The question of what it means to be human remains one of the most fundamental inquiries in philosophy, with profound ethical implications, particularly in healthcare. This paper offers a conceptual framework for healthcare professionals by exploring the ontological status of the human being and the concept of personhood, grounded in classical metaphysical principles. Through a phenomenological, epistemological, axiological, and ontological lens, it proposes a unified understanding of human dignity that can inform and elevate clinical practice. While the dialogue between Greek philosophy and the Judeo-Christian tradition established a robust and enduring notion of dignity, and Kantian ethics reinforced the centrality of the human being as an end in itself, the increasing compartmentalization of knowledge—though fruitful in some respects—has obscured the integral vision of the human person. In the medical field, this fragmentation can diminish awareness of the relational, existential, and spiritual dimensions essential to humane care. In response, this paper reaffirms the relevance of philosophical anthropology for medical ethics. It contends that safeguarding human dignity amid contemporary scientific and technological challenges requires returning to an ontological vision of the person-one that transcends functionalist and reductionist models and restores the human being to the center of healthcare. By doing so, it offers professionals a deeper foundation for ethical discernment and compassionate practice.
Tom Bisson, Henriette Voelker, Sanddhya Jayabalan
et al.
Large language model (LLM)-based AI agents are increasingly capable of complex clinical reasoning and may soon participate in medical decision-making with limited or no real-time human oversight. This shift raises fundamental questions about how the core principles of medical ethics (i.e., beneficence, nonmaleficence, autonomy, and justice) can be upheld when the clinical responsibility extends to autonomous systems. Here we propose an ethics-by-design framework for medical AI agents comprising six practical interventions: auditable ethical reasoning modules, explicit human override conditions, structured patient preference profiles, AI-specific ethics oversight tools, global benchmarking repositories for ethical scenarios, and regulatory sandboxes for real-world evaluation. Together, these mechanisms aim to operationalize ethical governance for emerging clinical AI agents. https://github.com/BissonTom/Ethical-Governance-of-Medical-AI-Agents
After World War Ⅱ, in order to avoid war crimes prosecution, the Unit 731 members handed over their research materials to the United States. Enryo Hojo, a figure who left a dark mark in the history of Japanese biological warfare, has largely remained outside the academic spotlight due to a lack of historical sources. This article systematically reviews Enryo Hojo's medical and military career, using research reports written by him, which are preserved in both the United States and Japan, as a guide. It explores the multifaceted roles of Unit 731's medical personnel within the wartime military-academic collaboration system and provides detailed accounts of the biological warfare experiments and tactics employed by Unit 731. These research reports are not only important materials for biological warfare studies but also serve as necessary references for examining Japanese colonial medicine during World War Ⅱ and as critical evidence revealing the medical crimes committed by Unit 731.
Abstract Background Medical gaslighting- a phenomenon where healthcare professionals dismiss or minimize patients’ symptoms- has garnered increasing attention due to its potential to cause significant harm to patients. This study aims to examine the ethical ramifications and implications of medical gaslighting, and explore how patients interpret and experience interactions affected by medical gaslighting. Methods We conducted two narrative interviews with fourteen participants. The first interview was conducted 2–3 days after discharge from hospitalization, and the second was carried out a month later. We then interpreted their stories through bioethical lenses. Results Data analysis yielded two main themes: (1) Pain dismissal and minimization; (2) Delayed or missed diagnoses- as subjectively perceived by interviewees. Using a principlist approach, we argue that medical gaslighting constitutes an obstacle to respect for patient autonomy and jeopardizes proper actualization of beneficence. Participants frequently described feeling dismissed, especially when presenting with complex or non-visible symptoms. Conclusions Medical gaslighting appears to be a common and impactful experience that contributes to psychological distress and reduces trust in the medical system, potentially delaying diagnosis and treatment. Healthcare institutions must prioritize training on implicit bias, communication skills, and patient-centered care to mitigate these harmful interactions. Future research should further explore structural contributors and develop interventions to foster more validating clinical environments. We propose some practical implications for eradicating medical gaslighting based on our findings.
Pietro Refolo, Costanza Raimondi, Salvatore Simone Masilla
et al.
Abstract Background End-of-life (EoL) decisions represent some of the most ethically complex and emotionally charged aspects of healthcare. Understanding the attitudes of physicians, nurses, and the public toward EoL decisions is crucial for aligning care provided with the personal values and preferences of patients. Aim To explore the attitudes of physicians, nurses, and the general public toward EoL decisions, including the withdrawal or withholding of life-sustaining treatments, euthanasia, physician-assisted suicide (PAS), palliative sedation, and advance care planning (ACP) within European countries. Design An umbrella review was conducted, covering the period from January 2010 to June 2024. The search strategy included Medline, CINAHL, and PsycINFO, supplemented by manual searches of reference lists of all included studies to identify additional relevant studies. Results The search identified 587 papers, 11 of which were included in the synthesis. Of these, six addressed euthanasia and PAS, three focused on ACP, one on the withdrawal of life-sustaining treatments, and one on palliative sedation. In Europe, the general public expressed the highest level of support for EoL practices such as euthanasia and PAS, followed by nurses, while physicians often held a more cautious perspective. For withdrawal of treatment, palliative sedation, and ACP, a critical recurring theme was the need to improve communication between patients and healthcare professionals. Conclusions The divergence underscores the intricate complexity of navigating ethical, cultural, and professional considerations in EoL care. Effective communication serves as a cornerstone for respecting patient autonomy and ensuring that healthcare decisions align with individual values, goals and preferences.
