Paper by Tânia Carvalho et al: “The Covid-19 pandemic has affected the world at multiple levels. Data sharing was pivotal for advancing research to understand the underlying causes and implement effective containment strategies. In response, many countries have facilitated access to daily cases to support research initiatives, fostering collaboration between organisations and making such data available to the public through open data platforms. Despite the several advantages of data sharing, one of the major concerns before releasing health data is its impact on individuals’ privacy. Such a sharing process should adhere to state-of-the-art methods in Data Protection by Design and by Default. In this paper, we use a Covid-19 data set from Portugal’s second-largest hospital to show how it is feasible to ensure data privacy while improving the quality and maintaining the utility of the data. Our goal is to demonstrate how knowledge exchange in multidisciplinary teams of healthcare practitioners, data privacy, and data science experts is crucial to co-developing strategies that ensure high utility in de-identified data…(More).”
Cities, health, and the big data revolution
Blog by Harvard Public Health: “Cities influence our health in unexpected ways. From sidewalks to crosswalks, the built environment affects how much we move, impacting our risk for diseases like obesity and diabetes. A recent New York City study underscores that focusing solely on infrastructure, without understanding how people use it, can lead to ineffective interventions. Researchers analyzed over two million Google Street View images, combining them with health and demographic data to reveal these dynamics. Harvard Public Health spoke with Rumi Chunara, director of New York University’s Center for Health Data Science and lead author of the study.
Why study this topic?
We’re seeing an explosion of new data sources, like street-view imagery, being used to make decisions. But there’s often a disconnect—people using these tools don’t always have the public health knowledge to interpret the data correctly. We wanted to highlight the importance of combining data science and domain expertise to ensure interventions are accurate and impactful.
What did you find?
We discovered that the relationship between built environment features and health outcomes isn’t straightforward. It’s not just about having sidewalks; it’s about how often people are using them. Improving physical activity levels in a community could have a far greater impact on health outcomes than simply adding more infrastructure.
It also revealed the importance of understanding the local context. For instance, Google Street View data sometimes misclassifies sidewalks, particularly near highways or bridges, leading to inaccurate conclusions. Relying solely on this data, without accounting for these nuances, could result in less effective interventions…(More)”.
Randomize NIH grant giving
Article by Vinay Prasad: “A pause in NIH study sections has been met with fear and anxiety from researchers. At many universities, including mine, professors live on soft money. No grants? If you are assistant professor, you can be asked to pack your desk. If you are a full professor, the university slowly cuts your pay until you see yourself out. Everyone talks about you afterwards, calling you a failed researcher. They laugh, a little too long, and then blink back tears as they wonder if they are next. Of course, your salary doubles in the new job and you are happier, but you are still bitter and gossiped about.
In order to apply for NIH grants, you have to write a lot of bullshit. You write specific aims and methods, collect bios from faculty and more. There is a section where you talk about how great your department and team is— this is the pinnacle of the proverbial expression, ‘to polish a turd.’ You invite people to work on your grant if they have a lot of papers or grants or both, and they agree to be on your grant even though they don’t want to talk to you ever again.
You submit your grant and they hire someone to handle your section. They find three people to review it. Ideally, they pick people who have no idea what you are doing or why it is important, and are not as successful as you, so they can hate read your proposal. If, despite that, they give you a good score, you might be discussed at study section.
The study section assembles scientists to discuss your grant. As kids who were picked last in kindergarten basketball, they focus on the minutiae. They love to nitpick small things. If someone on study section doesn’t like you, they can tank you. In contrast, if someone loves you, they can’t really single handedly fund you.
You might wonder if study section leaders are the best scientists. Rest assured. They aren’t. They are typically mid career, mediocre scientists. (This is not just a joke, data support this claim see www.drvinayprasad.com). They rarely have written extremely influential papers.
Finally, your proposal gets a percentile score. Here is the chance of funding by percentile. You might get a chance to revise your grant if you just fall short….Given that the current system is onerous and likely flawed, you would imagine that NIH leadership has repeatedly tested whether the current method is superior than say a modified lottery, aka having an initial screen and then randomly giving out the money.
