On the forecastability of food insecurity


Paper by Pietro Foini,  Michele Tizzoni, Daniela Paolotti, and Elisa Omodei: “Food insecurity, defined as the lack of physical or economic access to safe, nutritious and sufficient food, remains one of the main challenges included in the 2030 Agenda for Sustainable Development. Near real-time data on the food insecurity situation collected by international organizations such as the World Food Programme can be crucial to monitor and forecast time trends of insufficient food consumption levels in countries at risk.

Here, using food consumption observations in combination with secondary data on conflict, extreme weather events and economic shocks, we build a forecasting model based on gradient boosted regression trees to create predictions on the evolution of insufficient food consumption trends up to 30 days in to the future in 6 countries (Burkina Faso, Cameroon, Mali, Nigeria, Syria and Yemen). Results show that the number of available historical observations is a key element for the forecasting model performance. Among the 6 countries studied in this work, for those with the longest food insecurity time series, the proposed forecasting model makes it possible to forecast the prevalence of people with insufficient food consumption up to 30 days into the future with higher accuracy than a naive approach based on the last measured prevalence only. The framework developed in this work could provide decision makers with a tool to assess how the food insecurity situation will evolve in the near future in countries at risk. Results clearly point to the added value of continuous near real-time data collection at sub-national level…(More)”.

Lessons learned from telco data informing COVID-19 responses: toward an early warning system for future pandemics?


Introduction to a special issue of Data and Policy (Open Access) by Richard Benjamins, Jeanine Vos, and Stefaan Verhulst: “More than a year into the COVID-19 pandemic, the damage is still unfolding. While some countries have recently managed to gain an element of control through aggressive vaccine campaigns, much of the developing world — South and Southeast Asia in particular — remain in a state of crisis. Given what we now know about the global nature of this disease and the potential for mutant versions to develop and spread, a crisis anywhere is cause for concern everywhere. The world remains very much in the grip of this public health crisis.

From the beginning, there has been hope that data and technology could offer solutions to help inform the government’s response strategy and decision-making. Many of the expectations have been focused on mobile data analytics in particular, whereby mobile network operators create mobility insights and decision-support tools generated from anonymized and aggregated telco data. This stems both from a growing group of mobile network operators having significantly invested in systems and capabilities to develop such products and services for public and private sector customers. As well as their value having been demonstrated in addressing different global challenges, ranging from models to better understand the spread of Zika in Brazil to interactive dashboards to aid emergency services during earthquakes and floods in Japan. Yet despite these experiences, many governments across the world still have limited awareness, capabilities and resources to leverage these tools, in their efforts to limit the spread of COVID-19 using non-pharmaceutical interventions (NPI), both from a medical and economic point of view.

Today, we release the first batch of papers of a special collection of Data & Policy that examines both the potential of mobile data, as well as the challenges faced in delivering these tools to inform government decision-making. Consisting of 5 papers from 33 researchers and experts from academia, industry and government, the articles cover a wide range of geographies, including Europe, Argentina, Brazil, Ecuador, France, Gambia, Germany, Ghana, Austria, Belgium, and Spain. Responding to our call for case studies to illustrate the opportunities (and challenges) offered by mobile big data in the fight against COVID-19, the authors of these papers describe a number of examples of how mobile and mobile-related data have been used to address the medical, economic, socio-cultural and political aspects of the pandemic….(More)”.

Ethics and governance of artificial intelligence for health


The WHO guidance…”on Ethics & Governance of Artificial Intelligence for Health is the product of eighteen months of deliberation amongst leading experts in ethics, digital technology, law, human rights, as well as experts from Ministries of Health.  While new technologies that use artificial intelligence hold great promise to improve diagnosis, treatment, health research and drug development and to support governments carrying out public health functions, including surveillance and outbreak response, such technologies, according to the report, must put ethics and human rights at the heart of its design, deployment, and use.