The ethics committee (EC) promotes ethical evaluation of biomedical research to safeguard and well-being of all potential research participants. Assessment of research protocol, patient information leaflet, informed consent form, questionnaire, and any other supporting documents is a moral and legal obligation to EC. According to the WHO (World Health Organization), to be a member of EC requires a basic certification. However, this practice is uncertain in Bangladesh. This short communication highlights how EC members learn research ethics.
Heyuan Huang, Alexandra DeLucia, Vijay Murari Tiyyala
et al.
While Large Language Models (LLMs) can generate fluent and convincing responses, they are not necessarily correct. This is especially apparent in the popular decompose-then-verify factuality evaluation pipeline, where LLMs evaluate generations by decomposing the generations into individual, valid claims. Factuality evaluation is especially important for medical answers, since incorrect medical information could seriously harm the patient. However, existing factuality systems are a poor match for the medical domain, as they are typically only evaluated on objective, entity-centric, formulaic texts such as biographies and historical topics. This differs from condition-dependent, conversational, hypothetical, sentence-structure diverse, and subjective medical answers, which makes decomposition into valid facts challenging. We propose MedScore, a new pipeline to decompose medical answers into condition-aware valid facts and verify against in-domain corpora. Our method extracts up to three times more valid facts than existing methods, reducing hallucination and vague references, and retaining condition-dependency in facts. The resulting factuality score substantially varies by decomposition method, verification corpus, and used backbone LLM, highlighting the importance of customizing each step for reliable factuality evaluation by using our generalizable and modularized pipeline for domain adaptation.
Medical Referring Image Segmentation (MRIS) involves segmenting target regions in medical images based on natural language descriptions. While achieving promising results, recent approaches usually involve complex design of multimodal fusion or multi-stage decoders. In this work, we propose NTP-MRISeg, a novel framework that reformulates MRIS as an autoregressive next-token prediction task over a unified multimodal sequence of tokenized image, text, and mask representations. This formulation streamlines model design by eliminating the need for modality-specific fusion and external segmentation models, supports a unified architecture for end-to-end training. It also enables the use of pretrained tokenizers from emerging large-scale multimodal models, enhancing generalization and adaptability. More importantly, to address challenges under this formulation-such as exposure bias, long-tail token distributions, and fine-grained lesion edges-we propose three novel strategies: (1) a Next-k Token Prediction (NkTP) scheme to reduce cumulative prediction errors, (2) Token-level Contrastive Learning (TCL) to enhance boundary sensitivity and mitigate long-tail distribution effects, and (3) a memory-based Hard Error Token (HET) optimization strategy that emphasizes difficult tokens during training. Extensive experiments on the QaTa-COV19 and MosMedData+ datasets demonstrate that NTP-MRISeg achieves new state-of-the-art performance, offering a streamlined and effective alternative to traditional MRIS pipelines.
Lemar Abdi, Francisco Caetano, Amaan Valiuddin
et al.
In medical imaging, unsupervised out-of-distribution (OOD) detection offers an attractive approach for identifying pathological cases with extremely low incidence rates. In contrast to supervised methods, OOD-based approaches function without labels and are inherently robust to data imbalances. Current generative approaches often rely on likelihood estimation or reconstruction error, but these methods can be computationally expensive, unreliable, and require retraining if the inlier data changes. These limitations hinder their ability to distinguish nominal from anomalous inputs efficiently, consistently, and robustly. We propose a reconstruction-free OOD detection method that leverages the forward diffusion trajectories of a Stein score-based denoising diffusion model (SBDDM). By capturing trajectory curvature via the estimated Stein score, our approach enables accurate anomaly scoring with only five diffusion steps. A single SBDDM pre-trained on a large, semantically aligned medical dataset generalizes effectively across multiple Near-OOD and Far-OOD benchmarks, achieving state-of-the-art performance while drastically reducing computational cost during inference. Compared to existing methods, SBDDM achieves a relative improvement of up to 10.43% and 18.10% for Near-OOD and Far-OOD detection, making it a practical building block for real-time, reliable computer-aided diagnosis.
While Medical Large Language Models (MedLLMs) have demonstrated remarkable potential in clinical tasks, their ethical safety remains insufficiently explored. This paper introduces $\textbf{MedEthicsQA}$, a comprehensive benchmark comprising $\textbf{5,623}$ multiple-choice questions and $\textbf{5,351}$ open-ended questions for evaluation of medical ethics in LLMs. We systematically establish a hierarchical taxonomy integrating global medical ethical standards. The benchmark encompasses widely used medical datasets, authoritative question banks, and scenarios derived from PubMed literature. Rigorous quality control involving multi-stage filtering and multi-faceted expert validation ensures the reliability of the dataset with a low error rate ($2.72\%$). Evaluation of state-of-the-art MedLLMs exhibit declined performance in answering medical ethics questions compared to their foundation counterparts, elucidating the deficiencies of medical ethics alignment. The dataset, registered under CC BY-NC 4.0 license, is available at https://github.com/JianhuiWei7/MedEthicsQA.
