Evidence map›Paper›PMID 36650230›Full record

ArticleScientific reports2023

Using survey data to estimate the impact of the omicron variant on vaccine efficacy against COVID-19 infection.

Jesús Rufino, Carlos Baquero, Davide Frey, Christin A Glorioso, Antonio Ortega, Nina Reščič, Julian Charles Roberts, Rosa E Lillo, Raquel Menezes, Jaya Prakash Champati and 1 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
1.6field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Relative Virulence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Among Vaccinated and Unvaccinated Individuals Hospitalized With SARS-CoV-2.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Article
  6. Observational
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 9 institutions in 5 countries.

Jesús RufinoCoronaSurveys Team, Madrid, Spain.
Carlos BaqueroCoronaSurveys Team, Madrid, Spain.
Davide FreyCoronaSurveys Team, Madrid, Spain.
Christin A GloriosoCoronaSurveys Team, Madrid, Spain.
Antonio OrtegaCoronaSurveys Team, Madrid, Spain.
Nina ReščičCoronaSurveys Team, Madrid, Spain.
Julian Charles RobertsCoronaSurveys Team, Madrid, Spain.
Rosa E LilloCoronaSurveys Team, Madrid, Spain.
Raquel MenezesCoronaSurveys Team, Madrid, Spain.
Jaya Prakash ChampatiCoronaSurveys Team, Madrid, Spain.
Antonio Fernández AntaCoronaSurveys Team, Madrid, Spain. antonio.fernandez@imdea.org.
IMDEA Networks · ESINESC TEC · PTInstitut de Recherche en Informatique et Systèmes Aléatoires · FRJožef Stefan Institute · SISkyhaven Systems (United States) · USUniversidad Carlos III de Madrid · ESUniversity of Minho · PTUniversity of San Francisco · USUniversity of Southern California · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Symptoms-based detection of SARS-CoV-2 infection is not a substitute for precise diagnostic tests but can provide insight into the likely level of infection in a given population. This study uses symptoms data collected in the Global COVID-19 Trends and Impact Surveys (UMD Global CTIS), and data on variants sequencing from GISAID. This work, conducted in January of 2022 during the emergence of the Omicron variant (subvariant BA.1), aims to improve the quality of infection detection from the available symptoms and to use the resulting estimates of infection levels to assess the changes in vaccine efficacy during a change of dominant variant; from the Delta dominant to the Omicron dominant period. Our approach produced a new symptoms-based classifier, Random Forest, that was compared to a ground-truth subset of cases with known diagnostic test status. This classifier was compared with other competing classifiers and shown to exhibit an increased performance with respect to the ground-truth data. Using the Random Forest classifier, and knowing the vaccination status of the subjects, we then proceeded to analyse the evolution of vaccine efficacy towards infection during different periods, geographies and dominant variants. In South Africa, where the first significant wave of Omicron occurred, a significant reduction of vaccine efficacy is observed from August-September 2021 to December 2021. For instance, the efficacy drops from 0.81 to 0.30 for those vaccinated with 2 doses (of Pfizer/BioNTech), and from 0.51 to 0.09 for those vaccinated with one dose (of Pfizer/BioNTech or Johnson & Johnson). We also extended the study to other countries in which Omicron has been detected, comparing the situation in October 2021 (before Omicron) with that of December 2021. While the reduction measured is smaller than in South Africa, we still found, for instance, an average drop in vaccine efficacy from 0.53 to 0.45 among those vaccinated with two doses. Moreover, we found a significant negative (Pearson) correlation of around - 0.6 between the measured prevalence of Omicron in several countries and the vaccine efficacy in those same countries. This prediction, in January of 2022, of the decreased vaccine efficacy towards Omicron is in line with the subsequent increase of Omicron infections in the first half of 2022.

Indexed as

COVID-19GeographyHumansSARS-CoV-2Vaccine Efficacy

Identifiers

PMID36650230
PMCPMC9844193
OpenAlexW4316813157

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.