How many lives can be saved? A global view on the impact of testing, herd immunity and demographics on COVID-19 fatality rates

Autorinnen und Autoren Miguel Sanchez-Romero, Vanessa di Lego, Alexia Prskawetz, Bernardo L Queiroz
Institution(en) ÖAW
Zeitpunkt(e)/Zeitraum der Erhebung(en)
Art der Stichprobe und Benennung der Personengruppe(n) und Anzahl

Fragestellung(en) der Befragung

In this work, we assess the global impact of COVID-19 showing how demographic factors, testing policies and herd immunity are key for saving lives. We extend a standard epidemiological SEIR model in order to: (a) identify the role of demographics (population size and population age distribution) on COVID-19 fatality rates; (b) quantify the maximum number of lives that can be saved according to different testing strategies, different levels of herd immunity, and specific population characteristics; and (d) infer from the observed case fatality rates (CFR) what the true fatality rate might be. Different from previous SEIR model extensions, we implement a Bayesian Melding method in our calibration strategy which enables us to account for data limitation on the total number of deaths. We
derive a distribution of the set of parameters that best replicate the observed evolution of deaths by using information from both the model and the data. (ÖAW: VID)



Diese Information wurde am 16. April 2021 aus dem Repositorium IHS entnommen.

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