Surveillance capitalism companies, such as Google and Facebook, have substantially increased the amount of information collected, analyzed, and monetized, including health information increasingly used in precision medicine research, thereby presenting great challenges for health privacy.

The Centers for Disease Control and Prevention’s goal is to develop a surveillance system of public health laws that would both support research and analysis among policymakers and legislators, and support the scientific basis for public health law. This session was convened, in part, to discuss the value of creating an electronic system to track public health legal information. Public health surveillance is the “ongoing, systematic collection, analysis, interpretation, and dissemination of data regarding (...) a health-related event for use in public health action to reduce morbidity and mortality and to improve health. Data disseminated by a public health surveillance system can be used for immediate public health action, program planning and evaluation, and formulating research hypotheses.” There is currently no system available that meets the goals of this definition of “surveillance” for public health laws. (shrink)

The Centers for Disease Control and Prevention’s goal is to develop a surveillance system of public health laws that would both support research and analysis among policymakers and legislators, and support the scientific basis for public health law. This session was convened, in part, to discuss the value of creating an electronic system to track public health legal information. Public health surveillance is the “ongoing, systematic collection, analysis, interpretation, and dissemination of data regarding (...) a health-related event for use in public health action to reduce morbidity and mortality and to improve health. Data disseminated by a public health surveillance system can be used for immediate public health action, program planning and evaluation, and formulating research hypotheses.” There is currently no system available that meets the goals of this definition of “surveillance” for public health laws. (shrink)

For the first time, the revised Common Rule specifies that public health surveillance activities are not research. This article reviews the historical development of the public health surveillance exclusion and implications for other foundational public health practices.

Existing ethics guidelines, influential literature and policies on ethical research generally focus on real-time data collection from humans. They enforce individual rights and liberties, thereby lowering need for aggregate protections. Although dependable, emerging public health research paradigms like research using public health data raise new challenges to their application. Unlike traditional research, RUPD is population-based, aligned to public health activities, and often reliant on pre-collected longitudinal data. These characteristics, when considered in relation to the (...) generally lower protective ethico-legal frameworks of the Global South, including Africa, highlight ethical gaps. Health and demographic surveillance systems are examples of public health programs that accommodate RUPD in these contexts. We set out to explore the perspectives of professionals with a working knowledge of these systems to determine practical ways of appropriating the foundational principles of health research to advance the ever growing opportunities in RUPD. We present their perspectives and in relation to the literature and our ethical analysis, make context relevant recommendations. We further argue for the development of a framework founded on the discussions and recommendations as a minimum base for achieving optimal ethics for optimal RUPD in the Global South. (shrink)

Data-sharing is a desired default in the field of public health and a source of much ethical deliberation. Sharing data potentially contributes the largest, most efficient source of scientific data, but is fraught with contextual challenges which make stakeholders, particularly those in under-resourced contexts hesitant or slow to share. Relatively little empirical research has engaged stakeholders in discussing the issue. This study sought to explore relevant experiences, contextual, and subjective explanations around the topic to provide a (...) rich and detailed presentation of what it means to different stakeholders and contexts to share data and how that can guide practice and ethical guidance. A qualitative design involving interviews was undertaken with professionals working in public health institutions endowed with data, ethics committees, and advisory agencies which help shape health research in Africa. A descriptive form of thematic analysis was used to summarize results into six key themes: The role of HDSSs in research using public health data and data-sharing; Ownership and funding are critical factors influencing data-sharing; Other factors discourage data-sharing; Promoting and sustaining data-sharing; Ethical guidance structures; and Establishing effective guidance. The themes reveal factors regarding the willingness or not to share and an intricate ethical system that current discourse could reflect. Many of the concerns resonate with the literature, but a whole other gamut of people and process issues; commitments, investments, careers, and the right ethical guidance are needed to realize a sustainable goal of reaching ‘share’ as a default. (shrink)

Volume 20, Issue 10, October 2020, Page 63-65.

Volume 20, Issue 10, October 2020, Page 79-81.

Background Bioethical debates about privacy, big data, and public health surveillance have not sufficiently engaged the perspectives of those being surveilled. The data justice framework suggests that big data applications have the potential to create disproportionate harm for socially marginalized groups. Using examples from our research on HIV surveillance for individuals incarcerated in jails, we analyze ethical issues in deploying big data in public health surveillance. -/- Methods We conducted qualitative, semi-structured (...) interviews with 24 people living with HIV who had been previously incarcerated in county jails about their perspectives on and experiences with HIV surveillance, as part of a larger study to characterize ethical considerations in leveraging big data techniques to enhance continuity of care for incarcerated people living with HIV. -/- Results Most participants expressed support for the state health department tracking HIV testing results and viral load data. Several viewed HIV surveillance as a violation of privacy, and several had actively avoided contact from state public health outreach workers. Participants were most likely to express reservations about surveillance when they viewed the state’s motives as self-interested. Perspectives highlight the mistrust that structurally vulnerable people may have in the state’s capacity to act as an agent of welfare. Findings suggest that adopting a nuanced, context-sensitive view on surveillance is essential. -/- Conclusions Establishing trustworthiness through interpersonal interactions with public health personnel is important to reversing historical legacies of harm to racial minorities and structurally vulnerable groups. Empowering stakeholders to participate in the design and implementation of data infrastructure and governance is critical for advancing a data justice agenda, and can offset privacy concerns. The next steps in advancing the data justice framework in public health surveillance will be to innovate ways to represent the voices of structurally vulnerable groups in the design and governance of big data initiatives. (shrink)

In the era of precision medicine and expanding health information technologies, large representative datasets are considered necessary for addressing health inequities. Partially in response to gro...

