Evidence map›Paper›PMID 36325837›Full record

ArticleEpidemiology and infection2022

Preceding anti-spike IgG levels predicted risk and severity of COVID-19 during the Omicron-dominant wave in Santa Fe city, Argentina.

Ayelen T Eberhardt, Melina Simoncini, Carlos Piña, Germán Galoppo, Virginia Parachú-Marco, Andrea Racca, Sofía Arce, Evangelina Viotto, Florencia Facelli, Florencia Valli and 15 more

Open access · goldAbstract read
In one paragraph

Article in Epidemiology and infection, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
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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

25 authors at 3 institutions in 1 country.

Ayelen T EberhardtLaboratorio de Ecología de Enfermedades, Instituto de Ciencias Veterinarias del Litoral (ICIVET-Litoral), Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Esperanza, Argentina.
Melina SimonciniCentro de Investigación Científica y de Transferencia Tecnológica a la Producción-Consejo Nacional de Investigaciones Científicas y Técnicas-Provincia de Entre Ríos-Universidad Autónoma de Entre Ríos, Diamante, Argentina.
Carlos PiñaCentro de Investigación Científica y de Transferencia Tecnológica a la Producción-Consejo Nacional de Investigaciones Científicas y Técnicas-Provincia de Entre Ríos-Universidad Autónoma de Entre Ríos, Diamante, Argentina.
Germán GaloppoLaboratorio de Ecofisiopatología - Instituto de Salud y Ambiente del Litoral (ISAL) Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Santa Fe, Argentina.
Virginia Parachú-MarcoLaboratorio de Ecología Molecular Aplicada, Instituto de Ciencias Veterinarias del Litoral-Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Esperanza, Argentina.
Andrea RaccaLaboratorio de Ecología de Enfermedades, Instituto de Ciencias Veterinarias del Litoral (ICIVET-Litoral), Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Esperanza, Argentina.
Sofía ArceLaboratorio de Ecología de Enfermedades, Instituto de Ciencias Veterinarias del Litoral (ICIVET-Litoral), Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Esperanza, Argentina.
Evangelina ViottoCentro de Investigación Científica y de Transferencia Tecnológica a la Producción-Consejo Nacional de Investigaciones Científicas y Técnicas-Provincia de Entre Ríos-Universidad Autónoma de Entre Ríos, Diamante, Argentina.
Florencia FacelliLaboratorio de Ecología de Enfermedades, Instituto de Ciencias Veterinarias del Litoral (ICIVET-Litoral), Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Esperanza, Argentina.
Florencia ValliCentro de Investigación Científica y de Transferencia Tecnológica a la Producción-Consejo Nacional de Investigaciones Científicas y Técnicas-Provincia de Entre Ríos-Universidad Autónoma de Entre Ríos, Diamante, Argentina.
Cecilia BottoFacultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral (FBCB-UNL), Santa Fe, Argentina.
Leonardo ScarpaCentro de Investigación Científica y de Transferencia Tecnológica a la Producción-Consejo Nacional de Investigaciones Científicas y Técnicas-Provincia de Entre Ríos-Universidad Autónoma de Entre Ríos, Diamante, Argentina.
Celina JungesLaboratorio de Ecología de Enfermedades, Instituto de Ciencias Veterinarias del Litoral (ICIVET-Litoral), Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Esperanza, Argentina.
Cintia PalavecinoLaboratorio de Ecología de Enfermedades, Instituto de Ciencias Veterinarias del Litoral (ICIVET-Litoral), Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Esperanza, Argentina.
Camila BeccariaFacultad de Ciencias Veterinarias, Universidad Nacional del Litoral, Esperanza, Santa Fe, Argentina.
Diego SklarInstituto de Matemáticas Aplicadas del Litoral (IMAL), Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Santa Fe, Argentina.
Graciela MingoInstituto de Estudios Sociales (INES), Universidad Nacional de Entre Ríos-Consejo Nacional de Investigaciones Científicas y Técnicas (UNER-CONICET), Paraná, Argentina.
Alicia GenoletInstituto de Estudios Sociales (INES), Universidad Nacional de Entre Ríos-Consejo Nacional de Investigaciones Científicas y Técnicas (UNER-CONICET), Paraná, Argentina.
Mónica Muñoz de ToroLaboratorio de Ecofisiopatología - Instituto de Salud y Ambiente del Litoral (ISAL) Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Santa Fe, Argentina.
Hugo AimarInstituto de Matemáticas Aplicadas del Litoral (IMAL), Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Santa Fe, Argentina.
Verónica MarignacCentro de Investigación Científica y de Transferencia Tecnológica a la Producción-Consejo Nacional de Investigaciones Científicas y Técnicas-Provincia de Entre Ríos-Universidad Autónoma de Entre Ríos, Diamante, Argentina.
Juan Carlos BossioInstituto Nacional de Enfermedades Respiratorias 'Dr Emilio Coni', Santa Fe, Argentina.
Gustavo ArmandoInstituto Nacional de Enfermedades Respiratorias 'Dr Emilio Coni', Santa Fe, Argentina.
Hugo FernándezInstituto Nacional de Enfermedades Respiratorias 'Dr Emilio Coni', Santa Fe, Argentina.
Pablo M BeldomenicoLaboratorio de Ecología de Enfermedades, Instituto de Ciencias Veterinarias del Litoral (ICIVET-Litoral), Universidad Nacional del Litoral - Consejo Nacional de Investigaciones Científicas y Técnicas (UNL-CONICET), Esperanza, Argentina.ORCID 0000-0001-5039-8975
Consejo Nacional de Investigaciones Científicas y Técnicas · ARAdministración Nacional de Laboratorios e Institutos de Salud · ARUniversidad Nacional del Litoral · AR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 Omicron variant has increased infectivity and immune escape compared with previous variants, and caused the surge of massive COVID-19 waves globally. Despite a vast majority (~90%) of the population of Santa Fe city, Argentina had been vaccinated and/or had been infected by SARS-CoV-2 when Omicron emerged, the epidemic wave that followed its arrival was by far the largest one experienced in the city. A serosurvey conducted prior to the arrival of Omicron allowed to assess the acquired humoral defences preceding the wave and to conduct a longitudinal study to provide individual-level real-world data linking antibody levels and protection against COVID-19 during the wave. A very large proportion of 1455 sampled individuals had immunological memory against COVID-19 at the arrival of Omicron (almost 90%), and about half (48.9%) had high anti-spike immunoglobulin G levels (>200 UI/ml). However, the antibody titres varied greatly among the participants, and such variability depended mainly on the vaccine platform received, on having had COVID-19 previously and on the number of days elapsed since last antigen exposure (vaccine shot or natural infection). A follow-up of 514 participants provided real-world evidence of antibody-mediated protection against COVID-19 during a period of high risk of exposure to an immune-escaping highly transmissible variant. Pre-wave antibody titres were strongly negatively associated with COVID-19 incidence and severity of symptoms during the wave. Also, receiving a vaccine shot during the follow-up period reduced the COVID-19 risk drastically (15-fold). These results highlight the importance of maintaining high defences through vaccination at times of high risk of exposure to immune-escaping variants.

Indexed as

COVID-19ArgentinaHumansImmunoglobulin GLongitudinal StudiesSARS-CoV-2Immunoglobulin GAntibody titredisease severityhumoral defencesinfection risklongitudinal studypre-exposureSARS-CoV-2

Identifiers

PMID36325837
PMCPMC9947048
OpenAlexW4308053961

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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.