Aging Epidemiology: A Hereditary Mechanics–Inspired Approach to COVID-19 Fatality RatesSource: Journal of Engineering Mechanics:;2024:;Volume ( 150 ):;issue: 007::page 04024041-1DOI: 10.1061/JENMDT.EMENG-7640Publisher: American Society of Civil Engineers
Abstract: The COVID-19 pandemic has evidenced that reliable model-based epidemiological predictions have remained an open challenge, and this concerns in particular the identification of model parameters that may change throughout the course of the pandemic. This aging characteristic of an epidemic is our present focus, by example of predicting fatality trends from infection histories. Regarding the challenge as a mechanobiological problem, we employ a hereditary mechanics-rooted Boltzmann-Volterra-type integro-differential equation, so that the fatality rate is obtained as a time integral over the rate of confirmed cases (i.e., the so-called incidence), multiplied with a kernel depending on evolving, i.e., time-dependent, fatality fractions and time lags between infection and death. This novel convolution approach, including its degeneration to an aging infection-to-death-rate delay rule, is superior to the traditional kinetics approach in as many as 93% of the tested cases associated with 228 countries, territories, and US states. The corresponding country-, territory-, and US state-specific fatality fractions appear as exponentially decaying quantities with characteristic decay times ranging from around 100 days to several years; with a world median of some 480 days, and with 100 to 200 days being typical for Western Europe and several Eastern US states. These parameters show periods of fair stability over one to several hundred days, indicating midterm prediction capabilities of our novel approach.
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contributor author | Niketa Ukaj | |
contributor author | Christian Hellmich | |
contributor author | Stefan Scheiner | |
date accessioned | 2024-12-24T10:25:27Z | |
date available | 2024-12-24T10:25:27Z | |
date copyright | 7/1/2024 12:00:00 AM | |
date issued | 2024 | |
identifier other | JENMDT.EMENG-7640.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4298893 | |
description abstract | The COVID-19 pandemic has evidenced that reliable model-based epidemiological predictions have remained an open challenge, and this concerns in particular the identification of model parameters that may change throughout the course of the pandemic. This aging characteristic of an epidemic is our present focus, by example of predicting fatality trends from infection histories. Regarding the challenge as a mechanobiological problem, we employ a hereditary mechanics-rooted Boltzmann-Volterra-type integro-differential equation, so that the fatality rate is obtained as a time integral over the rate of confirmed cases (i.e., the so-called incidence), multiplied with a kernel depending on evolving, i.e., time-dependent, fatality fractions and time lags between infection and death. This novel convolution approach, including its degeneration to an aging infection-to-death-rate delay rule, is superior to the traditional kinetics approach in as many as 93% of the tested cases associated with 228 countries, territories, and US states. The corresponding country-, territory-, and US state-specific fatality fractions appear as exponentially decaying quantities with characteristic decay times ranging from around 100 days to several years; with a world median of some 480 days, and with 100 to 200 days being typical for Western Europe and several Eastern US states. These parameters show periods of fair stability over one to several hundred days, indicating midterm prediction capabilities of our novel approach. | |
publisher | American Society of Civil Engineers | |
title | Aging Epidemiology: A Hereditary Mechanics–Inspired Approach to COVID-19 Fatality Rates | |
type | Journal Article | |
journal volume | 150 | |
journal issue | 7 | |
journal title | Journal of Engineering Mechanics | |
identifier doi | 10.1061/JENMDT.EMENG-7640 | |
journal fristpage | 04024041-1 | |
journal lastpage | 04024041-17 | |
page | 17 | |
tree | Journal of Engineering Mechanics:;2024:;Volume ( 150 ):;issue: 007 | |
contenttype | Fulltext |