Of course not. Self important people giving out someone else’s money rarely study their own processes. If study sections are no better than lottery, that would mean a lot of NIH study section officers would no longer need to work hard from home half the day, freeing up money for one more grant.
Let’s say we take $200 million and randomize it. Half of it is allocated to being given out in the traditional method, and the other half is allocated to a modified lottery. If an application is from a US University and passes a minimum screen, it is enrolled in the lottery.
Then we follow these two arms into the future. We measure publications, citations, h index, the average impact factor of journals in which the papers are published, and more. We even take a subset of the projects and blind reviewers to score the output. Can they tell which came from study section?…(More)”.
The Attention Crisis Is Just a Distraction
Essay by Daniel Immerwahr: “…If every video is a starburst of expression, an extended TikTok session is fireworks in your face for hours. That can’t be healthy, can it? In 2010, the technology writer Nicholas Carr presciently raised this concern in “The Shallows: What the Internet Is Doing to Our Brains,” a Pulitzer Prize finalist. “What the Net seems to be doing,” Carr wrote, “is chipping away my capacity for concentration and contemplation.” He recounted his increased difficulty reading longer works. He wrote of a highly accomplished philosophy student—indeed, a Rhodes Scholar—who didn’t read books at all but gleaned what he could from Google. That student, Carr ominously asserted, “seems more the rule than the exception.”
Carr set off an avalanche. Much read works about our ruined attention include Nir Eyal’s “Indistractable,” Johann Hari’s “Stolen Focus,” Cal Newport’s “Deep Work,” and Jenny Odell’s “How to Do Nothing.” Carr himself has a new book, “Superbloom,” about not only distraction but all the psychological harms of the Internet. We’ve suffered a “fragmentation of consciousness,” Carr writes, our world having been “rendered incomprehensible by information.”
Read one of these books and you’re unnerved. But read two more and the skeptical imp within you awakens. Haven’t critics freaked out about the brain-scrambling power of everything from pianofortes to brightly colored posters? Isn’t there, in fact, a long section in Plato’s Phaedrus in which Socrates argues that writing will wreck people’s memories?…(More)”.
To Bot or Not to Bot? How AI Companions Are Reshaping Human Services and Connection
Essay by Julia Freeland Fisher: “Last year, a Harvard study on chatbots drew a startling conclusion: AI companions significantly reduce loneliness. The researchers found that “synthetic conversation partners,” or bots engineered to be caring and friendly, curbed loneliness on par with interacting with a fellow human. The study was silent, however, on the irony behind these findings: synthetic interaction is not a real, lasting connection. Should the price of curing loneliness really be more isolation?
Missing that subtext is emblematic of our times. Near-term upsides often overshadow long-term consequences. Even with important lessons learned about the harms of social media and big tech over the past two decades, today, optimism about AI’s potential is soaring, at least in some circles.
Bots present an especially tempting fix to long-standing capacity constraints across education, health care, and other social services. AI coaches, tutors, navigators, caseworkers, and assistants could overcome the very real challenges—like cost, recruitment, training, and retention—that have made access to vital forms of high-quality human support perennially hard to scale.
But scaling bots that simulate human support presents new risks. What happens if, across a wide range of “human” services, we trade access to more services for fewer human connections?…(More)”.
Overcoming challenges associated with broad sharing of human genomic data
Paper by Jonathan E. LoTempio Jr & Jonathan D. Moreno: “Since the Human Genome Project, the consensus position in genomics has been that data should be shared widely to achieve the greatest societal benefit. This position relies on imprecise definitions of the concept of ‘broad data sharing’. Accordingly, the implementation of data sharing varies among landmark genomic studies. In this Perspective, we identify definitions of broad that have been used interchangeably, despite their distinct implications. We further offer a framework with clarified concepts for genomic data sharing and probe six examples in genomics that produced public data. Finally, we articulate three challenges. First, we explore the need to reinterpret the limits of general research use data. Second, we consider the governance of public data deposition from extant samples. Third, we ask whether, in light of changing concepts of broad, participants should be encouraged to share their status as participants publicly or not. Each of these challenges is followed with recommendations…(More)”.
