Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jan 14, 2023
Date Accepted: Dec 24, 2023
Digital crisis technologies as ‘evidence machines’: The case of pandemic simulation models during COVID-19.
ABSTRACT
Background:
* Reviewer AI recommended to drop the background section what has been done in the latest version of the article *
Objective:
This article focuses on pandemic simulation models as algorithmic governance tools that without doubt played a central role in political decision-making during the Covid-19 crisis. For an assessment of the social implications of pandemic simulation models, the premises of data collection, sorting and evaluation must be disclosed and reflected upon. Consequently, it must be a matter of revealing the social construction principles of digital health technologies and examining them for their effects with regard to ethical, social, and political issues.
Methods:
The contribution starts with a systematization of different simulation approaches to create a typology of pandemic simulation models. Based on this, various properties, functions, and challenges of these simulation models are revealed and discussed in greater detail from a socio-scientific point of view.
Results:
The typology of pandemic simulation methods reveals the diversity of model-driven handling of pandemic threats. However, it is reasonable to assume that the use of simulation models could increasingly shift towards agent-based or AI models in the future, thus promoting the logic of algorithmic decision making (ADM) in responses to public health crises. As ADM aims more at predicting future dynamics than statistical practices of assessing pandemic events, the article discusses this development in detail, resulting in an operationalized overview of the key social and ethical issues related to pandemic crisis technologies.
Conclusions:
The article identifies three major recommendations for the future of pandemic crisis technologies.
Citation
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Copyright
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