[A Proposed Epidemiologic Risk Threshold for SARS-CoV-2 for Assisting Healthcare Decision-Making].

Sistema de ayuda a la toma de decisiones sanitarias. Propuesta de umbrales de riesgo epidemiológico ante SARS-CoV-2.
Alert levels Covid-19 Incidence rates Modelization Spain

Journal

Archivos de bronconeumologia
ISSN: 1579-2129
Titre abrégé: Arch Bronconeumol
Pays: Spain
ID NLM: 0354720

Informations de publication

Date de publication:
Apr 2021
Historique:
received: 16 11 2020
accepted: 29 12 2020
entrez: 11 10 2021
pubmed: 12 10 2021
medline: 12 10 2021
Statut: ppublish

Résumé

The SARS-CoV-2 pandemic is the most important health challenge observed in 100 years, and since its emergence has generated the highest excess of non-war-related deaths in the western world. Since this disease is highly contagious and 33% of cases are asymptomatic, it is crucial to develop methods to predict its course. We developed a predictive model for Covid-19 infection in Spanish provinces. We applied main components analysis to epidemiological data for Spanish provinces obtained from the National Centre of Epidemiology, based on the epidemiological curve between 24 February and 8 June 2020. Using this method, we classified provinces according to their epidemiological progress (worst, intermediate, and good). We identified 2 components that explained 99% of variability in the 52 epidemiological curves. The first component can be interpreted as the crude incidence rate trend and the second component as the speed of increase or decrease in the incidence rate during the period analysed. We identified 10 provinces in the group with the worst progress and 17 in the intermediate group. The threshold values for the 7-day incidence rate for an alert 1 (intermediate) were 134 cases/100,000 inhabitants, and 167 for alert 2 (high), respectively, showing a high discriminative power between provinces. These alert levels might be useful for deciding which measures may affect population mobility and other public health decisions when considering community transmission of SARS-CoV-2 in a given geographical area. This information would also facilitate intercomparison between healthcare areas and Autonomous Communities.

Identifiants

pubmed: 34629639
doi: 10.1016/j.arbres.2020.12.036
pii: S0300-2896(21)00022-3
pmc: PMC7826127
doi:

Types de publication

English Abstract Journal Article

Langues

spa

Pagination

21-27

Informations de copyright

© 2021 SEPAR. Published by Elsevier España, S.L.U. All rights reserved.

Références

Nat Med. 2020 Jun;26(6):855-860
pubmed: 32322102
Science. 2020 Jul 10;369(6500):
pubmed: 32414780
PLoS One. 2020 Sep 4;15(9):e0238559
pubmed: 32886696

Auteurs

María Isolina Santiago Pérez (MI)

Servicio de Epidemiología, Dirección General de Salud Pública, Consellería de Sanidade, Xunta de Galicia, Santiago de Compostela, España.

Esther López-Vizcaíno (E)

Servicio de Difusión e Información, Instituto Galego de Estadística, Xunta de Galicia, Santiago de Compostela, España.

Alberto Ruano-Ravina (A)

Área de Medicina Preventiva y Salud Pública, Universidad de Santiago de Compostela, Santiago de Compostela, España.
CIBER de Epidemiología y Salud Pública, CIBERESP, Madrid, España.
Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, España.

Mónica Pérez-Ríos (M)

Área de Medicina Preventiva y Salud Pública, Universidad de Santiago de Compostela, Santiago de Compostela, España.
CIBER de Epidemiología y Salud Pública, CIBERESP, Madrid, España.
Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, España.

Classifications MeSH