How ‘Social Distancing’ Can Get Lost in Translation

Curated on Posted on by Stefaan Verhulst

Ruth Michaelson at the Smithsonian Magazine: “…Even as tongue-in-cheek phrases like “avoiding the Rona” abound on American social media, to say nothing of the rapper Cardi B’s enunciation of “coronavirus,” other terms like “social distancing,” or “lockdown,” have quickly entered our daily vocabulary.

But what these terms mean in different countries (or regions or cities within regions, in Wuhan’s case) is a question of translation as well as interpretation. Communities around the world remain under government-enforced lockdown to prevent the spread of COVID-19, but few have understood “stay at home,” or liu-zai-jia-li in Mandarin, to mean precisely the same thing. The concept of social distancing, normally indicating a need to avoid contact with others, can mean anything from avoiding public transport to the World Health Organization’s recommendation to “maintain at least one metre distance,” from those who are coughing or sneezing. In one Florida county, officials explained the guideline by suggesting to residents they stay “one alligator” away from each other.

The way that terms like “social distancing,” are adopted across languages provides a way to understand how countries across the globe are coping with the COVID-19 threat. For instance, the Mandarin Chinese translation of “social distancing”, or ju-li-yuan-dian, is interpreted differently in Wuhan dialect, explains Jin. “Instead of ‘keep a distance,’ Wuhan dialect literally translates this as ‘send far away.’”

Through these small shifts in language, says Jin, “people in Wuhan expose their feelings about their own suffering.”

In Sweden, meanwhile, has currently registered more than 16,000 cases of COVID-19, the highest incidence rate in Scandinavia. The government has taken an unusually lax approach to enforcing its pandemic mitigation policies, placing the emphasis on citizens to self-police, perhaps to ill effect. While Swedes do use terms like social distancing, or rather the noun socialt avstånd, these are accompanied by other ideas that are more popular in Sweden. “Herd immunity or flockimmunitet is a very big word around here,” says Jan Pedersen, director of the Institute for Interpreting and Translation Studies at Stockholm University.

“Sweden is famous for being a very consensus driven society, and this applies here as well,” he says. “There’s a great deal of talk about trust.” In this case, he explained, citizens have trust – tillit – in the authorities to make good choices and so choose to take personligt ansvar, or personal responsibility.

Pedersen has also noticed some new language developing as a result. “The word recommendation, rekommendationer, in Sweden has taken on much stronger force,” he said. “Recommendation used to be a recommendation, what you could do or not. Now it’s slightly stronger … We would use words like obey with laws, but now here you obey a recommendation, lyda rekommendationer.”…(More)”.

How data science can ease the COVID-19 pandemic

Curated on Posted on by Stefaan Verhulst

Nigam Shah and Jacob Steinhardt at Brookings: “Social distancing and stay-at-home orders in the United States have slowed the infection rate of SARS-CoV-2, the pathogen that causes COVID-19. This has halted the immediate threat to the U.S. healthcare system, but consensus on a long-term plan or solution to the crisis remains unclear.  As the reality settles in that there are no quick fixes and that therapies and vaccines will take several months if not years to invent, validate, and mass produce, this is a good time to consider another question: How can data science and technology help us endure the pandemic while we develop therapies and vaccines?

Before policymakers reopen their economies, they must be sure that the resulting new COVID-19 cases will not force local healthcare systems to resort to crisis standards of care. Doing so requires not just prevention and suppression of the virus, but ongoing measurement of virus activity, assessment of the efficacy of suppression measures, and forecasting of near-term demand on local health systems. This demand is highly variable given community demographics, the prevalence of pre-existing conditions, and population density and socioeconomics.

Data science can already provide ongoing, accurate estimates of health system demand, which is a requirement in almost all reopening plans. We need to go beyond that to a dynamic approach of data collection, analysis, and forecasting to inform policy decisions in real time and iteratively optimize public health recommendations for re-opening. While most reopening plans propose extensive testing, contact tracing, and monitoring of population mobility, almost none consider setting up such a dynamic feedback loop. Having such feedback could determine what level of virus activity can be tolerated in an area, given regional health system capacity, and adjust population distancing accordingly.

