A Data Ecosystem to Defeat COVID-19

Curated on Posted on by Stefaan Verhulst

Paper by Bapon Fakhruddin: “…A wide range of approaches could be applied to understand transmission, outbreak assessment, risk communication, cascading impacts assessment on essential and other services. The network-based modelling of System of Systems (SOS), mobile technology, frequentist statistics and maximum-likelihood estimation, interactive data visualization, geostatistics, graph theory, Bayesian statistics, mathematical modelling, evidence synthesis approaches and complex thinking frameworks for systems interactions on COVID-19 impacts could be utilized. An example of tools and technologies that could be utilized to act decisively and early to prevent the further spread or quickly suppress the transmission of COVID-19, strengthen the resilience of health systems and save lives and urgent support to developing countries with businesses and corporations are shown in Figure 2. There are also WHO guidance on ‘Health Emergency and Disaster Risk Management[8]’, UNDRR supported ‘Public Health Scorecard Addendum[9]’, and other guidelines (e.g. WHO practical considerations and recommendations for religious leaders and faith-based communities in the context of COVID-19[10]) that could enhance pandemic response plan. It needs to be ensured that any such use is proportionate, specific and protected and does not increase civil liberties’ risk. It is essential therefore to examine in detail the challenge of maximising data use in emergency situations, while ensuring it is task-limited, proportionate and respectful of necessary protections and limitations. This is a complex task and the COVID-19 wil provide us with important test cases. It is also important that data is interpreted accurately. Otherwise, misinterpretations could lead each sector down to incorrect paths.

Figure 2: Tools to strengthen resilience for COVID-19

Many countries are still learning how to make use of data for their decision making in this critical time. The COVID-19 pandemic will provide important lessons on the need for cross-domain research and on how, in such emergencies, to balance the use of technological opportunities and data to counter pandemics against fundamental protections….(More)”.

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment

Curated on Posted on by Stefaan Verhulst

Paper by Mirco Nanni: “The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens’ privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking.

We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens’ “personal data stores”, to be shared separately and selectively, voluntarily, only when the citizen has tested positive for COVID-19, and with a privacy preserving level of granularity.

This approach better protects the personal sphere of citizens and affords multiple benefits: it allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allow the user to share spatio-temporal aggregates – if and when they want, for specific aims – with health authorities, for instance. Second, we favour a longer-term pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society….(More)”

The Meaning of Masks

Curated on Posted on by Stefaan Verhulst

Paper by Cass Sunstein: “Many incentives are monetary, and when private or public institutions seek to change behavior, it is natural to change monetary incentives. But many other incentives are a product of social meanings, about which people may not much deliberate, but which can operate as subsidies or as taxes. In some times and places, for example the social meaning of smoking has been positive, increasing the incentive to smoke; in other times and places, it has been negative, and thus served to reduce smoking.

With respect to safety and health, social meanings change radically over time, and they can be dramatically different in one place from what they are in another. Often people live in accordance with meanings that they deplore, or at least wish were otherwise. But it is exceptionally difficult for individuals to alter meanings on their own. Alteration of meanings can come from law, which may, through a mandate, transform the meaning of action into a bland, “I comply with law,” or into a less bland, “I am a good citizen.” Alteration of social meanings can also come from large-scale private action, engineered or promoted by “meaning entrepreneurs,” who can turn the meaning of action from, “I am an oddball,” to, “I do my civic duty,” or, “I protect others from harm.” Sometimes subgroups rebel against new or altered meanings, produced by law or meaning entrepreneurs, but often those meanings stick and produce significant change….(More)”.

Federalism and Polycentric Government in a Pandemic

Curated on Posted on by Stefaan Verhulst

Paper by Victoria Perez and Justin M. Ross: “Networks of overlapping local governments are the front line of governmental responses to pandemics. Local governments, both general purpose (municipalities, counties, etc.) and special districts (school, fire, police, hospital, etc.), implement state and federal directives while acting as a producer and as a third-party payer in the healthcare system. They possess local information necessary in determining the best use of finite resources and available assets. Furthermore, a liberal society requires voluntary cooperation of citizens skeptical of opportunistic authoritarianism. Therefore, successful local governance instills a reassuring division of political power.

The COVID-19 pandemic has created two significant challenges for local governments in their efforts to respond effectively to the crisis: public finance and intergovernmental collaboration. This brief recommends practical solutions to meet these challenges….(More)”.