Surveillance in public health is the means by which people who are responsible for preventing or controlling threats to health get the timely, ongoing, and reliable information they need about the occurrence, antecedents, time course, geographic spread, consequences, and nature of these threats among the populations they serve. “Policy surveillance” is the ongoing, systematic collection, analysis, and dissemination of information about laws and other policies of health importance.

This chapter provides a high-level overview of key ethical issues raised by the use of surveillance technologies, such as digital contact tracing, disease surveillance, and vaccine passports, to combat the COVID-19 pandemic. To some extent, these issues are entirely familiar. I argue that they raise old questions in new form and with new urgency, at the intersection of information ethics, research ethics, and public health. Whenever we deal with data-driven technologies, we have to ask how they (...) fare in relation to important values like privacy, fairness, transparency, and accountability—values emphasized by information ethics scholars. Likewise, when such technologies put individuals at risk in order to drive scientific research and knowledge construction, we have to ask how they implicate values such as autonomy, beneficence and non-maleficence, and justice—values central to research ethics. And as researchers focusing on health information have long argued, when the data collected by these technologies pertain to individuals and public health, these ethical issues take on a special cast. -/- It is also true, however, that the pandemic has placed these questions in a new and revealing light. I highlight three insights from information ethics and research ethics that can help us navigate this difficult terrain. First, the value of privacy is instrumental, not absolute—there is nothing wrong with asking how to balance privacy against other important values. Second, privacy has both individual and social importance. Weighing privacy, on one hand, and public health, on the other, is not, therefore, a contest between individual and collective interests. Rather, it is an attempt to balance disparate public goods. Third, we ought to put these kinds of ethical decisions in the hands of third parties, rather than leaving them up to those who directly stand to benefit from them. In the case of pandemic surveillance technologies, this should mean more public, democratic oversight. (shrink)

Surveillance is essential for communicable disease prevention and control. Traditional notification of demographic and clinical information, about individuals with selected infectious diseases, allows appropriate public health action and is protected by public health and privacy legislation, but is slow and insensitive. Big data–based electronic surveillance, by commercial bodies and government agencies, which draws on a plethora of internet- and mobile device–based sources, has been widely accepted, if not universally welcomed. Similar anonymous digital sources also contain (...) syndromic information, which can be analysed, using customised algorithms, to rapidly predict infectious disease outbreaks, but the data are nonspecific and predictions sometimes misleading. However, public health authorities could use these online sources, in combination with de-identified personal health data, to provide more accurate and earlier warning of infectious disease events—including exotic or emerging infections—even before the cause is confirmed, and allow more timely public health intervention. Achieving optimal benefits would require access to selected data from personal electronic health and laboratory records and the potential to re-identify individuals found to be involved in outbreaks, to ensure appropriate care and infection control. Despite existing widespread digital surveillance and major potential community benefits of extending its use to communicable disease control, there is considerable public disquiet about allowing public health authorities access to personal health data. Informed public discussion, greater transparency and an ethical framework will be essential to build public trust in the use of new technology for communicable disease control. (shrink)

The public health measures implemented in response to the COVID-19 pandemic have resulted in a substantially increased shared reliance on private infrastructure and digital services in areas such as healthcare, education, retail, and the workplace. This development has (i) granted a number of private actors significant (informational) power, and (ii) given rise to a range of digital surveillance practices incidental to the pandemic itself. In this paper, we reflect on these secondary consequences of the pandemic and observe that, (...) even though collateral data disclosure and additional activity monitoring appears to have been generally socially accepted as inevitable consequences of the pandemic, part and parcel of a larger conglomeration of emergency compromises, these increased surveillance practices were not directly justified by appeals to solidarity and public health in the same way that the instigating public health measures were. Based on this observation, and given the increased reliance on private actors for maintaining the digital space, we argue that governments have a duty to (i) seek and ensure that there are justifications for collateral data disclosure and activity monitoring by private actors in the context of (future) public health emergencies like the COVID-19 pandemic, and (ii) regulate and provide accountability mechanisms for and oversight over these private surveillance practices on par with governmental essential services that engage in surveillance activities. (shrink)

ABSTRACT Data from digital technologies are increasingly integrated in public health research. In April of 2020, we interviewed a subset of participants who completed a survey approximately one month earlier. Using the survey, we contacted and interviewed participants who had expressed their willingness or unwillingness to share digital data for use in public health. We followed a directed content analysis approach for the analysis of the interview data. Among participants who had reported being unwilling to (...) share data, concerns about privacy, confidentiality, and the purpose of the research were cited. During the interviews, 76.9% of the participants who had who had previously indicated that they were unwilling to share their data, expressed willingness to share data in order to assist with COVID-19 prevention. Our results contribute to our understanding of people’s perspectives on sharing personal data and of the way their perspectives can vary as a function of potential uses of their personal information. (shrink)

