We argue that the health sciences make causal claims on the basis of evidence both of physical mechanisms, and of probabilistic dependencies. Consequently, an analysis of causality solely in terms of physical mechanisms or solely in terms of probabilistic relationships, does not do justice to the causal claims of these sciences. Yet there seems to be a single relation of cause in these sciences - pluralism about causality will not do either. Instead, we maintain, the health sciences require a theory (...) of causality that unifies its mechanistic and probabilistic aspects. We argue that the epistemic theory of causality provides the required unification. (shrink)

Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the limits (...) of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum. (shrink)

COVID-19 presents many challenges, both clinical and philosophical. In this paper we discuss a major lacuna that COVID-19 revealed in our philosophy and understanding of medicine. Whereas we have some understanding of how physician-scientists interrogate the world to learn more about medicine, we do not understand the epistemological costs and benefits of the various ways clinicians acquire new knowledge in their fields. We will also identify reasons this topic is important both when the world is facing a pandemic and when (...) it is not. (shrink)

In bioethics vaccine refusal is often discussed as an instance of free riding on the herd immunity of an infectious disease. However, the social science of vaccine refusal suggests that the reasoning behind refusal to vaccinate more often stems from previous negative experiences in healthcare practice as well as deeply felt distrust of healthcare institutions. Moreover, vaccine refusal often acts like an exit mechanism. Whilst free riding is often met with sanctions, exit, according to Albert Hirschman’s theory of exit and (...) voice is most efficiently met by addressing concerns and increasing the quality and number of feedback channels. If the legitimate grievances responsible for vaccine refusal are not heard or addressed by healthcare policy, further polarization of attitudes to vaccines is likely to ensue. Thus, there is a need in the bioethics of vaccine refusal to understand the diverse ethical questions of this inflammable issue in addition to those of individual responsibility to vaccinate. (shrink)

Throughout the Covid-19 pandemic, people have been eager to learn what factors, and especially what public health policies, cause infection rates to wax and wane. But figuring out conclusively what causes what is difficult in complex systems with nonlinear dynamics, such as pandemics. We review some of the challenges that scientists have faced in answering quantitative causal questions during the Covid-19 pandemic, and suggest that these challenges are a reason to augment the moral dimension of conversations about causal inference. We (...) take a lesson from Martha Nussbaum—who cautions us not to think we have just one question on our hands when we have at least two—and apply it to modeling for causal inference in the context of cost-benefit analysis. (shrink)

What kind of epidemiological modeling works well? This is determined by the nature of the target: the relevant causal relations are unstable across contexts. I look at two influential examples of modeling from the Covid pandemic. The first is the paper from Imperial College London, which, in March 2020, was influential in persuading the UK government to impose a lockdown. Because it assumes stability, this first example of modeling fails. A different modeling strategy is required, one less ambitious but more (...) effective. This is illustrated by a second paper from Imperial College London, which, in December 2020, first estimated the transmissibility of the Alpha variant. (shrink)

How physicians approach patients and the problems they present is much influenced by the conceptual models around which their knowledge is organized. In this paper the implications of the biopsychosocial model for the study and care of a patient with an acute myocardial infarction are presented and contrasted with approaches used by adherents of the more traditional biomedical model. CiteULike Connotea Del.icio.us What's this?

This paper aims at explicating the role of the connections and interactions between health, well being and beauty. The primary goal of all medical approaches, including the classic biomedical and humanistic or humane approaches, is to restore or create health, whereby medical approaches that include prevention go beyond the mere restoration of health to include the preservation of health. Equating well-being and thus health with a largely self-determined and joyful life, then not only does a healthy life become a beautiful (...) life, a beautiful life also becomes a healthy life! By bringing Beauty into the health discourse, we are entering the field of aesthetics in general and social aesthetics in particular. As the beautiful is not just a decorative element of life but a genuine source of human strength, it gives us the strength and power we need to implement and achieve all that we then experience as “well-being” and that is called a healthy life. Therefore a further development of a human-based medicine is needed, a medicine that focuses not on a disease construct but which places a human being as a whole, with all his potential and limitations at the heart of diagnostic and therapeutic efforts. The noblest therapeutic goal of this kind of medicine can only be the restoration or preservation of a comprehensive state of health in the sense of complete physical, mental and social well-being, in the sense of opening up the possibility for a mostly autonomous and joyful life. (shrink)

COVID-19 epidemic models raise important questions for science and philosophy of science. Here I provide a brief preliminary exploration of three: what kinds of predictions do epidemic models make, are they causal models, and how do different kinds of epidemic models differ in terms of what they represent?