We propose that by using existing technology and some nifty data science, it is possible to set up that feedback loop, which would maintain healthcare demand under the threshold of what is available in a region. Just as the maker community stepped up to cover for the failures of the government to provide adequate protective gear to health workers, this is an opportunity for the data and tech community to partner with healthcare experts and provide a measure of public health planning that governments are unable to do. Therefore, the question we invite the data science community to focus on is: How can data science help forecast regional health system resource needs given measurements of virus activity and suppression measures such as population distancing?…

Concretely, then, the crucial “data science” task is to learn the counterfactual function linking last week’s population mobility and today’s transmission rates to project hospital demand two weeks later. Imagine taking past measurements of mobility around April 10 in a region (such as the Santa Clara County’s report from COVID-19 Community Mobility Reports), the April 20 virus transmission rate estimate for the region (such as from http://rt.live), and the April 25 burden on the health system (such as from the Santa Clara County Hospitalization dashboard), to learn a function that uses today’s mobility and transmission rates to anticipate needed hospital resources two weeks later. It is unclear how many days of data of each proxy measurement we need to reliably learn such a function, what mathematical form this function might take, and how we do this correctly with the observational data on hand and avoid the trap of mere function-fitting. However, this is the data science problem that needs to be tackled as a priority. 

Adopting such technology and data science to keep anticipated healthcare needs under the threshold of availability in a region requires multiple privacy trade-offs, which will require thoughtful legislation so that the solutions invented for enduring the current pandemic do not lead to loss of privacy in perpetuity. However, given the immense economic as well as hidden medical toll of the shutdown, we urgently need to construct an early warning system that tells us to enhance suppression measures if the next COVID-19 outbreak peak might overwhelm our regional healthcare system. It is imperative that we focus our attention on using data science to anticipate, and manage, regional health system resource needs based on local measurements of virus activity and effects of population distancing….(More)”.

The digital tools that can keep democracy going during lockdown

Curated on Posted on by Stefaan Verhulst

Rosalyn Old at Nesta: “In the midst of the COVID-19 global pandemic, governments at all levels are having to make decisions to postpone elections and parliamentary sessions, all while working remotely and being under pressure to deliver fast-paced and effective decision-making.

In times of crisis, there can be a tension between the instinct to centralise decision-making for efficiency, sacrificing consultation in the process, and the need to get citizens on board with plans for large-scale changes to everyday life. While such initial reactions are understandable, in the current and next phases we need a different approach – democracy must go on.

Effective use of digital tools can provide a way to keep parliamentary and government processes going in a way that enhances rather than threatens democracy. This is a unique opportunity to experiment with digital methods to address a number of business-as-usual pain points in order to support institutions and citizen engagement in the long term.

Digital tools can help with the spectrum of decision-making

While digital tools can’t give the answers, they can support the practicalities of remote decision-making. Our typology of digital democracy shows how digital tools can be used to harness the wisdom of the crowd in different stages of a process:A typology of digital democracy

A typology of digital democracy

Digital tools can collect information from different sources to provide an overview of the options. To weigh up pros and cons, platforms such as Your Priorities and Consul enable people to contribute arguments. If you need a sense of what is important and to try to find consensus, Pol.is and Loomio may help. To quickly gauge support for different options from stakeholders, platforms such as All Our Ideas enable ranking of a live bank of ideas. If you need to gather questions and needs of citizens, head to platforms like Sli.do or online forms or task management tools like Trello or Asana….(More)”.

Digital tools against COVID-19: Framing the ethical challenges and how to address them

Curated on Posted on by Stefaan Verhulst

Paper by Urs Gasser et al: “Data collection and processing via digital public health technologies are being promoted worldwide by governments and private companies as strategic remedies for mitigating the COVID-19 pandemic and loosening lockdown measures. However, the ethical and legal boundaries of deploying digital tools for disease surveillance and control purposes are unclear, and a rapidly evolving debate has emerged globally around the promises and risks of mobilizing digital tools for public health. To help scientists and policymakers navigate technological and ethical uncertainty, we present a typology of the primary digital public health applications currently in use. Namely: proximity and contact tracing, symptom monitoring, quarantine control, and flow modeling. For each, we discuss context-specific risks, cross-sectional issues, and ethical concerns. Finally, in recognition of the need for practical guidance, we propose a navigation aid for policymakers made up of ten steps for the ethical use of digital public health tools….(More)”.

Crisis as Opportunity: Fostering Inclusive Public Engagement in Local Government

Curated on Posted on by Stefaan Verhulst

Ashley Labosier at Mercatus Center: “In addressing local challenges, such as budget deficits, aging infrastructure, workforce development, opioid addiction, homelessness, and disaster preparedness, a local government must take into account the needs, preferences, and values of its entire community, not just politically active groups. However, research shows that citizens who participate in council meetings or public hearings rarely reflect the diversity of the community in terms of age, race, or opinion, and traditional public comment periods seldom add substantively to local policy decisions. It is therefore clear that reform of public engagement in local governments is long overdue.

An opportunity for such a reform is emerging out of the tragedy of the COVID-19 pandemic. As local governments cope with the crisis, they should strengthen their relationship with their residents by adopting measures that are inclusive and sensitive to all the constituencies in their jurisdiction.