The European Union Data Protection Regulation will have profound implications for public health, health services research and statistics in Europe. The EU Commission's Proposal was a breakthrough in balancing privacy rights and rights to health and healthcare. The European Parliament, however, has proposed extensive amendments. This paper reviews the amendments proposed by the European Parliament Committee on Civil Liberties, Justice and Home Affairs and their implications for health research and statistics. The amendments eliminate most innovations (...) brought by the Proposal. Notably, derogation to the general prohibition of processing sensitive data shall be allowed for public interests such as the management of healthcare services, but not health research, monitoring, surveillance and governance. The processing of personal health data for historical, statistical or scientific purposes shall be allowed only with the consent of the data subject or if the processing serves an exceptionally high public interest, cannot be performed otherwise and is legally authorised. Research, be it academic, government, corporate or market research, falls under the same rule. The proposed amendments will make difficult or render impossible research and statistics involving the linkage and analysis of the wealth of data from clinical, administrative, insurance and survey sources, which have contributed to improving health outcomes and health systems performance and governance; and may illegitimise efforts that have been made in some European countries to enable privacy-respectful data use for research and statistical purposes. If the amendments stand as written, the right to privacy is likely to override the right to health and healthcare in Europe. (shrink)

Federal, state, and local laws shape the use of health information for public health purposes, such as the mandated collection of data through electronic disease reporting systems. Health professionals can leverage these data to better anticipate and plan for the needs of communities, which is seen in the use of electronic case reporting.

This book presents a comprehensive theory of the ethics and political philosophy of public health surveillance based on reciprocal obligations among surveillers, those under surveillance, and others potentially affected by surveillance practices. Public health surveillance aims to identify emerging health trends, population health trends, treatment efficacy, and methods of health promotion--all apparently laudatory goals. Nonetheless, as with anti-terrorism surveillance, public health surveillance raises complex questions about privacy, political liberty, (...) and justice both of and in data use. Individuals and groups can be chilled in their personal lives, stigmatized or threatened, and used for the benefit of others when health information is wrongfully collected or used. Transparency and openness about data use, public involvement in decisions, and just distribution of the benefits of surveillance are core elements in the justification of surveillance practices. Understanding health surveillance practices, the concerns it raises, and how to respond to them is critical not only to ethical and trustworthy but also to publicly acceptable and ultimately sustainable surveillance practices. The book is of interest to scholars and practitioners of the ethics and politics of public health, bioethics, privacy and data technology, and health policy. These issues are ever more pressing in pandemic times, where misinformation can travel quickly and suspicions about disease spread, treatment efficacy, and vaccine safety can have devastating public health effects. (shrink)

There is increasing concern about “surveillance capitalism,” whereby for-profit companies generate value from data, while individuals are unable to resist (Zuboff 2019). Non-profits using data-enabled surveillance receive less attention. Higher education institutions (HEIs) have embraced data analytics, but the wide latitude that private, profit-oriented enterprises have to collect data is inappropriate. HEIs have a fiduciary relationship to students, not a narrowly transactional one (see Jones et al, forthcoming). They are responsible for facets of student (...) life beyond education. In addition to classrooms, learning management systems, and libraries, HEIs manage dormitories, gyms, dining halls, health facilities, career advising, police departments, and student employment. HEIs collect and use student data in all of these domains, ostensibly to understand learner behaviors and contexts, improve learning outcomes, and increase institutional efficiency through “learning analytics” (LA). ID card swipes and Wi-Fi log-ins can track student location, class attendance, use of campus facilities, eating habits, and friend groups. Course management systems capture how students interact with readings, video lectures, and discussion boards. Application materials provide demographic information. These data are used to identify students needing support, predict enrollment demands, and target recruiting efforts. These are laudable aims. However, current LA practices may be inconsistent with HEIs’ fiduciary responsibilities. HEIs often justify LA as advancing student interests, but some projects advance primarily organizational welfare and institutional interests. Moreover, LA advances a narrow conception of student interests while discounting privacy and autonomy. Students are generally unaware of the information collected, do not provide meaningful consent, and express discomfort and resigned acceptance about HEI data practices, especially for non-academic data (see Jones et al. forthcoming). The breadth and depth of student information available, combined with their fiduciary responsibility, create a duty that HEIs exercise substantial restraint and rigorous evaluation in data collection and use. (shrink)

Data sharing – broadly defined as the exchange of health-related data among multiple controllers and processors – has gained increased relevance in the health sciences over recent years as the need and demand for collaboration has increased. This includes data obtained through healthcare provisions, clinical trials, observational studies, public health surveillance programs, and other data collection methods. The practice of data sharing presents several notable challenges, however. Compliance with a complex and (...) dynamic regulatory framework is essential, with the General Data Protection Regulation being a prominent example in a European context. Recent regulatory developments related to clinical trial transparency, trade secrecy, data access, AI training data, and health data spaces further contribute to the difficulties. Simultaneously, government initiatives often encourage scientists to embrace principles of “open data” and “open innovation.” The variety of regulations in this domain has the potential to impede widespread data sharing and hinder innovation. This edited volume, therefore, compiles comparative case studies authored by leading scholars from diverse disciplines and jurisdictions. The book aims to outline the legal complexities of data sharing. By examining real-world scenarios from diverse disciplines and a global perspective, it explores the normative, policy, and ethical dilemmas that surround data sharing in the health sciences today. Chapter Patient Perspectives on Data Sharing, Chapter Supplementary Measures and Appropriate Safeguards for International Transfers of Health Data after Schrems II are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. (shrink)