The report identifies the ethical challenges and risks with the use of artificial intelligence of health, six consensus principles to ensure AI works to the public benefit of all countries. It also contains a set of recommendations that can ensure the governance of artificial intelligence for health maximizes the promise of the technology and holds all stakeholders – in the public and private sector – accountable and responsive to the healthcare workers who will rely on these technologies and the communities and individuals whose health will be affected by its use…(More)”

Pooling society’s collective intelligence helped fight COVID – it must help fight future crises too


Aleks Berditchevskaia and Kathy Peach at The Conversation: “A Global Pandemic Radar is to be created to detect new COVID variants and other emerging diseases. Led by the WHO, the project aims to build an international network of surveillance hubs, set up to share data that’ll help us monitor vaccine resistance, track diseases and identify new ones as they emerge.

This is undeniably a good thing. Perhaps more than any event in recent memory, the COVID pandemic has brought home the importance of pooling society’s collective intelligence and finding new ways to share that combined knowledge as quickly as possible.

At its simplest, collective intelligence is the enhanced capacity that’s created when diverse groups of people work together, often with the help of technology, to mobilise more information, ideas and knowledge to solve a problem. Digital technologies have transformed what can be achieved through collective intelligence in recent years – connecting more of us, augmenting human intelligence with machine intelligence, and helping us to generate new insights from novel sources of data.

So what have we learned over the last 18 months of collective intelligence pooling that can inform the Global Pandemic Radar? Building from the COVID crisis, what lessons will help us perfect disease surveillance and respond better to future crises?…(More)”

Governance mechanisms for sharing of health data: An approach towards selecting attributes for complex discrete choice experiment studies


Paper by Jennifer Viberg Johansson: “Discrete Choice Experiment (DCE) is a well-established technique to elicit individual preferences, but it has rarely been used to elicit governance preferences for health data sharing.

The aim of this article was to describe the process of identifying attributes for a DCE study aiming to elicit preferences of citizens in Sweden, Iceland and the UK for governance mechanisms for digitally sharing different kinds of health data in different contexts.

A three-step approach was utilised to inform the attribute and level selection: 1) Attribute identification, 2) Attribute development and 3) Attribute refinement. First, we developed an initial set of potential attributes from a literature review and a workshop with experts. To further develop attributes, focus group discussions with citizens (n = 13), ranking exercises among focus group participants (n = 48) and expert interviews (n = 18) were performed. Thereafter, attributes were refined using group discussion (n = 3) with experts as well as cognitive interviews with citizens (n = 11).

The results led to the selection of seven attributes for further development: 1) level of identification, 2) the purpose of data use, 3) type of information, 4) consent, 5) new data user, 6) collector and 7) the oversight of data sharing. Differences were found between countries regarding the order of top three attributes. The process outlined participants’ conceptualisation of the chosen attributes, and what we learned for our attribute development phase.

This study demonstrates a process for selection of attributes for a (multi-country) DCE involving three stages: Attribute identification, Attribute development and Attribute refinement. This study can contribute to improve the ethical aspects and good practice of this phase in DCE studies. Specifically, it can contribute to the development of governance mechanisms in the digital world, where people’s health data are shared for multiple purposes….(More)”.

How Low and Middle-Income Countries Are Innovating to Combat Covid


Article by Ben Ramalingam, Benjamin Kumpf, Rahul Malhotra and Merrick Schaefer: “Since the Covid-19 pandemic hit, innovators around the world have developed thousands of novel solutions and practical approaches to this unprecedented global health challenge. About one-fifth of those innovations have come from low- and middle-income countries across sub-Saharan Africa, South Asia, and Latin America, according to our analysis of WHO data, and they work to address the needs of poor, marginalized, or excluded communities at the so-called bottom of the pyramid.

Over the past year we’ve been able to learn from and support some of those inspiring innovators. Their approaches are diverse in scope and scale and cover a vast range of pandemic response needs — from infection prevention and control to community engagement, contract tracing, social protection, business continuity, and more.

Here we share seven lessons from those innovators that offer promising insights not only for the ongoing Covid response but also for how we think about, manage, and enable innovation.

