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Robust estimation of diagnostic rate and real incidence of COVID-19 for European policymakers.

Authors :
Martí Català
David Pino
Miquel Marchena
Pablo Palacios
Tomás Urdiales
Pere-Joan Cardona
Sergio Alonso
David López-Codina
Clara Prats
Enrique Alvarez-Lacalle
Source :
PLoS ONE, Vol 16, Iss 1, p e0243701 (2021)
Publication Year :
2021
Publisher :
Public Library of Science (PLoS), 2021.

Abstract

Policymakers need clear, fast assessment of the real spread of the COVID-19 epidemic in each of their respective countries. Standard measures of the situation provided by the governments include reported positive cases and total deaths. While total deaths indicate immediately that countries like Italy and Spain had the worst situation as of mid-April, 2020, reported cases alone do not provide a complete picture of the situation. Different countries diagnose differently and present very distinctive reported case fatality ratios. Similar levels of reported incidence and mortality might hide a very different underlying pictures. Here we present a straightforward and robust estimation of the diagnostic rate in each European country. From that estimation we obtain a uniform, unbiased incidence of the epidemic. The method to obtain the diagnostic rate is transparent and empirical. The key assumption of the method is that the infection fatality ratio of COVID-19 in Europe is not strongly country-dependent. We show that this number is not expected to be biased due to demography nor to the way total deaths are reported. The estimation protocol is dynamic, and it has been yielding converging numbers for diagnostic rates in all European countries as from mid-April, 2020. Using this diagnostic rate, policy makers can obtain Effective Potential Growth updated every day, providing an unbiased assessment of the countries at greater risk of experiencing an uncontrolled situation. The method developed has been and will be used to track possible improvements in the diagnostic rate in European countries as the epidemic evolves.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
16
Issue :
1
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.7763205bb874d2c85c4ae3a4bd50d41
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0243701