Data sharing restrictions are hampering precision health in the European Union
Paper by Cristina Legido-Quigley et al: “Contemporary healthcare is undergoing a transition, shifting from a population-based approach to personalized medicine on an individual level. In October 2023, the European Partnership for Personalized Medicine was officially launched to communicate the benefits of this approach to citizens and healthcare systems in member countries. The main debate revolves around the inconsistency in regulatory changes within personal data access and its potential commercialization. Moreover, the lack of unified consensus within European Union (EU) countries is leading to problems with data sharing to progress personalized medicine. Here we discuss the integration of biological data with personal information on a European scale for the advancement of personalized medicine, raising legal considerations of data protection under the EU General Data Protection Regulation (GDPR)…(More)”.
Digitalizing sewage: The politics of producing, sharing, and operationalizing data from wastewater-based surveillance
Paper by Josie Wittmer, Carolyn Prouse, and Mohammed Rafi Arefin: “Expanded during the COVID-19 pandemic, Wastewater-Based Surveillance (WBS) is now heralded by scientists and policy makers alike as the future of monitoring and governing urban health. The expansion of WBS reflects larger neoliberal governance trends whereby digitalizing states increasingly rely on producing big data as a ‘best practice’ to surveil various aspects of everyday life. With a focus on three South Asian cities, our paper investigates the transnational pathways through which WBS data is produced, made known, and operationalized in ‘evidence-based’ decision-making in a time of crisis. We argue that in South Asia, wastewater surveillance data is actively produced through fragile but power-laden networks of transnational and local knowledge, funding, and practices. Using mixed qualitative methods, we found these networks produced artifacts like dashboards to communicate data to the public in ways that enabled claims to objectivity, ethical interventions, and transparency. Interrogating these representations, we demonstrate how these artifacts open up messy spaces of translation that trouble linear notions of objective data informing accountable, transparent, and evidence-based decision-making for diverse urban actors. By thinking through the production of precarious biosurveillance infrastructures, we respond to calls for more robust ethical and legal frameworks for the field and suggest that the fragility of WBS infrastructures has important implications for the long-term trajectories of urban public health governance in the global South…(More)”
Survey of attitudes in a Danish public towards reuse of health data
Paper by Lea Skovgaard et al: “Everyday clinical care generates vast amounts of digital data. A broad range of actors are interested in reusing these data for various purposes. Such reuse of health data could support medical research, healthcare planning, technological innovation, and lead to increased financial revenue. Yet, reuse also raises questions about what data subjects think about the use of health data for various different purposes. Based on a survey with 1071 respondents conducted in 2021 in Denmark, this article explores attitudes to health data reuse. Denmark is renowned for its advanced integration of data infrastructures, facilitating data reuse. This is therefore a relevant setting from which to explore public attitudes to reuse, both as authorities around the globe are currently working to facilitate data reuse opportunities, and in the light of the recent agreement on the establishment in 2024 of the European Health Data Space (EHDS) within the European Union (EU). Our study suggests that there are certain forms of health data reuse—namely transnational data sharing, commercial involvement, and use of data as national economic assets—which risk undermining public support for health data reuse. However, some of the purposes that the EHDS is supposed to facilitate are these three controversial purposes. Failure to address these public concerns could well challenge the long-term legitimacy and sustainability of the data infrastructures currently under construction…(More)”
Distorted insights from human mobility data
Paper by Riccardo Gallotti, Davide Maniscalco, Marc Barthelemy & Manlio De Domenico: “The description of human mobility is at the core of many fundamental applications ranging from urbanism and transportation to epidemics containment. Data about human movements, once scarce, is now widely available thanks to new sources such as phone call detail records, GPS devices, or Smartphone apps. Nevertheless, it is still common to rely on a single dataset by implicitly assuming that the statistical properties observed are robust regardless of data gathering and processing techniques. Here, we test this assumption on a broad scale by comparing human mobility datasets obtained from 7 different data-sources, tracing 500+ millions individuals in 145 countries. We report wide quantifiable differences in the resulting mobility networks and in the displacement distribution. These variations impact processes taking place on these networks like epidemic spreading. Our results point to the need for disclosing the data processing and, overall, to follow good practices to ensure robust and reproducible results…(More)”