Artificial intelligence (AI) is expected to revolutionize the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in a variety of clinical tasks: detecting diabetic retinopathy from images, predicting hospital readmissions, aiding in the discovery of new drugs, etc. AI's progress in medicine, however, has led to concerns regarding the potential effects of this technology upon relationships of trust in clinical practice. In this paper, I will argue that there is merit to these concerns, since AI systems can be relied upon, and are capable of reliability, but cannot be trusted, and are not capable of trustworthiness. Insofar as patients are required to rely upon AI systems for their medical decision-making, there is potential for this to produce a deficit of trust in relationships in clinical practice.
Manual annotation of volumetric medical images, such as magnetic resonance imaging (MRI) and computed tomography (CT), is a labor-intensive and time-consuming process. Recent advancements in foundation models for video object segmentation, such as Segment Anything Model 2 (SAM 2), offer a potential opportunity to significantly speed up the annotation process by manually annotating one or a few slices and then propagating target masks across the entire volume. However, the performance of SAM 2 in this context varies. Our experiments show that relying on a single memory bank and attention module is prone to error propagation, particularly at boundary regions where the target is present in the previous slice but absent in the current one. To address this problem, we propose Short-Long Memory SAM 2 (SLM-SAM 2), a novel architecture that integrates distinct short-term and long-term memory banks with separate attention modules to improve segmentation accuracy. We evaluate SLM-SAM 2 on four public datasets covering organs, bones, and muscles across MRI, CT, and ultrasound videos. We show that the proposed method markedly outperforms the default SAM 2, achieving an average Dice Similarity Coefficient improvement of 0.14 and 0.10 in the scenarios when 5 volumes and 1 volume are available for the initial adaptation, respectively. SLM-SAM 2 also exhibits stronger resistance to over-propagation, reducing the time required to correct propagated masks by 60.575% per volume compared to SAM 2, making a notable step toward more accurate automated annotation of medical images for segmentation model development.
Abstract Background During the COVID-19 pandemic, virtual visiting technologies were rapidly integrated into the care offered by intensive care units (ICUs) in the UK and across the globe. Today, these technologies offer a necessary adjunct to in-person visits for those with ICU access limited by geography, work/caregiving commitments, or frailty. However, few empirical studies explore the ethical issues associated with virtual visiting. This study aimed to explore the anticipated or unanticipated ethical issues raised by using virtual visiting in the ICU, such that healthcare professionals can be informed about how to carry out virtual visits ethically, safely and productively. Methods We used a descriptive exploratory qualitative research approach recruiting a convenience sample of newly-graduated junior doctors facilitating ICU virtual visits in a tertiary academic centre. Eight newly graduated junior doctors, seven female and one male, aged 23–27, participated in semi-structured interviews. We analysed transcripts using an inductive coding approach. Results Five overarching themes emerged. Two of the themes namely, ‘fulfilling a moral instinct to connect families’ and ‘promoting autonomy’, arose from participants’ descriptions of how virtual visits aligned with healthcare standards and practices they considered ethical. Three further themes, ‘preserving dignity and privacy’, ‘managing emotional distress’, and ‘providing equitable access’ to virtual visiting technologies, highlight how virtual visits might exacerbate ethical issues related to family communications. Conclusion Virtual visiting may potentially both ameliorate and exacerbate aspects of ethical healthcare delivery for ICU patients and family members. ICU team members should consider unique ethical considerations related to using virtual visiting. We recommend virtual communications skills training for staff and advocate for the use of easily accessible educational resources for families who wish to visit critically unwell patients remotely.
Abstract Background Symptom checker apps (SCAs) are mobile or online applications for lay people that usually have two main functions: symptom analysis and recommendations. SCAs ask users questions about their symptoms via a chatbot, give a list with possible causes, and provide a recommendation, such as seeing a physician. However, it is unclear whether the actual performance of a SCA corresponds to the users’ experiences. This qualitative study investigates the subjective perspectives of SCA users to close the empirical gap identified in the literature and answers the following main research question: How do individuals (healthy users and patients) experience the usage of SCA, including their attitudes, expectations, motivations, and concerns regarding their SCA use? Methods A qualitative interview study was chosen to clarify the relatively unknown experience of SCA use. Semi-structured qualitative interviews with SCA users were carried out by two researchers in tandem via video call. Qualitative content analysis was selected as methodology for the data analysis. Results Fifteen interviews with SCA users were conducted and seven main categories identified: (1) Attitudes towards findings and recommendations, (2) Communication, (3) Contact with physicians, (4) Expectations (prior to use), (5) Motivations, (6) Risks, and (7) SCA-use for others. Conclusions The aspects identified in the analysis emphasise the specific perspective of SCA users and, at the same time, the immense scope of different experiences. Moreover, the study reveals ethical issues, such as relational aspects, that are often overlooked in debates on mHealth. Both empirical and ethical research is more needed, as the awareness of the subjective experience of those affected is an essential component in the responsible development and implementation of health apps such as SCA. Trial registration German Clinical Trials Register (DRKS): DRKS00022465. 07/08/2020.
Actualmente la inteligencia artificial se encuentra en un punto de desarrollo nunca visto prometiendo grandes beneficios que trascienden en las distintas esferas sociales. Una problemática al respecto es la aparente neutralidad de los algoritmos utilizados en su programación y su impacto a gran escala en relación con la discriminación generada a partir de los sesgos inmersos en ellos, provenientes de sus diseñadores. Esto como resultado de una mirada parcial a la realidad y la persona misma. La solución a la segregación es posible hallarla no solo en las llamadas paridades, que son una respuesta que pretende ompensar errores en la programación y trae como consecuencia desigualdades en oportunidades y privilegios para ciertos grupos, sino en una mirada a la totalidad de la persona.
