Argumenta – Journal of Analytic Philosophy

I present and analyze the case of COVID-19 modeling at the Public Health Agency of Sweden (FoHM) between February 2020 and May 2021. The analysis casts the case as a decision problem: mod­elers choose from a strategically prepared menu that model which they have reasons to believe will best serve their current purpose. Specifically, I argue that the model choice at FoHM concerned a trade-off between model-target similarity and model simplicity. Five reasons for choosing to engage in such a trade-off are discussed: lack of information, avoiding overfitting, avoiding fuzzy…

In the understanding and prediction of a pandemic phenomenon, epidemiology is obviously the dedicated discipline. However, epidemiological models look at what we might call the proximate causes of the pandemic. On the other hand, the ultimate causes, those of an ecological, evolutionary, and socio-economic nature, are often too simplified or reduced to “minor” variables in epidemiological models. In this article, in dealing with a pandemic, we want to support the need to extend the study and design of responses to the ultimate causes and the disciplines that investigate them, with…

As the COVID-19 pandemic has demonstrated, barriers to vaccination uptake are heterogeneous and vary according to the local context. We argue that a more systematic consideration of local social and behavioural mechanisms could improve the development, assessment and refinement of vaccination uptake interventions. The EBM+ approach to evidence appraisal, which is a development of a recent line of work on the epistemology of causality, provides a means to evaluate mechanistic studies and their role in assessing the effectiveness of an intervention. We argue that an EBM+ methodology offers several potential…

Never as with the present pandemics, numbers and the attendant activities of measuring and modelling have taken centre-stage. Yet these numbers, often delivered by academicians and media alike with extraordinary precision, rely on a rich repertoire of assumptions, including forms of bias, that can significantly skew both the numbers per se and the trust we repose in them. We discuss the issue in relation to a particular case relative to the numbers on excess mortality during the first wave of the Covid-19 pandemic in Italy. We conclude with some considerations…

This paper is inspired by a thesis on “immune capital” by Kathryn Olivarius. We suggest that the biological capital, which immunity capital is part of, should be considered as an additional component of the life-course experience of individuals, together with the traditional Bourdieu’s social, economic and cultural capitals that drive their lives. Building upon this concept, we consider the relationships between science, society and policy-making in the course of the pandemic. We suggest that we need to ‘reframe problems so that their ethical dimensions are brought to light’ (Jasanoff), with…

In this paper, I argue that evidence of biological and socio-behavioural mechanisms can contribute to the management of Covid-19. I discuss two examples that show how scientists are using different forms of evidence, among which mechanistic evidence, to answer questions about the efficacy of vaccines against Covid-19 and the effectiveness of vaccination interventions in different contexts. In the first example I claim that, due to the fast pace of the pandemic, mechanistic reasoning and evidence of biological mechanisms play an important role in the study of vaccines’ efficacy and the…

In this paper, we analyse some of the challenges that pharmacovigilance, the science of detecting and assessing possible adverse reactions from medical interventions, is facing during the COVID-19 pandemic. In particular, we consider the issue of increased uncertainty of the evidence and the issue of dealing with an unprecedented amount of data. After presenting the technical advances implemented in response to these two challenges, we offer some conceptual reflections around such practical changes. We argue that the COVID-19 emergency represents a chance to push forward critical thinking in the field…

Modelling is a precious source of information in science. With models, we can simplify an otherwise messy reality in order to understand the fundamental driving forces of a system, like an epidemic, and we can try to predict the course of events in complex scenarios where there is a great degree of uncertainty. In short, models can be used to explain and predict phenomena. Yet models interact with expert opinions in two fundamental ways. They are sometimes in competition with expert opinion, and they are sometimes heavily dependent, for their…

One of the many peculiar phenomena that the Covid-19 pandemic has brought about is the engagement of non-scientists with specific questions surrounding the interpretation of epidemiological data and models. Many of them have even begun to get involved in the collection, analysis, and presentation of the data themselves. A reason for this might be that the insights that science can provide in a situation of crisis are often inconclusive or preliminary, motivating many people to look for the answers to pressing questions themselves. Moreover, public engagement is facilitated by the…

Unsurprisingly, science has been conferred growing expectations in the context of the COVID-19 pandemic. Accordingly, the issue of dissemination and popularization of scientific outcomes has come to the fore. The article describes the main features of the so-called dominant view in popular science, which is claimed to be implicitly connected to scientism, a stance identifying science as the most (if not the only) reliable source of legitimate knowledge. Scientism’s implicit philosophical roots are argued to lie in naturalism and a trivialized neopositivist concept of science, which underscores the supposed unity…