1. Ensure that your solutions are sensitive to social and cultural dynamics. 

Successful innovations are relevant to the lived realities of the people they’re intended to help. Socially and culturally sensitive design approaches see greater uptake and use. This is true in both resource-constrained and resource-rich environments.

Take contact tracing in Kenya. In a context where more than half of all residents use public transportation every day, the provider of a ticketing app for Nairobi’s bus fleets adapted its software to collect real-time passenger data. The app has been used across one of the world’s most mobile populations to trace Covid-19 cases, identify future clusters, trigger automated warnings to exposed passengers, and monitor the maximum number of people that could safely be allowed in each vehicle….(More)”.

The pandemic showed that big tech isn’t a public health savior


Nicole Wetsman at Verge: “…It seemed like Big Tech, with its analytic firepower and new focus on health, could help with these very real problems. “We saw all over the papers: Facebook is gonna save the world, and Google’s going to save the world,” says Katerini Storeng, a medical anthropologist who studies public-private partnerships in global public health at the University of Oslo. Politicians were eager to welcome Silicon Valley to the table and to discuss the best ways to manage the pandemic. “It was remarkable, and indicative of a blurring of the boundaries between the public domain and the private domain,” Storeng says.

Over a year later, many of the promised tech innovations never materialized. There are areas where tech companies have made significant contributions — like collecting mobility data that helped officials understand the effects of social distancing policies. But Google wasn’t actually building a nationwide testing website. The program that eventually appeared, a testing program for California run by Google’s sibling company Verily, was quietly phased out after it created more problems than it solved.

Now, after a year, we’re starting to get a clear picture of what worked, what didn’t, and what the relationship between Big Tech and public health might look like in the future.

Tech companies were interested in health before the pandemic, and COVID-19 accelerated those initiatives. There may be things that tech companies are better equipped to handle than traditional public health agencies and other public institutions, and the past year showed some of those strengths. But it also showed their weaknesses and underscored the risks to putting health responsibilities in the hands of private companies — which have goals outside of the public good.

When the pandemic started, Storeng was already studying how private companies participated in public health preparedness efforts. Over the past two decades, consumers and health officials have become more and more confident that tech hacks can be shortcuts to healthy communities. These digital hacks can take many forms and include everything from a smartphone app nudging people toward exercise to a data model analyzing how an illness spreads, she says.

“What they have in common, I think, is this hope and optimism that it’ll help bypass some more systemic, intrinsic problems,” Storeng says.

But healthcare and public health present hard problems. Parachuting in with a new approach that isn’t based on a detailed understanding of the existing system doesn’t always work. “I think we tend to believe in our culture that higher tech, private sector is necessarily better,” says Melissa McPheeters, co-director of the Center for Improving the Public’s Health through Informatics at Vanderbilt University. “Sometimes that’s true. And sometimes it’s not.”

McPheeters spent three years as the director of the Office of Informatics and Analytics at the Tennessee Department of Health. While in that role, she got calls from technology companies all the time, promising quick fixes to any data issues the department was facing. But they were more interested in delivering a product than a collaboration, she says. “It never began with, ‘Help me understand your problem.’”…(More)”

Collective data rights can stop big tech from obliterating privacy


Article by Martin Tisne: “…There are two parallel approaches that should be pursued to protect the public.

One is better use of class or group actions, otherwise known as collective redress actions. Historically, these have been limited in Europe, but in November 2020 the European parliament passed a measure that requires all 27 EU member states to implement measures allowing for collective redress actions across the region. Compared with the US, the EU has stronger laws protecting consumer data and promoting competition, so class or group action lawsuits in Europe can be a powerful tool for lawyers and activists to force big tech companies to change their behavior even in cases where the per-person damages would be very low.