How Facebook and Google are helping the CDC forecast coronavirus

Curated on Posted on by Stefaan Verhulst

Karen Hao at MIT Technology Review: “When it comes to predicting the spread of an infectious disease, it’s crucial to understand what Ryan Tibshirani, an associate professor at Carnegie Mellon University, calls the “the pyramid of severity.” The bottom of the pyramid is asymptomatic carriers (those who have the infection but feel fine); the next level is symptomatic carriers (those who are feeling ill); then come hospitalizations, critical hospitalizations, and finally deaths.

Every level of the pyramid has a clear relationship to the next: “For example, sadly, it’s pretty predictable how many people will die once you know how many people are under critical care,” says Tibshirani, who is part of CMU’s Delphi research group, one of the best flu-forecasting teams in the US. The goal, therefore, is to have a clear measure of the lower levels of the pyramid, as the foundation for forecasting the higher ones.

But in the US, building such a model is a Herculean task. A lack of testing makes it impossible to assess the number of asymptomatic carriers. The results also don’t accurately reflect how many symptomatic carriers there are. Different counties have different testing requirements—some choosing only to test patients who require hospitalization. Test results also often take upwards of a week to return.

The remaining option is to measure symptomatic carriers through a large-scale, self-reported survey. But such an initiative won’t work unless it covers a big enough cross section of the entire population. Now the Delphi group, which has been working with the Centers for Disease Control and Prevention to help it coordinate the national pandemic response, has turned to the largest platforms in the US: Facebook and Google.

Facebook will help CMU Delphi research group gather data about Covid symptoms

In a new partnership with Delphi, both tech giants have agreed to help gather data from those who voluntarily choose to report whether they’re experiencing covid-like symptoms. Facebook will target a fraction of their US users with a CMU-run survey, while Google has thus far been using its Opinion Rewards app, which lets users respond to questions for app store credit. The hope is this new information will allow the lab to produce county-by-county projections that will help policymakers allocate resources more effectively.

Neither company will ever actually see the survey results; they’re merely pointing users to the questions administered and processed by the lab. The lab will also never share any of the raw data back to either company. Still, the agreements represent a major deviation from typical data-sharing practices, which could raise privacy concerns. “If this wasn’t a pandemic, I don’t know that companies would want to take the risk of being associated with or asking directly for such a personal piece of information as health,” Tibshirani says.

Without such cooperation, the researchers would’ve been hard pressed to find the data anywhere else. Several other apps allow users to self-report symptoms, including a popular one in the UK known as the Covid Symptom Tracker that has been downloaded over 1.5 million times. But none of them offer the same systematic and expansive coverage as a Facebook or Google-administered survey, says Tibshirani. He hopes the project will collect millions of responses each week….(More)”.

Tracking coronavirus: big data and the challenge to privacy

Curated on Posted on by Stefaan Verhulst

Nic Fildes and Javier Espinoza at the Financial Times: “When the World Health Organization launched a 2007 initiative to eliminate malaria on Zanzibar, it turned to an unusual source to track the spread of the disease between the island and mainland Africa: mobile phones sold by Tanzania’s telecoms groups including Vodafone, the UK mobile operator.

Working together with researchers at Southampton university, Vodafone began compiling sets of location data from mobile phones in the areas where cases of the disease had been recorded. 

Mapping how populations move between locations has proved invaluable in tracking and responding to epidemics. The Zanzibar project has been replicated by academics across the continent to monitor other deadly diseases, including Ebola in west Africa….

With much of Europe at a standstill as a result of the coronavirus pandemic, politicians want the telecoms operators to provide similar data from smartphones. Thierry Breton, the former chief executive of France Telecom who is now the European commissioner for the internal market, has called on operators to hand over aggregated location data to track how the virus is spreading and to identify spots where help is most needed.

Both politicians and the industry insist that the data sets will be “anonymised”, meaning that customers’ individual identities will be scrubbed out. Mr Breton told the Financial Times: “In no way are we going to track individuals. That’s absolutely not the case. We are talking about fully anonymised, aggregated data to anticipate the development of the pandemic.”

But the use of such data to track the virus has triggered fears of growing surveillance, including questions about how the data might be used once the crisis is over and whether such data sets are ever truly anonymous….(More)”.