This work starts by communicating clearly both the measures adopted to combat COVID-19 and the guidelines for citizen compliance and by making sure this information is accessible and disseminated throughout the entire community. During the crisis, building trust with the community will also entail restraining from advancing projects that are not instrumental to crisis management, particularly controversial projects. Diligence and prudence during the crisis should create the opportunity to try and test new forms of dialogue with citizens.

These new forms of engagement should increase the legitimacy and public support for government decisions and cultivate a civic culture where residents no longer see themselves as customers vying for services, but as citizens with ownership in the democratic process and its outcomes. In this brief, I propose ways to integrate digital technology tools into those new forms of public engagement.

Integrating Digital Technologies into Public Engagement

Over the past 15 years a new civic tech industry has emerged to assist local governments with public engagement. Videos and podcasts increase access to guidelines, rules, and procedures published by local governments. Real-time language translation is possible thanks to machine-learning algorithms that are relatively easy to integrate into online help lines. Government web portals increase access to official information, particularly for those with limited mobility or with visual or hearing impairments. These and other digital platforms have the potential to increase citizens’ participation, particularly when the costs—such as transportation or childcare—keep people from attending public meetings.

Indeed, tech solutions have the potential to increase citizen participation. During a decade of working with local governments on technology and public engagement, I have observed technologies that promote inclusiveness in public participation and technologies that simply magnify the voice of groups traditionally engaged in politics. Drawing from this experience, I offer local governments and agencies five recommendations to integrate technology into their public engagement programs….(More)”.

Can We Track COVID-19 and Protect Privacy at the Same Time?

Curated on Posted on by Stefaan Verhulst

Sue Halpern at the New Yorker: “…Location data are the bread and butter of “ad tech.” They let marketers know you recently shopped for running shoes, are trying to lose weight, and have an abiding affection for kettle corn. Apps on cell phones emit a constant trail of longitude and latitude readings, making it possible to follow consumers through time and space. Location data are often triangulated with other, seemingly innocuous slivers of personal information—so many, in fact, that a number of data brokers claim to have around five thousand data points on almost every American. It’s a lucrative business—by at least one estimate, the data-brokerage industry is worth two hundred billion dollars. Though the data are often anonymized, a number of studies have shown that they can be easily unmasked to reveal identities—names, addresses, phone numbers, and any number of intimacies.

As Buckee knew, public-health surveillance, which serves the community at large, has always bumped up against privacy, which protects the individual. But, in the past, public-health surveillance was typically conducted by contract tracing, with health-care workers privately interviewing individuals to determine their health status and trace their movements. It was labor-intensive, painstaking, memory-dependent work, and, because of that, it was inherently limited in scope and often incomplete or inefficient. (At the start of the pandemic, there were only twenty-two hundred contact tracers in the country.)

Digital technologies, which work at scale, instantly provide detailed information culled from security cameras, license-plate readers, biometric scans, drones, G.P.S. devices, cell-phone towers, Internet searches, and commercial transactions. They can be useful for public-health surveillance in the same way that they facilitate all kinds of spying by governments, businesses, and malign actors. South Korea, which reported its first covid-19 case a month after the United States, has achieved dramatically lower rates of infection and mortality by tracking citizens with the virus via their phones, car G.P.S. systems, credit-card transactions, and public cameras, in addition to a robust disease-testing program. Israel enlisted Shin Bet, its secret police, to repurpose its terrorist-tracking protocols.  China programmed government-installed cameras to point at infected people’s doorways to monitor their movements….(More)”.

How to Make the Perfect Citizen? Lessons from China’s Model of Social Credit System

Curated on Posted on by Stefaan Verhulst

Paper by Liav Orgad and Wessel Reijers: “The COVID19 crisis has triggered a new wave of digitalization of the lives of citizens. To counter the devastating effects of the virus, states and corporations are experimenting with systems that trace citizens as an integral part of public life. In China, a comprehensive sociotechnical system of citizenship governance has already in force with the implementation of the Social Credit System—a technology-driven project that aims to assess, evaluate, and steer the behavior of Chinese citizens.

After presenting social credit systems in China’s public and private sectors (Part I), the article provides normative standards to distinguish the Chinese system from comparable Western systems (Part II). It then shows the manner in which civic virtue is instrumentalized in China, both in content (“what” it is) and in form (“how” to cultivate it) (Part III), and claims that social credit systems represent a new form of citizenship governance, “cybernetic citizenship,” which implements different conceptions of state power, civic virtue, and human rights (Part V). On the whole, the article demonstrates how the Chinese Social Credit System redefines the institution of citizenship and warns against similar patterns that are mushrooming in the West.

