Interpreting, analysing and modelling COVID-19 mortality data

Didier Sornette, Euan Mearns, Michael Schatz, Ke Wu and Didier Darcet
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Didier Sornette: ETH Zürich - Department of Management, Technology, and Economics (D-MTEC); Swiss Finance Institute
Euan Mearns: ETH Zürich - Department of Management, Technology, and Economics (D-MTEC)
Michael Schatz: ETH Zürich
Ke Wu: Southern University of Science and Technology; ETH Zurich - Department of Management, Technology, and Economics (D-MTEC)
Didier Darcet: Insight Research LLC

No 20-27, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We present results on the mortality statistics of the COVID-19 epidemics in a number of countries. Our data analysis suggests classifying countries in four groups, 1) Western countries, 2) East Block and developed South East Asian countries, 3) Northern Hemisphere developing countries and 4) Southern Hemisphere countries. Comparing the number of deaths per mil-lion inhabitants, a pattern emerges in which the Western countries exhibit the largest mortality. Furthermore, comparing the running cumulative death tolls as the same level of outbreak progress in different countries reveals several subgroups within the Western countries and further emphasises the difference between the four groups. Analysing the relationship between deaths per million and life expectancy in different countries, taken as a proxy of the preponderance of elderly people in the population, a main reason behind the relatively more severe COVID-19 epidemics in the Western countries countries is found to be their larger population of elderly people, with exceptions such as Norway, Canada and Japan, for which other factors seem to dominate. Our comparison between countries at the same level of outbreak progress allows us to identify and quantify a measure of efficiency of the level of stringency of confinement measures. We find that increasing the stringency from 20 to 60 decreases the death count by about 50 lives per million. Finally, we perform logistic equation analyses of confirmed cases and deaths as a means of tracking the maturity of outbreaks and estimating ultimate mortality, using four different models to identify model error and robustness of results. This quantitative analysis allows us to assess the outbreak progress in different countries, differentiating between those that are at a quite advanced stage and close to the end of the epidemics from those that are still in the middle of it. We also report large differences in our forecasts for the distribution of final death numbers per million with Austria and Germany exhibiting a factor at least three fewer deaths per millions than France of Italy. This raises many questions in terms of organisation, preparedness, governance structure, and so on.

Keywords: COVID-19 epidemics; mortality; life expectancy; stringency of confinement measures; logistic equation; outbreak progress (search for similar items in EconPapers)
JEL-codes: I12 I18 I30 M14 Q50 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2020-04
New Economics Papers: this item is included in nep-age and nep-sea
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2027

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