Class action lawsuits have most often been used in the US to seek financial damages, but they can also be used to force changes in policy and practice. They can work hand in hand with campaigns to change public opinion, especially in consumer cases (for example, by forcing Big Tobacco to admit to the link between smoking and cancer, or by paving the way for car seatbelt laws). They are powerful tools when there are thousands, if not millions, of similar individual harms, which add up to help prove causation. Part of the problem is getting the right information to sue in the first place. Government efforts, like a lawsuit brought against Facebook in December by the Federal Trade Commission (FTC) and a group of 46 states, are crucial. As the tech journalist Gilad Edelman puts it, “According to the lawsuits, the erosion of user privacy over time is a form of consumer harm—a social network that protects user data less is an inferior product—that tips Facebook from a mere monopoly to an illegal one.” In the US, as the New York Times recently reported, private lawsuits, including class actions, often “lean on evidence unearthed by the government investigations.” In the EU, however, it’s the other way around: private lawsuits can open up the possibility of regulatory action, which is constrained by the gap between EU-wide laws and national regulators.

Which brings us to the second approach: a little-known 2016 French law called the Digital Republic Bill. The Digital Republic Bill is one of the few modern laws focused on automated decision making. The law currently applies only to administrative decisions taken by public-sector algorithmic systems. But it provides a sketch for what future laws could look like. It says that the source code behind such systems must be made available to the public. Anyone can request that code.

Importantly, the law enables advocacy organizations to request information on the functioning of an algorithm and the source code behind it even if they don’t represent a specific individual or claimant who is allegedly harmed. The need to find a “perfect plaintiff” who can prove harm in order to file a suit makes it very difficult to tackle the systemic issues that cause collective data harms. Laure Lucchesi, the director of Etalab, a French government office in charge of overseeing the bill, says that the law’s focus on algorithmic accountability was ahead of its time. Other laws, like the European General Data Protection Regulation (GDPR), focus too heavily on individual consent and privacy. But both the data and the algorithms need to be regulated…(More)”

The Coronavirus Pandemic Creative Responses Archive


National Academies of Science: “Creativity often flourishes in stressful times because innovation evolves out of need. During the coronavirus pandemic, we are witnessing a range of creative responses from individuals, communities, organizations, and industries. Some are intensely personal, others expansively global—mirroring the many ways the pandemic has affected us. What do these responses to the pandemic tell us about our society, our level of resilience, and how we might imagine the future? Explore the Coronavirus Pandemic Creative Responses Archive…

What Robots Can — And Can’t — Do For the Old and Lonely


Katie Engelhart at The New Yorker: “…In 2017, the Surgeon General, Vivek Murthy, declared loneliness an “epidemic” among Americans of all ages. This warning was partly inspired by new medical research that has revealed the damage that social isolation and loneliness can inflict on a body. The two conditions are often linked, but they are not the same: isolation is an objective state (not having much contact with the world); loneliness is a subjective one (feeling that the contact you have is not enough). Both are thought to prompt a heightened inflammatory response, which can increase a person’s risk for a vast range of pathologies, including dementia, depression, high blood pressure, and stroke. Older people are more susceptible to loneliness; forty-three per cent of Americans over sixty identify as lonely. Their individual suffering is often described by medical researchers as especially perilous, and their collective suffering is seen as an especially awful societal failing….

So what’s a well-meaning social worker to do? In 2018, New York State’s Office for the Aging launched a pilot project, distributing Joy for All robots to sixty state residents and then tracking them over time. Researchers used a six-point loneliness scale, which asks respondents to agree or disagree with statements like “I experience a general sense of emptiness.” They concluded that seventy per cent of participants felt less lonely after one year. The pets were not as sophisticated as other social robots being designed for the so-called silver market or loneliness economy, but they were cheaper, at about a hundred dollars apiece.

In April, 2020, a few weeks after New York aging departments shut down their adult day programs and communal dining sites, the state placed a bulk order for more than a thousand robot cats and dogs. The pets went quickly, and caseworkers started asking for more: “Can I get five cats?” A few clients with cognitive impairments were disoriented by the machines. One called her local department, distraught, to say that her kitty wasn’t eating. But, more commonly, people liked the pets so much that the batteries ran out. Caseworkers joked that their clients had loved them to death….(More)”.