Modelling the new “social”: the evolution of risk assessments and mathematical modelling during the “first wave” of the pandemic
Paganopoulos, Michelangelo (2023) Modelling the new “social”: the evolution of risk assessments and mathematical modelling during the “first wave” of the pandemic. In: Abram, Simone, Lambert, Helen and Robinson, Jude, (eds.) How to Live Through a Pandemic. ASA Monographs - Association of Social Anthropologists . Routledge, London, pp. 63-88. ISBN 978-1003359371 (doi:10.4324/9781003359371-4)
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Abstract
This chapter offers an overview of the articles, updates, and pre-prints deposited in the London School of Hygiene and Tropical Medicine's Open Access repository during the “first wave” of the pandemic. It investigates the hypothesis that stochastic modelling is rapidly evolving alongside the evolution of the virus in terms of representing risk in public as the new “normal”. The chapter argues that this and future pandemics will require the continuous development of a combination of hi-tech tools and interactive technologies that allow for multiple positioning (“super-positioning”) and deep learning non-linear digital visualizations, live feedback, and interactive online databases that give access to communities, to achieve prompt timing for the accurate prediction and visualization of the dynamics of the virus on the ground. During the early stages of the Covid-19 outbreak, mathematical risk models estimated the case fatality ratio by following logistic curve-fitting models that were then presentable to and understood by the public.
| Item Type: | Book Section |
|---|---|
| Uncontrolled Keywords: | risk assessments, mathematical modelling, stochastic modelling, risk society, infodemics, Covid-19 |
| Subjects: | H Social Sciences > H Social Sciences (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QR Microbiology > QR355 Virology |
| Faculty / School / Research Centre / Research Group: | Information & Library Services |
| Last Modified: | 13 Mar 2026 15:05 |
| URI: | https://gala.gre.ac.uk/id/eprint/52656 |
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