The article makes three contributions: empirically, it presents China’s Social Credit Systems and reveals their data sources, criteria used, rating methods, and attached sanctions and rewards. Comparatively, it shows that, paradoxically, China’s Social Credit System is not fundamentally different than credit systems in Western societies, yet indicates four points of divergence: scope, authority, regulation, and regime. Normatively, it claims that China’s Social Credit System creates a form of cybernetic citizenship governance, which redefines the essence of citizenship….(More)”

COVID-19 Outbreak Prediction with Machine Learning

Curated on Posted on by Stefaan Verhulst

Paper by Sina F. Ardabili et al: “Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved.

This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models….(More)”.

Doctors are using AI to triage covid-19 patients. The tools may be here to stay

Curated on Posted on by Stefaan Verhulst

Karen Hao at MIT Technology Review: “The pandemic, in other words, has turned into a gateway for AI adoption in health care—bringing both opportunity and risk. On the one hand, it is pushing doctors and hospitals to fast-track promising new technologies. On the other, this accelerated process could allow unvetted tools to bypass regulatory processes, putting patients in harm’s way.

“At a high level, artificial intelligence in health care is very exciting,” says Chris Longhurst, the chief information officer at UC San Diego Health. “But health care is one of those industries where there are a lot of factors that come into play. A change in the system can have potentially fatal unintended consequences.”

Before the pandemic, health-care AI was already a booming area of research. Deep learning, in particular, has demonstrated impressive results for analyzing medical images to identify diseases like breast and lung cancer or glaucoma at least as accurately as human specialists. Studies have also shown the potential of using computer vision to monitor elderly people in their homes and patients in intensive care units.

But there have been significant obstacles to translating that research into real-world applications. Privacy concerns make it challenging to collect enough data for training algorithms; issues related to bias and generalizability make regulators cautious to grant approvals. Even for applications that do get certified, hospitals rightly have their own intensive vetting procedures and established protocols. “Physicians, like everybody else—we’re all creatures of habit,” says Albert Hsiao, a radiologist at UCSD Health who is now trialing his own covid detection algorithm based on chest x-rays. “We don’t change unless we’re forced to change.”

As a result, AI has been slow to gain a foothold. “It feels like there’s something there; there are a lot of papers that show a lot of promise,” said Andrew Ng, a leading AI practitioner, in a recent webinar on its applications in medicine. But “it’s not yet as widely deployed as we wish.”…

In addition to the speed of evaluation, Durand identifies something else that may have encouraged hospitals to adopt AI during the pandemic: they are thinking about how to prepare for the inevitable staff shortages that will arise after the crisis. Traumatic events like a pandemic are often followed by an exodus of doctors and nurses. “Some doctors may want to change their way of life,” he says. “What’s coming, we don’t know.”…(More)”

Reweaving the social fabric after the crisis

Curated on Posted on by Stefaan Verhulst

Andy Haldane at the Financial Times: “Yet one source of capital, as in past pandemics, is bucking these trends: social capital. This typically refers to the network of relationships across communities that support and strengthen societies. From surveys, we know that people greatly value these networks, even though social capital itself is rarely assigned a monetary value.

The social distancing policies enacted across the world to curb the spread of Covid-19 might have been expected to weaken social networks and damage social capital. In fact, the opposite has happened. People have maintained physical distance while pursuing social togetherness. Existing networks have been strengthened and new ones ­created, often digitally. Even as other capital has crumbled, the stock of social capital has risen, acting as a counter­cyclical stabiliser across communities. We see this daily on our doorsteps through small acts of neighbourly kindness.

We see it in the activities of community groups, charities and philanthropic movements, whose work has risen in importance and prominence. And we see it too in the vastly increased numbers of people volunteering to help. Before the crisis struck, the global volunteer corps numbered a staggering 1bn people. Since then, more people than ever have signed up for civic service, including 750,000 volunteers who are supporting the UK National Health Service. They are the often-invisible army helping fight this invisible enemy.

This same pattern appeared during past periods of societal stress, from pandemics to wars. Then, as now, faith and community groups provided the glue bonding societies together. During the 19th century, the societal stresses arising from the Industrial Revolution — homelessness, family separation, loneliness — were the catalyst for the emergence of the charitable sector.

The economic and social progress that followed the Industrial Revolution came courtesy of a three-way partnership among the private, public and social sectors. The private sector provided the innovative spark; the state provided insurance to the incomes, jobs and health of citizens; and the social sector provided the support network to cope with disruption to lives and livelihoods. Back then, social capital (every bit as much as human, financial and physical capital) provided the foundations on which capitalism was built….(More)”.