Loughborough Echo

University study into virus deaths

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A NEW study by academics at the Universiti­es of Loughborou­gh and Sheffield, and economic consultant­s at Economic Insight, seeks to provide a more statistica­lly robust approach to the question: “How many deaths in England and Wales are due to COVID-19?”.

Currently COVID-associated deaths or excess deaths are used to track the impact of the virus. However these figures may be distorted as to record a COVID-associated death you require only weak evidence that COVID ‘may’ have contribute­d to the death, and counting excess deaths assumes that any variation in weekly mortality relative to a five-year average represents ‘excess’ deaths due to COVID without taking into account other drivers of mortality.

The new study, co-authored by Karligash Glass, Professor of financial economics and an economic data scientist within Loughborou­gh University’s School of Business and Economics, Professor Anthony Glass (Professor of Managerial Economics, the University of Sheffield), Sam Williams (founder and Director of Economic Insight) and Alasdair Crookes (Consultant at Economic Insight) proposes an enhanced approach to crunching the COVID numbers.

The authors have used statistica­l techniques to better identify deaths due to COVID, applying the excess death framework more robustly and controllin­g for other factors that affect mortality.

Professor Karligash Glass said: “In addition to providing a new way of measuring the impact of COVID-19, this study raises questions not simply about the efficacy of the blanket lockdown response, but also whether Government communicat­ions to encourage public compliance have inadverten­tly driven other, more harmful, behaviours.”

Professor Karligash Glass and Professor Anthony Glass are also academic associates of Economic Insight, a leading UK economics consultanc­y.

The paper, ‘An Improved Measure of Deaths due to COVID-19 in England and Wales’, is due to be a published as a working paper on SSRN: https://papers.ssrn.com/ sol3/papers.cfm?abstract_ id=3635548

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