Mohammad Reza Hosseinzadeh Taher, Michael B. Gotway, Jianming Liang
Human anatomy is the foundation of medical imaging and boasts one striking characteristic: its hierarchy in nature, exhibiting two intrinsic properties: (1) locality: each anatomical structure is morphologically distinct from the others; and (2) compositionality: each anatomical structure is an integrated part of a larger whole. We envision a foundation model for medical imaging that is consciously and purposefully developed upon this foundation to gain the capability of "understanding" human anatomy and to possess the fundamental properties of medical imaging. As our first step in realizing this vision towards foundation models in medical imaging, we devise a novel self-supervised learning (SSL) strategy that exploits the hierarchical nature of human anatomy. Our extensive experiments demonstrate that the SSL pretrained model, derived from our training strategy, not only outperforms state-of-the-art (SOTA) fully/self-supervised baselines but also enhances annotation efficiency, offering potential few-shot segmentation capabilities with performance improvements ranging from 9% to 30% for segmentation tasks compared to SSL baselines. This performance is attributed to the significance of anatomy comprehension via our learning strategy, which encapsulates the intrinsic attributes of anatomical structures-locality and compositionality-within the embedding space, yet overlooked in existing SSL methods. All code and pretrained models are available at https://github.com/JLiangLab/Eden.
Anna Reithmeir, Julia A. Schnabel, Veronika A. Zimmer
Medical image registration aims at identifying the spatial deformation between images of the same anatomical region and is fundamental to image-based diagnostics and therapy. To date, the majority of the deep learning-based registration methods employ regularizers that enforce global spatial smoothness, e.g., the diffusion regularizer. However, such regularizers are not tailored to the data and might not be capable of reflecting the complex underlying deformation. In contrast, physics-inspired regularizers promote physically plausible deformations. One such regularizer is the linear elastic regularizer which models the deformation of elastic material. These regularizers are driven by parameters that define the material's physical properties. For biological tissue, a wide range of estimations of such parameters can be found in the literature and it remains an open challenge to identify suitable parameter values for successful registration. To overcome this problem and to incorporate physical properties into learning-based registration, we propose to use a hypernetwork that learns the effect of the physical parameters of a physics-inspired regularizer on the resulting spatial deformation field. In particular, we adapt the HyperMorph framework to learn the effect of the two elasticity parameters of the linear elastic regularizer. Our approach enables the efficient discovery of suitable, data-specific physical parameters at test time.
Photo by Mika Baumeister on Unsplash
INTORDUCTION
In March of 2022, New Jersey Governor Phil Murphy announced that the state would no longer mandate face masks for students, staff, and visitors at schools and childcare centers. Two-thirds of New Jersey residents already supported this decision.[1] Soon after, Princeton University led the way in learning to live with the virus by making the use of masks optional in most situations. At a time when vaccination rates were already high and Omicron hospitalization rates were falling, the decision to relax mask mandates was the right call.
Yet, Rutgers University has extended its mask mandate for the rest of the academic year, with no stated endpoint. In a university-wide email, Executive Vice President and Chief Operating Officer Antonio Calcado announced:
The university has been clear that the science and data would guide our path forward with respect to the health and safety of our community… Use of appropriate face coverings will still be required in all teaching spaces (classrooms, lecture halls, seminar rooms, etc.), teaching labs, computer labs, buses, libraries, and clinical facilities.[2]
Despite the university’s purported commitment to follow “the science and data,” there has been a noticeable lack of transparency regarding the scientific rationale and official endpoint for this extension of the mask mandate.
Given the same set of scientific data available, these neighboring universities came to opposite conclusions on the need for continued mask mandates. Notably, the Rutgers mask mandate continues to require students to mask in libraries but not in crowded cafeterias. These discrepancies have led to understandable frustration among members of the Rutgers community. In response, the Rutgers student newspaper objects to “the sense of optics” and “the lack of clear communication,” resulting in “confusion,” arguing that the university administration “needs to be more transparent” and “must communicate and explain the policy changes more effectively.”[3] At a time when trust in public health institutions is at an all-time low, Ava Kamb warns that a lack of transparent messaging can reduce public trust even further.[4] Instead, Kamb argues that public health mandates should use the least restrictive means necessary in order to promote health and civil liberties at the same time.
The ethical question is whether university mask mandates should be relaxed. I argue that the use of face masks by healthy individuals has uncertain benefits, which potential harms may outweigh, and should therefore be voluntary.
ANALYSIS
Rutgers intends “the science and data” to guide its path forward. As such, it is worth revisiting the controversial science behind mask mandates. From 2019 to 2020, systematic reviews by the World Health Organization (WHO) and Cochrane Acute Respiratory Infections concluded that the use of face masks by healthy individuals in the community lacks effectiveness in reducing viral transmission based on moderate-quality evidence.[5] Neither study concerned COVID-19 specifically. Since then, the only two randomized controlled trials of face masks published during the pandemic found little to no benefit.[6] Yet, the Centers for Disease Control and Prevention (CDC) cite many observational and modeling studies (based on empirical assumptions) which suggest that community masking is beneficial.[7] These studies support a larger benefit associated with masking, but they use less reliable research methods. Based on these non-randomized data and mechanistic plausibility, WHO’s current position is also supportive of community masking recommendations. But without high-quality evidence, it is difficult to justify a requirement rather than a recommendation.
