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  1. Etiological Explanations: Illness Causation Theory.Olaf Dammann - 2020 - Boca Raton, FL, USA: CRC Press.
    Theory of illness causation is an important issue in all biomedical sciences, and solid etiological explanations are needed in order to develop therapeutic approaches in medicine and preventive interventions in public health. Until now, the literature about the theoretical underpinnings of illness causation research has been scarce and fragmented, and lacking a convenient summary. This interdisciplinary book provides a convenient and accessible distillation of the current status of research into this developing field, and adds a personal flavor to the discussion (...)
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  • A pluralistic and socially responsible philosophy of epidemiology field should actively engage with social determinants of health and health disparities.Sean A. Valles - 2019 - Synthese 198 (Suppl 10):2589-2611.
    Philosophy of epidemiology has recently emerged as a distinct branch of philosophy. The field will surely benefit from pluralism, reflected in the broad range of topics and perspectives in this special issue. Here, I argue that a healthy pluralistic field of philosophy of epidemiology has social responsibilities that require the field as a whole to engage actively with research on social determinants of health and health disparities. Practicing epidemiologists and the broader community of public health scientists have gradually acknowledged that (...)
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  • Evidence Mapping to Justify Health Interventions.Olaf Dammann - 2021 - Perspectives in Biology and Medicine 64 (2):155-172.
    In order to support health interventions, biomedical and population health researchers need to collect solid evidence. This article asks what type of evidence this should be and expands on previous work that focused on etiological explanations, or causal-mechanical explanations of why and how illness occurs. The article proposes adding predictive evidence to the explanatory evidence, in order to form a joint evidence set, or JES = [A,B,C,D], which consists of four different types of evidence: association [A], biology [B], confirmation [C], (...)
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  • Agent-Based Models as Etio-Prognostic Explanations.Olaf Dammann - 2021 - Argumenta 7 (1):19-38.
    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 discussion, I conclude that while ABMs cannot help much with causal (...)
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