Components of artificial intelligence (AI) for analysing social big data, such as natural language processing (NLP) algorithms, have improved the timeliness and robustness of health data. NLP techniques have been implemented to analyse large volumes of text from social media platforms to gain insights on disease symptoms, understand barriers to care and predict disease outbreaks. However, AI-based decisions may contain biases that could misrepresent populations, skew results or lead to errors. Bias, within the scope of this paper, (...) is described as the difference between the predictive values and true values within the modelling of an algorithm. Bias within algorithms may lead to inaccurate healthcare outcomes and exacerbate health disparities when results derived from these biased algorithms are applied to health interventions. Researchers who implement these algorithms must consider when and how bias may arise. This paper explores algorithmic biases as a result of data collection, labelling and modelling of NLP algorithms. Researchers have a role in ensuring that efforts towards combating bias are enforced, especially when drawing health conclusions derived from social media posts that are linguistically diverse. Through the implementation of open collaboration, auditing processes and the development of guidelines, researchers may be able to reduce bias and improve NLP algorithms that improve health surveillance. (shrink)

Introduction No consent for health and medical research is appropriate when the criteria for a waiver of consent are met, yet some ethics committees and data custodians still require informed consent. Methods A single-blind parallel-group randomised controlled trial: 1129 families of children born at a South Australian hospital were sent information explaining data linkage of childhood immunisation and hospital records for vaccine safety surveillance with 4 weeks to opt in or opt out by reply form, telephone (...) or email. A subsequent telephone interview gauged the intent of 1026 parents (91%) in relation to their actions and the sociodemographic differences between participants and non-participants in each arm. Results The participation rate was 21% (n=120/564) in the opt-in arm and 96% (n=540/565) in the opt-out arm (χ2 (1 df) = 567.7, p<0.001). Participants in the opt-in arm were more likely than non-participants to be older, married/de facto, university educated and of higher socioeconomic status. Participants in the opt-out arm were similar to non-participants, except men were more likely to opt out. Substantial proportions did not receive, understand or properly consider study invitations, and opting in or opting out behaviour was often at odds with parents' stated underlying intentions. Conclusions The opt-in approach resulted in low participation and a biased sample that would render any subsequent data linkage unfeasible, while the opt-out approach achieved high participation and a representative sample. The waiver of consent afforded under current privacy regulations for data linkage studies meeting all appropriate criteria should be granted by ethics committees, and supported by data custodians. Trial registration number Australian New Zealand Clinical Trials Registry ACTRN12610000332022. (shrink)

The accelerating adoption of electronic health record systems will have profound impacts on clinical care. It will also have far-reaching implications for public health research and surveillance, which in turn could lead to changes in public policy, statutes, and regulations. The public health benefits of EHR use can be significant. However, researchers and analysts who rely on EHR data must proceed with caution and understand the potential limitations of EHRs.Much has been written about the risk (...) of EHR privacy breaches. This paper focuses on a different set of concerns, those relating to data quality. Unlike clinical trial data, EHR data is not recorded primarily to meet the needs of researchers. Because of clinicians’ workloads, poor user-interface design, and other factors, EHR data is surprisingly likely to be erroneous, miscoded, fragmented, and incomplete. Although EHRs eliminate the problem of cryptic handwriting, other kinds of errors are more common with EHRs than with paper records. (shrink)

Artificial intelligence surveillance can be used to diagnose individual cases, track the spread of Covid‐19, and help provide care. The use of AI for surveillance purposes (such as detecting new Covid‐19 cases and gathering data from healthy and ill individuals) in a pandemic raises multiple concerns ranging from privacy to discrimination to access to care. Luckily, there exist several frameworks that can help guide stakeholders, especially physicians but also AI developers and public health officials, as they (...) navigate these treacherous shoals. While these frameworks were not explicitly designed for AI surveillance during a pandemic, they can be adapted to help address concerns regarding privacy, human rights, and due process and equality. In a time where the rapid implementation of all tools available is critical to ending a pandemic, physicians, public health officials, and technology companies should understand the criteria for the ethical implementation of AI surveillance. (shrink)

Introduction : a framework for public health ethics -- Moral considerations : bases and limits for public health -- The political and legal context of public health ethics -- Public health perspectives -- Surveillance and public health data : the foundation and eyes of public health -- Case finding : screening, testing, and tracing -- Immunization : protection through vaccination -- Containing communicable diseases : personal control measures -- Health communication -- (...) Public health and the environment. (shrink)

Syndromic surveillance uses new ways of gathering data to identify possible disease outbreaks. Because syndromic surveillance can be implemented to detect patterns before diseases are even identified, it poses novel problems for informed consent, patient privacy and confidentiality, and risks of stigmatization. This paper analyzes these ethical issues from the viewpoint of the patient as victim and vector. It concludes by pointing out that the new International Health Regulations fail to take full account of the ethical (...) challenges raised by syndromic surveillance. (shrink)