It may be useful to draw an ethical distinction between a recommendation and a mandate in public health. A public health recommendation does not generally undermine individual autonomy because individuals have the choice to follow the recommendation. I argue that recommendations may be justified by a lower standard of proof or a lesser expected benefit precisely because they do not violate individual autonomy. On the other hand, a public health mandate demands compliance using the threat of penalty. To ethically justify an infringement of autonomy, strong evidence that demonstrates a significant health benefit should support a public health mandate. While the recommendation to use masks in accordance with personal preference may be a reasonable precaution—particularly for vulnerable individuals—the higher standards of evidence and benefit that would ethically justify mask mandates have not been met.
Notwithstanding, one might argue the precautionary principle justifies mask mandates. For example, Chinese CDC Director-General George Gao, medical researcher Trisha Greenhalgh, and others espouse such a view.[8] The precautionary principle holds that it is better to be safe than sorry. In the context of COVID-19, the principle has been used to advocate for public health measures which lack high-quality evidence. Accordingly, it might be thought that it is safer to implement potentially ineffective mask mandates than to risk forgoing a lifesaving benefit. Yet, the precautionary principle is an ill-defined concept that is philosophically problematic. Health economist Jay Bhattacharya and epidemiologist Sunetra Gupta argue that the precautionary principle cuts both ways because a public health mandate without high-quality evidence has both potential benefits and potential harms.[9] If the precautionary principle can justify implementing mask mandates due to the risk of forgoing possible benefit, then it might also be able to justify not implementing mask mandates due to the risk of potential harm caused by the intervention.
It is commonly thought that there is little to lose from the use of face masks, but this is not necessarily true. According to WHO, CDC, and the European Centre for Disease Prevention and Control (ECDC), the harms of face masks may include headaches, difficulty breathing, skin lesions, difficulty communicating, a false sense of security, environmental pollution, impaired learning, delayed psychosocial development, and disadvantages for individuals with cognitive or mental disorders.[10] These include both potential and observed harms drawn from the scientific literature. Yet, the negative side effects of masks remain significantly under-investigated. For example, there is emerging mechanistic evidence that prolonged mask use or reuse increases both inhaled and environmental microplastics, the long-term effects of which are unknown.[11] The harms related to communication, learning, and psychosocial development are particularly problematic for educational institutions, whose mission is to promote these very things. It is, therefore, possible that masks have done more harm than good.
While many observational studies and models support the potential benefits of masks, some interpret these studies to mean that masks clearly work. However, the limited body of randomized data paints a less optimistic picture and cannot be used to rule out an increase in infection from masks.[12] Other types of studies, less reliable research methods, do rule this out and support masking. Bhattacharya and Gupta would argue that it is safer to encourage voluntary, evidence-based interventions than to foist these potential harms upon individuals for the sake of uncertain benefits.
It remains unclear whether and to what extent the use of face masks by healthy individuals in the community influenced COVID-19 mortality. However, it is clear to me that community masking does not meet the higher standard of evidence necessary to justify a mandate and that mask use is associated with potential harm. The already tenuous case for masks continues to weaken with a mixed body of evidence, the availability of effective pharmaceuticals, and widespread natural immunity to COVID-19. If public health should aim for the least restrictive means necessary to promote health while respecting civil liberties, then the extension of burdensome mask mandates which lack high-quality evidence is ethically problematic.
CONCLUSION
Given the current state of COVID-19, a university mask mandate for a low-risk population with high levels of immunity is not justified. In times of fear and uncertainty, higher education institutions ought to make reasoned policy decisions guided by “the science and data.” It would seem that, of the universities that mandated masks, Princeton has emerged as a national leader in mask policy while Rutgers lags behind. Schools across the nation should take note.
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[1] Rutgers University Eagleton Institute of Politics. Two-thirds of New Jerseyans agree with lifting school mask mandate, most comfortable returning to normal; half think NJ has done “just right” on pandemic. Accessed May 14, 2022. https://eagletonpoll.rutgers.edu/wp-content/uploads/2022/03/Rutgers-Eagleton-Poll-COVID-March-7-2022.pdf
[2] Calcado AM. Return to Campus Update – January 31, 2022. Accessed May 14, 2022. https://coronavirus.rutgers.edu/changes-related-to-covid-19-protocols
[3] The Daily Targum. Rutgers’ new mask policies are more than confusing. Accessed May 14, 2022. https://dailytargum.com/article/2022/04/editorial-rutgers-new-mask-policies-are-more-than-confusing
[4] Kamb A. The false choice between public health and civil liberties. Voices in Bioethics 2020;6. doi:10.7916/vib.v6i.6297.
[5] World Health Organization Global Influenza Programme. Non-pharmaceutical public health measures for mitigating the risk and impact of epidemic and pandemic influenza. Geneva: World Health Organization; 2019; Jefferson T, Del Mar CB, Dooley L, et al. Physical interventions to interrupt or reduce the spread of respiratory viruses. Cochrane Database of Systematic Reviews 2020;11(CD006207). doi:10.1002/14651858.CD006207.pub5.
