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

Miguel Sánchez-Romero, Vanessa Di Lego, Alexia Fürnkranz-Prskawetz and Bernardo Lanza Queiroz

No 05/2020, ECON WPS - Working Papers in Economic Theory and Policy from TU Wien, Institute of Statistics and Mathematical Methods in Economics, Economics Research Unit

Abstract: 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 (c) 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.

Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/218732/1/1698672055.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:tuweco:052020

Access Statistics for this paper

More papers in ECON WPS - Working Papers in Economic Theory and Policy from TU Wien, Institute of Statistics and Mathematical Methods in Economics, Economics Research Unit Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().