Drug‐resistant bacterial infections constitute a major threat to global public health. Several key bacteria that are becoming increasingly resistant are among those that are ubiquitously carried by human beings and usually cause no symptoms (i.e. individuals are asymptomatic carriers) until and/or unless a precipitating event leads to symptomatic infection (and thus disease). Carriers of drug‐resistant bacteria can also transmit resistant pathogens to others, thus putting the latter at risk of resistant infections. Accumulating evidence suggests that such transmission occurs not (...) only in hospital settings but also in the general community, although considerably more data are needed to assess the extent of this problem. Asymptomatic carriage of drug‐resistant bacteria raises important ethical questions regarding the appropriate public health response, including the degree to which it would be justified to impose burdens on asymptomatic carriers (and others) in order to prevent transmission. In this paper, we (i) summarize current evidence regarding the carriage of key drug‐resistant bacteria, noting important knowledge gaps; and (ii) explore the particular implications of existing public health ethics frameworks for policy‐making regarding asymptomatic carriers. Inter alia, we argue that the relative burdens imposed by public health measures on healthy carriers (as opposed to sick individuals) warrant careful consideration and should be proportionate to the expected public health benefits in terms of risks averted. We conclude that more surveillance and research regarding community transmission will be needed in order to clarify relevant risks and design proportionate policies, although extensive community surveillance itself would also require careful ethical consideration. (shrink)

Bioethics, Volume 36, Issue 3, Page 305-312, March 2022.

Web scraping involves using computer programs for automated extraction and organization of data from the Web for the purpose of further data analysis and use. It is frequently used by commercial companies, but also has become a valuable tool in epidemiological research and public health planning. In this paper, we explore ethical issues in a project that “scrapes” public websites of U.S. county jails as part of an effort to develop a comprehensive database to enhance HIV (...) class='Hi'>surveillance and improve continuity of care for incarcerated populations. We argue that the well-known framework of Emanuel et al. provides only partial ethical guidance for the activities we describe, which lie at a complex intersection of public health research and public health practice. We suggest some ethical considerations from the ethics of public health practice to help fill gaps in this relatively unexplored area. (shrink)

Surveillance is a core function of all public health systems. Responses to the COVID-19 pandemic have deployed traditional public health surveillance responses, such as contact tracing and quarantine, and extended these responses with the use of varied technologies, such as the use of smartphone location data, data networks, ankle bracelets, drones, and big data analysis. Applying Foucault’s (1979) notion of the panopticon, with its twin focus on surveillance and self-regulation, as the preeminent (...) form of social control in modern societies, we examine the increasing levels of surveillance enacted during this pandemic and how people have participated in, and extended, this surveillance, self-regulation, and social control through the use of digital media. Consideration is given to how such surveillance may serve public health needs and/or political interests and whether the rapid deployment of these extensive surveillance mechanisms risks normalizing these measures so that they become more acceptable and then entrenched post-COVID-19. (shrink)

This essay adopts three accounts of “the social” to get a clearer picture of why there is a barrier faced by the government when implementing contact tracing mobile applications. In Hong Kong's context, the paradox involves declining trust of the government's protection of data privacy and growing concern about data surveillance since the 2019 social unrest I argue that exploring the idea of sociality is valuable in that it re-reconfigures the datafication of pandemic control by revealing different (...) sets of social relations, particularly the asymmetrical power relation between the government and its people. The refusal to download or use the mobile app also shows that the public has a faith in human agency and human resistance in data-saturated cities. (shrink)

Public health ethics, like the field of public health it addresses, traditionally has focused more on practice and particular cases than on theory, with the result that some concepts, methods, and boundaries remain largely undefined. This paper attempts to provide a rough conceptual map of the terrain of public health ethics. We begin by briefly defining public health and identifying general features of the field that are particularly relevant for a discussion of public health ethics.Public (...) health is primarily concerned with the health of the entire population, rather than the health of individuals. Its features include an emphasis on the promotion of health and the prevention of disease and disability; the collection and use of epidemiological data, population surveillance, and other forms of empirical quantitative assessment; a recognition of the multidimensional nature of the determinants of health; and a focus on the complex interactions of many factors—biological, behavioral, social, and environmental—in developing effective interventions. (shrink)

Background Outbreaks of infectious disease cause serious and costly health and social problems. Two new technologies – pathogen whole genome sequencing and Big Data analytics – promise to improve our capacity to detect and control outbreaks earlier, saving lives and resources. However, routinely using these technologies to capture more detailed and specific personal information could be perceived as intrusive and a threat to privacy. Method Four community juries were convened in two demographically different Sydney municipalities and two regional (...) cities in New South Wales, Australia to elicit the views of well-informed community members on the acceptability and legitimacy of: making pathogen WGS and linked administrative data available for public health researchusing this information in concert with data linkage and machine learning to enhance communicable disease surveillance systems Fifty participants of diverse backgrounds, mixed genders and ages were recruited by random-digit-dialling and topic-blinded social-media advertising. Each jury was presented with balanced factual evidence supporting different expert perspectives on the potential benefits and costs of technologically enhanced public health research and communicable disease surveillance and given the opportunity to question experts. Results Almost all jurors supported data linkage and WGS on routinely collected patient isolates for the purposes of public health research, provided standard de-identification practices were applied. However, allowing this information to be operationalised as a syndromic surveillance system was highly contentious with three juries voting in favour, and one against by narrow margins. For those in favour, support depended on several conditions related to system oversight and security being met. Those against were concerned about loss of privacy and did not trust Australian governments to run secure and effective systems. Conclusions Participants across all four events strongly supported the introduction of data linkage and pathogenomics to public health research under current research governance structures. Combining pathogen WGS with event-based data surveillance systems, however, is likely to be controversial because of a lack of public trust, even when the potential public health benefits are clear. Any suggestion of private sector involvement or commercialisation of WGS or surveillance data was unanimously rejected. (shrink)