[6] Abaluck J, Kwong LH, Styczynski A, et al. Impact of community masking on COVID-19: A cluster-randomized trial in Bangladesh. Science 2022;375(6577):eabi9069. doi:10.1126/science.abi9069. (intervention reduced symptomatic seroprevalence by 9.5%; 95% confidence interval = [0.82, 1.00].); Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, et al. Effectiveness of adding a mask recommendation to other public health measures to prevent SARS-CoV-2 infection in Danish mask wearers: A randomized controlled trial. Ann Intern Med 2021;174(3):335-343. doi:10.7326/M20-6817. (trial was conducted in a setting where mask wearing was uncommon and the findings were inconclusive; 95% confidence interval = [0.54, 1.23].)
[7] U.S. Centers for Disease Control and Prevention. Science Brief: Community Use of Masks to Control the Spread of SARS-CoV-2. Accessed May 14, 2022. https://www.cdc.gov/coronavirus/2019-ncov/science/science-briefs/masking-science-sars-cov2.html
[8] Zimmerman A. The precautionary principle in mask-wearing: When waiting for explicit scientific evidence is unwise. Voices in Bioethics 2020;6. doi:10.7916/vib.v6i.5896. (supporting the use of masks early in the pandemic arguing that the harms of masking in the short term were unlikely to be severe or to outweigh the benefits.); Greenhalgh T, Schmid MB, Czypionka T, et al. Face masks for the public during the COVID-19 crisis. BMJ 2020;369:m1435. doi:10.1136/bmj.m1435.
[9] Bhattacharya J. On the Catastrophic Misapplication of the Precautionary Principle. Accessed May 14, 2022. https://collateralglobal.org/article/misapplication-of-the-precautionary-principle; Gupta S. A Betrayal of the Precautionary Principle. Accessed May 14, 2022. https://collateralglobal.org/article/a-betrayal-of-the-precautionary-principle
[10] World Health Organization. Mask use in the context of COVID-19: Interim guidance, 1 December 2020. Accessed May 14, 2022. https://apps.who.int/iris/handle/10665/337199; U.S. Centers for Disease Control and Prevention; European Centre for Disease Prevention and Control. Using face masks in the community: First update - Effectiveness in reducing transmission of COVID-19. Accessed May 14, 2022. https://www.ecdc.europa.eu/sites/default/files/documents/covid-19-face-masks-community-first-update.pdf
[11] Li L, Zhao X, Li Z, et al. COVID-19: Performance study of microplastic inhalation risk posed by wearing masks. J Hazard Mater 2021;411:124955. doi:10.1016/j.jhazmat.2020.124955; Ma J, Chen F, Xu H, et al. Face masks as a source of nanoplastics and microplastics in the environment: Quantification, characterization, and potential for bioaccumulation. Environ Pollut 2021;288:117748. doi:10.1016/j.envpol.2021.117748; Chen X, Chen X, Liu Q, et al. Used disposable face masks are significant sources of microplastics to environment. Environ Pollut 2021;285:117485. doi:10.1016/j.envpol.2021.117485.
[12] Bundgaard et al. (inconclusive with a 95% confidence interval = [0.54, 1.23]).
Photo by Mika Baumeister on Unsplash
INTRODUCTION
When the COVID-19 pandemic swept the globe, governments and healthcare systems scrambled to control it. While most of the global public health community agreed that actions against the COVID-19 pandemic needed to be prompt and efficient, there were disagreements on what those actions should be. Some governments opted to adopt a containment strategy while others implemented mitigation measures; each had reasons to support their course of action, whether rooted in governmental structures, scientific findings, beliefs, or ethical and moral values. However, the dramatically different response strategies may have led to disparate results. This divide is furthered when ethical and moral values and cultural norms are added to this equation. In this paper, I will examine China and Korea, two countries that implemented a preventative containment strategy, and the United States of America and the United Kingdom, which adopted mitigation strategies. I will examine the differences in their outcomes and whether there is a “correct” response to pandemics like COVID-19.