Online collective intelligence course aims to improve responses to COVID-19 and other crises

Curated on Posted on by Stefaan Verhulst

PressRelease: “Working with 11 partner institutions around the world,  The Governance Lab (The GovLab) at the New York University Tandon School of Engineering today launches a massive open online course (MOOC) on “Collective Crisis Intelligence.” The course is free, open to anyone, and designed to help institutions improve disaster response through the use of data and volunteer participation. 

Thirteen modules have been created by leading global experts in major disasters such as the post-election violence in Kenya in 2008, the Fukushima nuclear plant disaster in 2011, the Ebola crisis in 2014, the Zika outbreak in 2016, and the current coronavirus. The course is designed to help those responding to coronavirus make use of volunteerism. 

As the COVID-19 pandemic reaches unprecedented proportions and spreads to more than 150 countries on six continents, policymakers are struggling to answer questions such as “How do we predict how the virus will spread?,” “How do we help the elderly and the homebound?,” “How do we provide economic assistance to those affected by business closures?,” and more. 

In each mini-lecture, those who have learned how to mobilize groups of people online to manage in a crisis present the basic concepts and tools to learn, analyze, and implement a crowdsourced public response. Lectures include

  • Introduction: Why Collective Intelligence Matters in a Crisis
  • Defining Actionable Problems (led by Matt Andrews, Harvard Kennedy School)
  • Three Day Evidence Review (led by Peter Bragge, Monash University, Australia)
  • Priorities for Collective Intelligence (led by Geoff Mulgan, University College London) 
  • Smarter Crowdsourcing (led by Beth Simone Noveck, The GovLab)
  • Crowdfunding (led by Peter Baeck, Nesta, United Kingdom)
  • Secondary Fall Out (led by Azby Brown, Safecast, Japan)
  • Crowdsourcing Surveillance (led by Tolbert Nyenswah, Johns Hopkins Bloomberg School of Public Health, United States/Liberia)
  • Crowdsourcing Data (led by Angela Oduor Lungati and Juliana Rotich, Ushahidi, Kenya)
  • Mobilizing a Network (led by Sean Bonner, Safecast, Japan)
  • Crowdsourcing Scientific Expertise (led by Ali Nouri, Federation of American Scientists)
  • Chatbots and Social Media Strategies for Crisis (led by Nashin Mahtani, PetaBencana.id, Indonesia)
  • Conclusion: Lessons Learned

The course explores such innovative uses of crowdsourcing as Safecast’s implementation of citizen science to gather information about environmental conditions after the meltdown of the Fukushima nuclear plant; Ushahidi, an online platform in Kenya for crowdsourcing data for crisis relief, human rights advocacy, transparency, and accountability campaigns; and “Ask a Scientist,” an interactive tool developed by The GovLab with the Federation of American Scientists and the New Jersey Office of Innovation, in which a network of scientists answer citizens’ questions about COVID-19.

More information on the courses is available at https://covidcourse.thegovlab.org “

New Tool to Establish Responsible Data Collaboratives in the Time of COVID-19

Curated on Posted on by Stefaan Verhulst

Announcement: “To address the COVID-19 pandemic and other dynamic threats, The GovLab has called for the development of a new data infrastructure and ecosystem. Establishing data collaboratives in a responsible manner often necessitates the creation of data sharing agreements and other legal documentation — a strain on time and capacity both for data holders and those who could use data in the public interest.

Today, to support the development of data collaboratives in a responsible and agile way, we are sharing a new tool that addresses the complexity in preparing a Data Sharing Agreement from Contracts for Data Collaboration (a joint initiative of SDSN-TReNDS, the World Economic Forum, The GovLab, and the University of Washington’s Information Risk Research Initiative). Providing a checklist to support organizations with reviewing, negotiating and preparing Data Sharing Arrangements, the intent is to strengthen stakeholder trust and help accelerate responsible data sharing arrangements given the urgency of the global pandemic.

(Please note that the check list is a tool for formulating and understanding legal issues, but we are not offering it as legal advice.)

CLICK HERE TO DOWNLOAD THE TOOL (More)”.

Combating COVID-19 with Data: What Role for National Statistical Systems?

Curated on Posted on by Stefaan Verhulst

Press Release: “As part of its ongoing response to the COVID-19 crisis, PARIS21 released today a policy brief at the intersection of statistics and policy making to help inform the measures taken to address the pandemic.