Research on privacy practices in digital environments has oftentimes discovered a paradoxical relationship between users’ discursive appraisal of privacy and their actual practices: the “privacy paradox.” The emergence of this paradox prompts us to conduct ethnography of a health and fitness platform in order to flesh out the structural mechanisms generating this paradox. We provide an ethnographic analysis of surveillance capitalism in action that relates front-end practices empirically to the data economy’s back-end operations to show how this (...) material-semiotic setup elicits users’ desire to become self-determined subjects in a way that makes them amenable as objects of behavioral engineering. We combine different ethnographic methods and materials to specify how different types of values are produced and translated on the investigated platform. The latter offers users the values of self-mastery and social visibility. However, the data generated in this process serve to translate these values into the value of economic amenability and thereupon ultimately into economic profit. What gets lost in translation, though, is the front-end promise of self-mastery. It is these structural mechanisms that generate the privacy paradox in the first place. (shrink)

The Dobbs opinion emphasizes that the state’s interest in the fetus extends to “all stages of development.” This essay briefly explores whether state legislators, agencies, and courts could use the “all stages of development” language to expand reproductive surveillance by using novel developments in consumer health technologies to augment those efforts.

Surveillance programs supporting the management of One Health issues such as antibiotic resistance are complex systems in themselves. Designing ethical surveillance systems is thus a complex task (retroactive and iterative), yet one that is also complicated to implement and evaluate (e.g., sharing, collaboration, and governance). The governance of health surveillance requires attention to ethical concerns about data and knowledge (e.g., performance, trust, accountability, and transparency) and empowerment ethics, also referred to as a form of (...) responsible self-governance. Ethics in reflexive governance operates as a systematic critical-thinking procedure that aims to define its value: What are the “right” criteria to justify how to govern “good” actions for a “better” future? The objective is to lay the foundations for a methodological framework in empirical bioethics, the rudiments of which have been applied to a case study to building reflexive governance in One Health. This ongoing critical thinking process involves “mapping, framing, and shaping” the dynamics of interests and perspectives that could jeopardize a “better” future. This paper proposes to hybridize methods to combine insights from collective deliberation and expert evaluation through a reflexive governance functioning as a community-based action-ethics methodology. The intention is to empower individuals and associations in a dialogue with society, which operation is carried out using a case study approach on data sharing systems. We based our reasoning on a feasibility study conducted in Québec, Canada (2018–2021), envisioning an antibiotic use surveillance program in animal health for 2023. Using the adaptive cycle and governance techniques and perspectives, we synthesize an alternative governance model rooted in the value of empowerment. The framework, depicted as a new “research and design (R&D)” practice, is linking operation and innovation by bridging the gap between Reflexive, Evaluative, and Deliberative reasonings and by intellectualizing the management of democratizing critical thinking locally (collective ethics) by recognizing its context (social ethics). Drawing on the literature in One Health and sustainable development studies, this article describes how a communitarian and pragmatic approach can broaden the vision of feasibility studies to ease collaboration through public-private-academic partnerships. The result is a process that “reassembles” the One Health paradigm under the perspective of global bioethics to create bridges between the person and the ecosystem through pragmatic ethics. (shrink)

Responses to outbreaks, epidemics and pandemics involves a heterogeneous set of activities that aim to address threats to public health. In addition to research, non-research activities, such as prevention and control interventions, and surveillance, are conducted. The boundaries between research and non-research responses can rapidly blur during a public health emergency such as the COVID-19 pandemic. There may be common elements between these types of activities, and they may draw on the same resources and infrastructure. Non-research activities, (...) such as surveillance and emergency non-research use of unproven interventions, and research activities must all be undertaken in an ethical manner as components of emergency response. However, care is needed to distinguish between non-research public health activities and research, because research often has considerations and requirements for its ethical conduct which are distinct from non-research public health activities. Research aims to produce generalizable knowledge, and mechanisms such as participant consent and independent ethics review aim to ensure that the rights and interests of research participants are respected. Ensuring that research and non-research activities are appropriately distinguished can additionally promote proper coordination of such activities, and increase trust and social accountability in pandemic responses. Consequently, it is important to distinguish between these different activities on the basis of their primary aim, and to consider whether their implementation is justifiable, based on their aims and the relevant ethical framework for each type of activity, and how they are coordinated as part of the larger collective activity of emergency response and management. Complex questions arise about how the different stakeholders involved in decision-making should make valid and justifiable decisions about whether the response activity is research or non-research. The cases in this chapter invite consideration about how such decisions should be made, and their implications, in the context of applications to conduct retrospective research into the outcomes of emergency uses of unproven interventions outside clinical trials, and of characterising antibody-testing initiatives and systematic data collection activities as surveillance or research. (shrink)

Containing the spread of pandemic transmission tends to go hand in hand with a surveillance regime that tracks movement, transmission and those who contract the virus or disease. An enduring legacy of the COVID-19 crisis will be the incremental development of surveillance technologies, ostensibly purposed to identify the threat and spread of a pandemic, giving birth to what amounts to the pandemic surveillance state. Whether this is seen as an undesirable outcome depends very much on the field (...) of expertise and the relevant slant. Health professionals and epidemiologists favor more surveillance; privacy and data security advocates fear a further denuding of protections. This paper examines the dangers of such technologies and efforts to seek a middle ground on app technologies designed to protect privacy. Such designs may, in time, seem more hopeful than actual. (shrink)