l. Response in China and Korea
After its initial discovery in December 2019, COVID-19 rapidly spread beyond China to surrounding countries, including South Korea, Japan, and Singapore. China implemented swift measures drawing on its experience with the SARS outbreak. Measures included lockdowns, contact tracing, testing all individuals exposed to the virus, and consequently enforcing isolation and quarantine provisions.[1] During the early stages, the public health systems and the national government moved to a “health care to all” system to avoid nationwide spread. The government and all sectors of society were mobilized to track, contain, and adapt to the overall state of the epidemic.[2] COVID-19 continued and spread in China during Lunar New Year celebrations when population movement within the country was at its peak. Thus, Wuhan entered lockdown to control the number of infected people leaving the city to contain the virus;[3] even in areas where there were few to no cases, the general population of China voluntarily abided by measures like those implemented in Wuhan. The measures included wearing masks, social distancing, and following stay-at-home orders. Furthermore, healthcare workers from all over the country volunteered to travel to Hubei, where Wuhan is, and assembled several Fangcang shelter hospitals.[4]
Fangcang hospitals were designed based on emergency medical care cabins that were used after two devastating earthquakes in China and served as temporary quarantine housing and hospital facilities.[5] They are mobile, have fast deployment, and can adapt quickly to different environments. At the start of the pandemic, Wuhan converted gymnasiums, convention centers, sports arenas and training centers, factories, and other venues into Fangcang hospitals. Although temporary, these quarantine hospital facilities were equipped with full medical equipment and personnel, allowing for complete medical functions for “treatment, disease monitoring, diagnosis and other clinical tasks.”[6] Teams of psychologists were also assigned to each hospital to provide counseling for patients.[7] Beyond separating those who were infected from the rest of the population and thus having more control over the community spread of the virus, Fangcang hospitals played a vital role in reducing patient density in traditional hospitals and medical centers by expanding treatment capacities.[8]
South Korea reported its first COVID-19 case in January 2020, and, within days, the government activated the Central Disaster and Safety Countermeasures Headquarters.[9] Similar to China, South Korea used existing epidemic protocols and implemented the 3Ts strategy, prioritizing testing, tracing, and treatment.[10] High-capacity screening facilities and working with the private sector to ensure an adequate supply of tests made South Korea’s efforts successful.[11] The South Korean government strictly regulated self-isolation and quarantine. Contact tracing efforts used various data sources, “including credit card transactions and closed-circuit television footage.”[12] The government also placed stringent restrictions on travel, beginning with designated entry lines and questionnaires, but expanding to include temperature checks, testing for all travelers at the border, and a mandatory fourteen-day monitored quarantine for anyone entering the country.[13] The majority of the population responded immediately with compliance, with national weekly movement decreasing by 38 percent between February 24, 2020, and March 1, 2020, compared to the corresponding week the previous month. Schools swiftly closed across the nation, and the entire country transitioned to remote learning until the gradual reopening in May and June 2020.[14]
There was some discontentment within the population, especially with the South Korean government’s practice of publicly announcing the names of individuals who tested positive.[15] Critics of this practice say it is an infringement of patient privacy and can even be viewed as an invitation to public bullying.[16] However, even with some dissatisfaction with government regulations, a survey of 1,200 South Koreans in September 2020 asking people to agree if they were satisfied with the government’s response showed that the overwhelming majority either agreed or strongly agreed (44.08 percent and 19.75 percent, respectively), and less than 20 percent of the respondents either disagreed or strongly disagreed (11.50 percent and 5.08 percent, respectively).[17]
Regulations surrounding isolation and quarantine were strict and applied to those with confirmed cases of COVID-19, anyone who traveled internationally, or individuals suspected to be infected. Individuals were required to use the Self-Quarantine Safety Protection app that tracked location for fourteen days to ensure that quarantine protocols were followed.[18] Case officers monitored the app, and violators not only faced a substantial fine but were also required to wear electronic wristbands that would alert the officers if the individual left the location of their mobile device.[19]
ll. The Western Response: The UK and US
COVID-19 was reported in many Western nations around January 2020. However, unlike South Korea, many countries did not immediately respond to the outbreak with surveillance and containment strategies but had a wait-and-see approach. As the pandemic worsened, they gradually adopted mitigation strategies to combat the disease as it progressed. While the US adopted a combination of containment and mitigation strategies, a concrete response from state and federal governments did not occur until March 2020.[20] Even then, many states did little to address the pandemic. Although equipped with a robust healthcare system, a shortage of ventilators and hospital beds became evident in some localities early on. The US healthcare system failed to acknowledge the pandemic and prepare a coordinated response in time to stop the momentum of the disease.[21] The goal became “flattening the curve” (keeping the number of cases that needed hospital care low enough to avoid overwhelming the hospital system) as it was clear containment would be impossible. Once tests were developed, poor coordination of testing efforts and insufficient resources to test at the necessary scale to provide comprehensive national surveillance of the disease further hindered efforts to contain infected individuals and decelerate its spread.[22] Eventually, regulations and mitigation measures were implemented, including mask mandates, school closures, caps or bans on in-person gatherings, and the closure of non-essential businesses.[23] However, enforcement of these measures proved difficult, and people instigated protests against many of the recommended policies and requirements.
The UK and the US both encountered a shortage of personal protective equipment for healthcare workers.[24] However, a more prominent problem arose from the UK’s initial response to the pandemic. The UK first said COVID-19 was like influenza and therefore did not call for emergency measures to deter its spread.[25] Furthermore, in the first few weeks of the pandemic, the UK government believed herd immunity was the best course of action, stating that most people would have mild symptoms,[26] and the population would become mostly immune to the virus once enough people were infected.[27] In theory, herd immunity was a potentially effective strategy. The public health authorities thought that if the threshold for herd immunity was reached, enough people would have developed protective antibodies against any future infection.[28] However, the risks of COVID-19 were high and the cases “would lead to high rates of hospitalization and need for critical care, straining health service capacity past the breaking point.”[29] Furthermore, while getting COVID-19 would offer some natural immunity against reinfection, reinfection remained a possibility, especially during the early stages of the pandemic when vaccines were unavailable.[30] Later, when vaccines were available, a study showed that an unvaccinated person who contracted the virus was more than twice as likely to become reinfected than a fully vaccinated person.[31]
