendment process.

Reviewing the Irish experience, we suggest that deliberative mini-publics are unlikely to reverse democratic backsliding. Populist rhetoric is fueled by the very measures intended to combat democratic backsliding: enhanced constitutional constraints merely illustrate how the will of the people is being thwarted. The virtues of Ireland’s experiment in deliberative democracy — citizen participation, integration with representative democracy, deliberation, balanced information, expertise — have all been criticized in ways that are at least consistent with populist narratives. The failure of such narratives to take hold in Ireland, we suggest, may be due to a political system that is already resistant to populist rhetoric, as well as a tradition of participatory constitutionalism. The experiment with deliberative mini-publics may have strengthened Ireland’s constitutional culture by reinforcing anti-populist features. But it cannot be assumed that this experience would be replicated in larger countries polarized along political, ethnic, or religious lines….(More)”.

Why isn’t the government publishing more data about coronavirus deaths?


Article by Jeni Tennison: “Studying the past is futile in an unprecedented crisis. Science is the answer – and open-source information is paramount…Data is a necessary ingredient in day-to-day decision-making – but in this rapidly evolving situation, it’s especially vital. Everything has changed, almost overnight. Demands for foodtransport, and energy have been overhauled as more people stop travelling and work from home. Jobs have been lost in some sectors, and workers are desperately needed in others. Historic experience can no longer tell us how our society or economy is working. Past models hold little predictive power in an unprecedented situation. To know what is happening right now, we need up-to-date information….

This data is also crucial for scientists, who can use it to replicate and build upon each other’s work. Yet no open data has been published alongside the evidence for the UK government’s coronavirus response. While a model that informed the US government’s response is freely available as a Google spreadsheet, the Imperial College London model that prompted the current lockdown has still not been published as open-source code. Making data open – publishing it on the web, in spreadsheets, without restrictions on access – is the best way to ensure it can be used by the people who need it most.

There is currently no open data available on UK hospitalisation rates; no regional, age or gender breakdown of daily deaths. The more granular breakdown of registered deaths provided by the Office of National Statistics is only published on a weekly basis, and with a delay. It is hard to tell whether this data does not exist or the NHS has prioritised creating dashboards for government decision makers rather than informing the rest of the country. But the UK is making progress with regard to data: potential Covid-19 cases identified through online and call-centre triage are now being published daily by NHS Digital.

Of course, not all data should be open. Singapore has been publishing detailed data about every infected person, including their age, gender, workplace, where they have visited and whether they had contact with other infected people. This can both harm the people who are documented and incentivise others to lie to authorities, undermining the quality of data.

When people are concerned about how data about them is handled, they demand transparency. To retain our trust, governments need to be open about how data is collected and used, how it’s being shared, with whom, and for what purpose. Openness about the use of personal data to help tackle the Covid-19 crisis will become more pressing as governments seek to develop contact tracing apps and immunity passports….(More)”.

Collective Intelligence at EU Level – Social and Democratic Dimensions


Paper by Nora Milotay and Gianluca Sgueo: “Humans are among the many living species capable of collaborative and imaginative thinking. While it is widely agreed among scholars that this capacity has contributed to making humans the dominant species, other crucial questions remain open to debate. Is it possible to encourage large groups of people to engage in collective thinking? Is it possible to coordinate citizens to find solutions to address global challenges? Some scholars claim that large groups of independent, motivated, and well-informed people can, collectively, make better decisions than isolated individuals can – what is known as ‘collective intelligence.’

The social dimension of collective intelligence mainly relates to social aspects of the economy and of innovation. It shows that a holistic approach to innovation – one that includes not only technological but also social aspects – can greatly contribute to the EU’s goal of promoting a just transition for everyone to a sustainable and green economy in the digital age. The EU has been taking concrete action to promote social innovation by supporting the development of its theory and practice. Mainly through funding programmes, it helps to seek new types of partners and build new capacity – and thus shape the future of local and national innovations aimed at societal needs.

The democratic dimension suggests that the power of the collective can be leveraged so as to improve public decision-making systems. Supported by technology, policy-makers can harness the ‘civic surplus’ of citizens – thus providing smarter solutions to regulatory challenges. This is particularly relevant at EU level in view of the planned Conference on the Future of Europe, aimed at engaging communities at large and making EU decision-making more inclusive and participatory.

The current coronavirus crisis is likely to change society and our economy in ways as yet too early to predict, but recovery after the crisis will require new ways of thinking and acting to overcome common challenges, and thus making use of our collective intelligence should be more urgent than ever. In the longer term, in order to mobilise collective intelligence across the EU and to fully exploit its innovative potential, the EU needs to strengthen its education policies and promote a shared understanding of a holistic approach to innovation and of collective intelligence – and thus become a ‘global brain,’ with a solid institutional set-up at the centre of a subsidised experimentation process that meets the challenges imposed by modernday transformations…(More)”.