The essays in this book clarify the technical, legal, ethical, and social aspects of the interaction between eHealth technologies and surveillance practices. The book starts out by presenting a theoretical framework on eHealth and surveillance, followed by an introduction to the various ideas on eHealth and surveillance explored in the subsequent chapters. Issues addressed in the chapters include privacy and data protection, social acceptance of eHealth, cost-effective and innovative healthcare, as well as the privacy aspects of (...) employee wellness programs using eHealth, the use of mobile health app data by insurance companies, advertising industry and law enforcement, and the ethics of Big Data use in healthcare. A closing chapter draws on the previous content to explore the notion that people are 'under observation', bringing together two hitherto unrelated streams of scholarship interested in observation: eHealth and surveillance studies. In short, the book represents a first essential step towards cross-fertilization and offers new insights into the legal, ethical and social significance of being 'under observation'. (shrink)

This article examines how digital epidemiology and eHealth coalesce into a powerful health surveillance system that fundamentally changes present notions of body and health. In the age of Big Data and Quantified Self, the conceptual and practical distinctions between individual and population body, personal and public health, surveillance and health care are diminishing. Expanding on Armstrong’s concept of “surveillance medicine” to “quantified self medicine” and drawing on my own research on the symbolic (...) power of statistical constructs in medical encounters, this article explores the impact of digital health surveillance on people’s perceptions, actions and subjectivities. It discusses the epistemic confusions and paradoxes produced by a health care system that increasingly treats patients as risk profiles and prompts them to do the same, namely to perceive and manage themselves as a bundle of health and security risks. Since these risks are necessarily constructed in reference to epidemiological data that postulate a statistical gaze, they also construct or make-up disembodied “individuals on alert”. (shrink)

Background The emergence of molecular HIV surveillance (MHS) and cluster detection and response (CDR) programs as key features of the United States (US) HIV strategy since 2018 has caused major controversies. HIV surveillance programs that re-use individuals’ routinely collected clinical HIV data do not require consent on the basis that the public benefit of these programs outweighs individuals’ rights to opt out. However, criticisms of MHS/CDR have questioned whether expanded uses of HIV genetic sequence data for (...) prevention reach beyond traditional public health ethics frameworks. This study aimed to explore views on consent within MHS/CDR among critical stakeholders.Methods In 2021 we interviewed 26 US HIV stakeholders who identified as being critical or concerned about the rollout of MHS/CDR. Stakeholders included participants belonging to networks of people living with HIV, other advocates, academics, and public health professionals. This analysis focused on identifying the range of positions among critical and concerned stakeholders on consent affordances, opt-outs, how to best inform people living with HIV about how data about them are used in public health programs, and related ethical issues.Results Participants were broadly supportive of introducing some forms of consent into MHS/CDR. However, they differed on the specifics of implementing consent. While some participants did not support introducing consent affordances, all supported the idea that people living with HIV should be informed about how HIV surveillance and prevention is conducted and how individuals’ data are used.Conclusions MHS/CDR has caused sustained controversy. Among critical stakeholders, consent is generally desirable but contested, although the right for people living with HIV to be informed was centrally supported. In an era of big data-driven public health interventions and routine uses of HIV genetic sequence data in surveillance and prevention, CDC and other agencies should revisit public health ethics frameworks and consider the possibility of consent processes. (shrink)

KEY POINTS In Canada, commercial data brokers collect deidentified patient data from pharmacies, private drug insurers, the federal government and medical clinics without patient consent. Although pharmaceutical companies are the data brokers’ primary customers, academics and nonprofit and public entities also use commercial data sets, given the absence of a coordinated public approach to collecting these data across Canada. Risks of commercialized patient data include loss of anonymity, surveillance and marketing, discrimination and violation (...) of Indigenous data sovereignty. Coordinated infrastructure for the collection and coordination of health data across Canada and updated privacy legislation would protect individuals and communities and enable appropriate data uses. (shrink)

The Center for Disease Control and Prevention’s Active Bacterial Core Surveillance (CDC ABCs) Program is a collaborative effort betweeen the CDC, state health departments, laboratories, and universities to track invasive bacterial pathogens of particular importance to public health [1]. The year-end surveillance reports produced by this program help to shape public policy and coordinate responses to emerging infectious diseases over time. The ABCs case report form (CRF) data represents an excellent opportunity for data reuse (...) beyond the original surveillance purposes. (shrink)

The rise of genomic technologies has catalyzed shifts in the health care landscape through the commercialization of genome sequencing and testing services in the genomics marketplace. The development of consumer genomics into a growing array of information technologies aimed at collecting, curating, and broadly sharing personal data and biological materials reconstitutes the meaning of health and reframes patients into biocitizens. In this context, the good biocitizen is expected to assume personal responsibility for health through consumption of (...) genomic information and acquiescence to public and private efforts at data surveillance and aggregation. These shifts raise fundamental questions about how competing interests of the public, the state, and corporate entities will be reconciled and what trade‐offs are demanded for the promise of precision health. (shrink)