The UK government also expressed concern for “behavioral fatigue.”[32] It claimed that if restrictions were enforced pre-emptively and prematurely, people might become progressively “uncooperative and less vigilant.”[33] Regarding the concern for “behavioral fatigue,” numerous behavioral scientists stated that they were unconvinced that this reason was enough to hold off implementing restrictions. There was a lack of evidence of this phenomenon, and a group of 681 UK behavioral scientists said in an open letter that “[s]uch evidence is necessary if we are to base a high-risk public health strategy on it.”[34] Fortunately, this strategy only remained under consideration for a short period. After rapid increases in confirmed cases and deaths due to COVID-19, the UK government implemented more strict measures, like city lockdown, school closures, and the closure of non-essential businesses.[35] These restrictions took legal effect on March 26th, 2020 – around two weeks after the first proposal of the “herd immunity” strategy.[36]
lll. Comparing the Two Approaches
The Eastern and Western countries experienced significant outbreaks of COVID-19. However, looking at the mortality rate and new confirmed cases, the differences between the two categories of response to COVID-19 are significant. As of December 31, 2020, the mortality rate per 100,000 population for China and South Korea were 0.3 and 1.8, respectively, and new confirmed cases per day per 100,000 population were 87 and 1,029, respectively. However, the mortality rates per 100,000 in the US and the UK were 107 and 108, respectively, and they had up to 234,133 and 56,029 new confirmed cases every day, respectively.[37] As of July 2022, total deaths in China were 22, 994[38] (population 1.45 billion)[39] and in South Korea 24,794[40] (population 51.36 million)[41] compared to 1,015,093[42] in the US (population 335.03 million)[43] and 182,727[44] in the UK (population 68.62 million).[45]
Further differences can be seen in the varying sectors of society, such as healthcare systems and authority models, political structures, and cultural customs among these countries, which in turn affect the response and control strategies.[46] In the US and the UK, rights-based political structures affected the response, making tracking and surveillance more problematic early on. But Western countries did have strict lockdowns and quarantines. China and South Korea maintained a proactive approach by “identifying and managing cases, tracking and isolating close contacts, and strictly restricting or controlling population movement when feasible and appropriate.”[47] In contrast, the UK implemented nationwide lockdowns early on, and the US restrictions varied among states. Both the UK and the US focused on treating the severe cases and those with underlying conditions rather than proactively preventing new cases from developing in the early pandemic.[48] They did shift gears to mass testing schemes and attempts to slow transmission. By the time they implemented cohesive strategies, COVID-19 was widespread. Due to their slow initial responses, they needed to manage an onslaught of cases while trying to prevent transmission.
lV. Ethical Implications
The “West vs. Rest” culture divide emerges when comparing the COVID-19 response strategies of East Asian countries to those of Western countries. The differences in their strategies further highlight the differences in the prevailing moral values influencing public policy. The preventative stance adopted by many East Asian countries shows a stronger collective identity among citizens. But it also may show more substantial governmental power and less appetite for protest. In contrast, the mostly non-interfering nature of Western governments’ actions shows a reliance on the “autonomous and unanimous responsibility of individuals.”[49] The moral values in the US also may reflect the prioritized position of personal rights and the suspicion of intrusive government policies.
Culturally, the populations of South Korea and China are generally more tolerant of personal data-sharing and monitoring, suggesting there is less concern for autonomy or privacy. However, many people in the US and UK would consider the use of location tracking apps and electronic bracelets to be violations of individual autonomy and privacy.[50] Sectors of the Western world also argue that mandating masking or social distancing imposes on individual autonomy and free will. Mask-wearing was an existing practice in East Asian countries, even without mandates or pandemics. Individuals wear masks for common colds and influenza and do not consider a mask requirement an infringement of their autonomy. Furthermore, whether it is due to the authoritarian nature of the government or not, there is a general tendency toward public compliance and accepting government policies in many East Asian countries,[51] and the lack of public dissent played an important part in making combating COVID-19 easier for countries like China and South Korea.
The lack of initiative from Western nations arguably violates the bioethical principles of beneficence and nonmaleficence.[52] For example, the promotion of the “herd immunity” strategy from the UK government and consequently the government’s inaction, risked the well-being of its citizens. The government failed to avoid the harm that COVID-19 brought. Similarly, by delaying its response until nearly two months after the initial case was reported, the US also violated the principle of non-maleficence. The success seen in South Korea and China during the early pandemic better exemplifies beneficence and nonmaleficence. The strategy of contact tracing and strict containment saved lives.
The consequences of the restrictions varied across the countries as well. Not everyone can afford to self-isolate or quarantine and being required to do so can significantly impact many individuals’ well-being. Furthermore, not everyone’s occupation allows them to work from home and business closures disadvantaged portions of the population disparately. For those who are essential workers, school closures may also burden parents who do not have access to affordable childcare. The stringent restrictions regarding quarantine and self-isolation in East Asian countries also harmed people disparately, raising problems surrounding the principle of justice. However, the speed at which China had COVID-19 contained allowed people there to return to their normal lives quickly. Compared to some Western countries’ waves of lockdown and reinforcement of restrictions, the “zero-COVID” strategy in countries like China showed success, at least during the early stages of the pandemic. The contact tracing and containment was likely financially beneficial. While the pandemic resulted in substantial economic growth downgrades and global recessions, regions like East Asia were estimated to grow by around 0.5 percent. In comparison, the economy in regions like Europe contracted by around 4.7 percent.[53]
CONCLUSION
China arguably had an advantage in combating COVID-19 since the outbreak was relatively concentrated in one region. This allowed early detection of symptoms and quick containment of the virus. Other countries, like the US, had new cases on both coasts early in the pandemic; thus, containment was more challenging than it was in China. However, the delayed and reluctant response from countries like the US and the UK did not benefit the well-being of their populations and proved to put more stress on their healthcare systems. While mass tracking of people is politically contentious, the promptness of actions many East Asian countries employed at the beginning of COVID-19 seemed to be the more effective course of action that best protected the well-being of their citizens.
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