Evidence map›Paper›PMID 36543873›Full record

ArticleScientific reports2022

Evolution of the lethality due to SARS-CoV-2 in Spain according to age group and sex.

Pedro Saavedra, Angelo Santana, Alejandro Peñate, Carol Herrera, José-Miguel Pacheco

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 50% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Pedro Saavedra *Department of Mathematics, University of Las Palmas de Gran Canaria, 35017, Las Palmas de Gran Canaria, Spain.
Angelo Santana *Department of Mathematics, University of Las Palmas de Gran Canaria, 35017, Las Palmas de Gran Canaria, Spain. angelo.santana@ulpgc.es.
Alejandro Peñate *Faculty of Health Sciences, University of Las Palmas de Gran Canaria, 35016, Las Palmas de Gran Canaria, Spain.
Carol Herrera *Faculty of Health Sciences, University of Las Palmas de Gran Canaria, 35016, Las Palmas de Gran Canaria, Spain.
José-Miguel Pacheco *Department of Mathematics, University of Las Palmas de Gran Canaria, 35017, Las Palmas de Gran Canaria, Spain.
Universidad de Las Palmas de Gran Canaria · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of SARS-CoV-2 in China in December 2019 has posed a major challenge to health systems in all countries around the world. One of the most relevant epidemiological measures to consider during the course of a pandemic is the proportion of cases that eventually die from the disease (case fatality ratio, CFR). Monitoring the evolution of this indicator is of paramount importance because it allows for the assessment of both variations in the lethality of the virus and the effectiveness of the control measures implemented by health authorities. One of the problems with estimating the CFR in practice is that the available data only show daily or weekly counts of new cases and deaths; there is no information on when each deceased patient was infected and therefore it is not possible to know exactly how many cases there were at the time the patient became infected. Various approaches have been proposed for calculating the CFR by correcting for the time lag between infection and death. In this paper, we present a novel methodology to perform a non-parametric estimation of the evolution of the CFR by initially identifying an optimal time lag between infections and deaths. The goodness of this procedure is assessed by means of a simulation study and the method is applied to the estimation of the CFR in Spain in the period from July 2020 to March 2022.

Indexed as

COVID-19SARS-CoV-2ChinaHumansPandemicsSpain

Identifiers

PMID36543873
PMCPMC9768406
OpenAlexW4312070359

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.