The corona pandemic altered many traditional and historical norms of society and law. COVID-19 created a humanitarian crisis in some parts of globe, while pandemic privacy and civil liberties were under threat all over world. To combat the deadly virus, individual liberty and equality were compromised. This paper focuses on how India’s health problem has compromised people’s right to privacy. It will highlight how strict executive policies led to the creation of a massive surveillance system in the name (...) of combating the COVID-19 pandemic, as well as how the absence of any policy or legal framework led to the exclusion of individuals and their families who were suspected of having the virus or caring for those who were infected with the deadly virus. The paper uses case studies and data collected from primary as well as secondary sources. The authors will also point out how the absence of privacy regulation puts millions of citizens’ private information at risk of being compromised or exploited against their will. (shrink)

Emerging genomic technologies promise more efficient infectious disease control. Whole genome sequencing is increasingly being used in tuberculosis diagnosis, surveillance, and epidemiology. However, while the use of WGS by public health agencies may raise ethical, legal, and socio-political concerns, these challenges are poorly understood. Between November 2017 and April 2018, we conducted semi-structured interviews with 22 key stakeholders across the fields of governance and policy, public health, and laboratory sciences representing the major jurisdictions currently using WGS in (...) national TB programs. Thematic analysis of the interviews was conducted using NVivo 11. Respondents identified several ethical and practical challenges associated with WGS in TB care and surveillance, all related to issues of trust, including: 1) the power of public health; 2) data sharing and profits derived from surveillance efforts; and 3) concerns regarding who has access to, and can benefit from, the technology. Additional challenges included: the potential utility that WGS adds to a public health program, the risks associated with linking necessary epidemiological metadata to the genomic data, and challenges associated with jurisdictional capacity to implement the technology. Successful implementation of WGS is dependent on fostering relationships of trust between those working with genomics technology and those directly impacted by it, including clinicians. Building trust between the public and the public health agencies and within public health agencies themselves is critical due to the inherent complexity of WGS and its implementation for communicable disease control purposes. (shrink)

Feminist scholars have long demonstrated how women are constrained through dieting discourse. Today’s scholars wrestle with similar themes, but confront a thornier question: how do we make sense of a food discourse that frames food choices through a lens of empowerment and health, rather than vanity and restriction? This article addresses this question, drawing from interviews and focus groups with women (N = 100), as well as health-focused food writing. These data allow us to document a postfeminist (...) food discourse that we term the do-diet. The do-diet reframes dietary restrictions as positive choices, while maintaining an emphasis on body discipline, expert knowledge, and self-control. Our analysis demonstrates how the do-diet remediates a tension at the heart of neoliberal consumer culture: namely, the tension between embodying discipline through dietary control and expressing freedom through consumer choice. With respect to theory, our analysis demonstrates how the embodied dimensions of neoliberalism find gendered expression through postfeminism. We conclude that the do-diet heightens the challenge of developing feminist critiques of gendered body ideals and corporeal surveillance, as it promises a way of eating that is both morally responsible and personally empowering. (shrink)

The design and reporting of data-driven studies seeking to measure misinformation are patchy and inconsistent, and these studies rarely measure associations with, or effects on, behaviour. The consequence is that data-driven misinformation studies are not yet useful as an empirical basis for guiding when to act on emerging misinformation threats, or for deciding when it is more appropriate to do nothing to avoid inadvertently amplifying misinformation. In a narrative review focused on examples of health-related misinformation, we take (...) a critical perspective of data-driven misinformation studies. To address this problem, we propose a curated and open library of misinformation examples and describe its structure and how it might be used to support actionable surveillance. We draw on experiences with other curated repositories to speculate on the likely challenges related to achieving critical mass and maintaining data consistency. We conclude that an open library of misinformation could help improve the consistency of data-driven misinformation study design and reporting, as well as provide an empirical basis from which to make decisions about how to act on new and emerging misinformation threats. (shrink)

Background The opioid epidemic has enabled rapid and unsurpassed use of big data on people with opioid use disorder to design initiatives to battle the public health crisis, generally without adequate input from impacted communities. Efforts informed by big data are saving lives, yielding significant benefits. Uses of big data may also undermine public trust in government and cause other unintended harms. Objectives We aimed to identify concerns and recommendations regarding how to use big data (...) on opioid use in ethical ways. Methods We conducted focus groups and interviews in 2019 with 39 big data stakeholders who had interest in or knowledge of the Public Health Data Warehouse maintained by the Massachusetts Department of Public Health. Results Concerns regarding big data on opioid use are rooted in potential privacy infringements due to linkage of previously distinct data systems, increased profiling and surveillance capabilities, limitless lifespan, and lack of explicit informed consent. Also problematic is the inability of affected groups to control how big data are used, the potential of big data to increase stigmatization and discrimination of those affected despite data anonymization, and uses that ignore or perpetuate biases. Participants support big data processes that protect and respect patients and society, ensure justice, and foster patient and public trust in public institutions. Recommendations for ethical big data governance offer ways to narrow the big data divide, enact shared data governance, cultivate public trust and earn social license for big data uses, and refocus ethical approaches. Conclusions Using big data to address the opioid epidemic poses ethical concerns which, if unaddressed, may undermine its benefits. Findings can inform guidelines on how to conduct ethical big data governance and in ways that protect and respect patients and society, ensure justice, and foster patient and public trust in public institutions. (shrink)