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Agent-Based Models as Etio-Prognostic Explanations [Special Issue]

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Agent-based models (ABMs) are one type of simulation model used in the context of the COVID-19 pandemic. In contrast to equation-based models, ABMs are algorithms that use individual agents and attribute changing characteristics to each one, multiple times during multiple iterations over time. This paper focuses on three philosophical aspects of ABMs as models of causal mechanisms, as generators of emergent phenomena, and as providers of explanation. Based on my…

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KISSing in the Time of COVID-19: Some Lessons for Model Choice [Special Issue]

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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…

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Modeling Pandemic: Proximate and Ultimate Causes [Special Issue]

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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…

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Vaccination Uptake Interventions: An EBM+ Approach [Special Issue]

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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…

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The Strange Numbers of Covid-19 [Special Issue]

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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…

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The Immunity Capital [Special Issue]

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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…

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Making Best Use of the Available Evidence: Mechanistic Evidence and the Management of the Covid-19 Pandemic [Special Issue]

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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…

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Monitoring the Safety of Medicines and Vaccines in Times of Pandemic: Practical, Conceptual, and Ethical Challenges in Pharmacovigilance [Special Issue]

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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…

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Models and Experts: The Contribution of Expertise to Epidemic and Pandemic Modelling [Special Issue]

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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…