Urgently Needed for Policy Guidance: An Operational Tool for Monitoring the COVID-19 Pandemic


Paper by Stephane Luchini et al:” The radical uncertainty around the current COVID19 pandemics requires that governments around the world should be able to track in real time not only how the virus spreads but, most importantly, what policies are effective in keeping the spread of the disease under check. To improve the quality of health decision-making, we argue that it is necessary to monitor and compare acceleration/deceleration of confirmed cases over health policy responses, across countries. To do so, we provide a simple mathematical tool to estimate the convexity/concavity of trends in epidemiological surveillance data. Had it been applied at the onset of the crisis, it would have offered more opportunities to measure the impact of the policies undertaken in different Asian countries, and to allow European and North-American governments to draw quicker lessons from these Asian experiences when making policy decisions. Our tool can be especially useful as the epidemic is currently extending to lower-income African and South American countries, some of which have weaker health systems….(More)”.

Privacy Protection Key for Using Patient Data to Develop AI Tools


Article by  Jessica Kent: “Clinical data should be treated as a public good when used for research or artificial intelligence algorithm development, so long as patients’ privacy is protected, according to a report from the Radiological Society of North America (RSNA).

As artificial intelligence and machine learning are increasingly applied to medical imaging, bringing the potential for streamlined analysis and faster diagnoses, the industry still lacks a broad consensus on an ethical framework for sharing this data.

“Now that we have electronic access to clinical data and the data processing tools, we can dramatically accelerate our ability to gain understanding and develop new applications that can benefit patients and populations,” said study lead author David B. Larson, MD, MBA, from the Stanford University School of Medicine. “But unsettled questions regarding the ethical use of the data often preclude the sharing of that information.”

To offer solutions around data sharing for AI development, RSNA developed a framework that highlights how to ethically use patient data for secondary purposes.

“Medical data, which are simply recorded observations, are acquired for the purposes of providing patient care,” Larson said….(More)”

Unpredictable Residency during the COVID-19 Pandemic Spells Trouble for the 2020 Census Count


Blog by Diana Elliott and Robert Santos: “Social distancing measures to curtail the community spread of COVID-19 have upended daily life. Just before lockdowns were implemented across the country, there was tremendous movement and migration of people relocating to different residences to shelter in place. This makes sense for the people involved but could be disastrous for the communities they fled and the final 2020 Census counts.

Pandemic-based migration undermines an accurate count

The 2020 Census, like most data collected by the US Census Bureau, is residence based. In the years leading up to 2020, the US Census Bureau worked diligently on the quality of the Master Address File, or the catalog of all residential addresses in the country. Staff account for newly built housing developments and buildings, apartment units or accessory dwelling units that are used as permanent residences, and the demolition of homes and apartments in the past decade. Census materials are sent to an address, rather than a person.

Most residences across America have already received their 2020 Census invitation. Whether completed online, by paper, by phone, or in person, the first official question on the 2020 Census questionnaire is “How many people were living or staying in this house, apartment, or mobile home on April 1, 2020?” Households are expected to answer this based on the concept of “usual residence,” or the place where a person lives and sleeps most of the time.

Despite written guidance provided on the 2020 Census on how to answer this question, doing so may be wrought with complexities and nuance from the pandemic.

First, research reveals that respondents do not often read questionnaire instructions; they dive in and start answering. With many people scrambling to other counties, cities, and states to hunker down for the long haul with loved ones, this will lead to incorrect counts when people are counted at temporary addresses.

Second, for many, the concept of “usual residence” has little relevance in the uncertainty unfolding during the COVID-19 pandemic. What if your temporary address becomes your permanent address? What does “usual residence” mean during a global epidemic that could stretch for 18 months or more? And perhaps more importantly, what should it mean?

Finally, there is the added complication of census operational delays (PDF). Self-response to the 2020 Census has been extended into August, as have the nonresponse follow-up efforts, when enumerators knock on the doors of those who haven’t yet answered the census. Additional delays seem unavoidable. The longer the delay, the more time there is for people who have not yet completed a census form to realize their temporary plan has evolved into a state of permanence….(More)”.

Researchers Develop Faster Way to Replace Bad Data With Accurate Information


NCSU Press Release: “Researchers from North Carolina State University and the Army Research Office have demonstrated a new model of how competing pieces of information spread in online social networks and the Internet of Things (IoT). The findings could be used to disseminate accurate information more quickly, displacing false information about anything from computer security to public health….

In their paper, the researchers show that a network’s size plays a significant role in how quickly “good” information can displace “bad” information. However, a large network is not necessarily better or worse than a small one. Instead, the speed at which good data travels is primarily affected by the network’s structure.

A highly interconnected network can disseminate new data very quickly. And the larger the network, the faster the new data will travel.

However, in networks that are connected primarily by a limited number of key nodes, those nodes serve as bottlenecks. As a result, the larger this type of network is, the slower the new data will travel.

The researchers also identified an algorithm that can be used to assess which point in a network would allow you to spread new data throughout the network most quickly.

“Practically speaking, this could be used to ensure that an IoT network purges old data as quickly as possible and is operating with new, accurate data,” Wenye Wang says.

“But these findings are also applicable to online social networks, and could be used to facilitate the spread of accurate information regarding subjects that affect the public,” says Jie Wang. “For example, we think it could be used to combat misinformation online.”…(More)”

Full paper: “Modeling and Analysis of Conflicting Information Propagation in a Finite Time Horizon,”