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The COVID-19 pandemic has brought data to the centre of policy making and public attention. A diverse ecosystem of data producers, both private and public, report rates of infection, fatality and recovery on a daily basis. However, a proliferation of data, which is at times contradictory, can also lead to confusion and mistrust among data users.

Meanwhile, policymakers, development partners and citizens need to take quick, informed actions to design interventions that reach the most vulnerable and leave no one behind. As countries comply with lockdowns and other containment measures, national statistical systems (NSSs) face a dual effect of growing data demand and constrained supply. This in turn may squeeze NSSs beyond their institutional capacity.

At the same time, alternative data sources such as mobile phone or satellite data are in abundance. These data could potentially complement traditional sources such as censuses, surveys and administrative systems. However, with scant governance frameworks to scale and sustain their use, policy action is not yet based on a convergence of evidence.

This policy brief introduces a conceptual framework that describes the adverse effects of the crisis on NSSs in developing countries. Moreover, it suggests short and medium-term actions to mitigate the negative effects by:

1. Focusing data production on priority economic, social and demographic data.
2. Communicating proactively with citizens, academia, private sector and policy makers.
3. Positioning the NSO as advisor and knowledge bank for national governments.

NSSs contribute significantly to robust policy responses in a crisis. The brief thus calls on national statistical offices to assume a central role as coordinators of the NSSs and chart the way toward improved data ecosystem governance for informing policies during and after COVID-19….(More)”.

A widening data divide: COVID-19 and the Global South

Curated on Posted on by Stefaan Verhulst

Essay by stefania milan and Emiliano Treré at Data & Policy: “If numbers are the conditions of existence of the COVID-19 problem, we ought to pay attention to the actual (in)ability of many countries in the South to test their population for the virus, and to produce reliable population statistics more in general — let alone to adequately care for them. It is a matter of a “data gap” as well as of data quality, which even in “normal” times hinders the need for “evidence-based policy making, tracking progress and development, and increasing government accountability” (Chen et al., 2013). And while the World Health Organization issues warning about the “dramatic situation” concerning the spread of COVID-19 in the African continent, to name just one of the blind spots of our datasets of the global pandemic, the World Economic Forum calls for “flattening the curve” in developing countries. Progress has been made following the revision of the United Nations’ Millennium Development Goals in 2005, with countries in the Global South have been invited (and supported) to devise National Strategies for the Development of Statistics. Yet, a cursory look at the NYU GovLab’s valuable repository of data collaboratives” addressing the COVID-19 pandemic reveals the virtual absence of data collection and monitoring projects in the South of the hemisphere. The next obvious step is the dangerous equation “no data=no problem”.

Disease and “whiteness”

Epidemiology and pharmacogenetics (i.e. the study of the genetic basis of how people respond to pharmaceuticals), to name but a few amongst the number of concerned life sciences, are largely based on the “inclusion of white/Caucasians in studies and the exclusion of other ethnic groups” (Tutton, 2007). In other words, modeling of disease evolution and the related solutions are based on datasets that take into account primarily — and in fact almost exclusively — the caucasian population. This is a known problem in the field, which derives from the “assumption that a Black person could be thought of as being White”, dismissing specificities and differences. This problem has been linked to the “lack of social theory development, due mainly to the reluctance of epidemiologists to think about social mechanisms (e.g., racial exploitation)” (Muntaner, 1999, p. 121). While COVID-19 represents a slight variation on this trend, having been first identified in China, the problem on the large scale remains. And in times of a health emergency as global as this one, risks to be reinforced and perpetuated.

A succulent market for the industry

In the lack of national testing capacity, the developing world might fall prey to the blooming industry of genetic and disease testing, on the one hand, and of telecom-enabled population monitoring on the other. Private companies might be able to fill the gap left by the state, mapping populations at risk — while however monetizing their data. The case of 23andme is symptomatic of this rise of industry-led testing, which constitutes a double-edge sword. On the one hand, private actors might supply key services that resource-poor or failing states are unable to provide. On the other hand, however, the distorted and often hidden agendas of profit-led players reveals its shortcomings and dangers. If we look at the telecom industry, we note how it has contributed to track disease propagation in a number of health emergencies such as Ebola. And if the global open data community has called for smoother data exchange between the private and the public sector to collectively address the spread of the virus,in the absence of adequate regulatory frameworks in the Global South, for example in the field of privacy and data retention, local authorities might fall prey to outside interventions of dubious nature….(More)”.