Evidence map›Paper›PMID 36963419›Full record

ArticleThe Lancet. Microbe2023

Correlates of protection against COVID-19 infection and intensity of symptomatic disease in vaccinated individuals exposed to SARS-CoV-2 in households in Israel (ICoFS): a prospective cohort study.

Gili Regev-Yochay, Yaniv Lustig, Gili Joseph, Mayan Gilboa, Noam Barda, Ilana Gens, Victoria Indenbaum, Osnat Halpern, Shiri Katz-Likvornik, Tal Levin and 13 more

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Microbe, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed
20.4field-weighted citation impact, top 1% 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

72 citing papers in PubMed, 105 citations in OpenAlex.

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12 more citing papers are in PubMed but not listed here.

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

23 authors at 3 institutions in 1 country.

Gili Regev-YochayInfection Prevention & Control Unit, Sheba Medical Center, Ramat Gan, Israel; Sackler School of Medicine, Tel-Aviv University, Tel Aviv, Israel. Electronic address: gili.regev@sheba.health.gov.il.
Yaniv LustigSackler School of Medicine, Tel-Aviv University, Tel Aviv, Israel; Central Virology Laboratory, Public Health Services, Ministry of Health, Ramat Gan, Israel.
Gili JosephInfection Prevention & Control Unit, Sheba Medical Center, Ramat Gan, Israel.
Mayan GilboaInfection Prevention & Control Unit, Sheba Medical Center, Ramat Gan, Israel; Sackler School of Medicine, Tel-Aviv University, Tel Aviv, Israel.
Noam BardaARC Innovation Center, Sheba Medical Center, Ramat Gan, Israel; Department of Software and Information Systems Engineering, and Department of Epidemiology, Biostatistics and Community Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel.
Ilana GensPublic Health Services, Israeli Ministry of Health, Jerusalem, Israel.
Victoria IndenbaumCentral Virology Laboratory, Public Health Services, Ministry of Health, Ramat Gan, Israel.
Osnat HalpernCentral Virology Laboratory, Public Health Services, Ministry of Health, Ramat Gan, Israel.
Shiri Katz-LikvornikCentral Virology Laboratory, Public Health Services, Ministry of Health, Ramat Gan, Israel.
Tal LevinCentral Virology Laboratory, Public Health Services, Ministry of Health, Ramat Gan, Israel.
Yara KanaanehCentral Virology Laboratory, Public Health Services, Ministry of Health, Ramat Gan, Israel.
Keren AsrafThe Dworman Automated-Mega Laboratory, Sheba Medical Center, Ramat Gan, Israel.
Sharon AmitClinical Microbiology, Sheba Medical Center, Ramat Gan, Israel; Clinical Microbiology, Sheba Medical Center, Ramat Gan, Israel.
Carmit RubinInfection Prevention & Control Unit, Sheba Medical Center, Ramat Gan, Israel.
Arnona ZivData Management Unit, Gerner Institute, Sheba Medical Center, Ramat Gan, Israel.
Ravit KorenCentral Virology Laboratory, Public Health Services, Ministry of Health, Ramat Gan, Israel.
Michal MandelboimSackler School of Medicine, Tel-Aviv University, Tel Aviv, Israel; Central Virology Laboratory, Public Health Services, Ministry of Health, Ramat Gan, Israel.
Noam H TokayerInfection Prevention & Control Unit, Sheba Medical Center, Ramat Gan, Israel.
Lilac MeltzerInfection Prevention & Control Unit, Sheba Medical Center, Ramat Gan, Israel.
Ram DoolmanData Management Unit, Gerner Institute, Sheba Medical Center, Ramat Gan, Israel.
Ella MendelsonCentral Virology Laboratory, Public Health Services, Ministry of Health, Ramat Gan, Israel.
Sharon Alroy-PreisPublic Health Services, Israeli Ministry of Health, Jerusalem, Israel.
Yitshak KreissGeneral Management, Sheba Medical Center, Ramat Gan, Israel; Sackler School of Medicine, Tel-Aviv University, Tel Aviv, Israel.
Israel Ministry of Health · ILSheba Medical Center · ILTel Aviv University · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIdentifying COVID-19 correlates of protection and immunity thresholds is important for policy makers and vaccine development. We aimed to identify correlates of protection of BNT162b2 (Pfizer-BioNTech) vaccination against COVID-19.

methodsIn this prospective cohort study, households within a radius of 40 km of the Sheba Medical Center in Israel in which a new SARS-CoV-2 infection (defined as the index case) was detected within the previous 24 h were approached between July 25 and Nov 15, 2021. We included adults (aged >18 years) who had received one or two vaccine doses, had an initial negative SARS-CoV-2 PCR and no previous infection reported, and had a valid IgG and neutralising antibody result. The exposure of interest was baseline immune status, including IgG antibody concentration, neutralising antibody titre, and T-cell activation. The outcomes of interest were PCR-positive SARS-CoV-2 infection between day 2 and day 21 of follow-up and intensity of disease symptoms (self-reported via a telephone questionnaire) among participants who had a confirmed infection. Multivariable logistic and ordered logit ordinal regressions were used for the adjusted analysis. To identify immunological thresholds for clinical protection, we estimated the conditional probability of infection and moderate or severe disease for individuals with pre-exposure IgG and neutralising antibody concentrations above each value observed in the study data.

findingsFrom 16 675 detected index cases in the study region, 5718 household members agreed to participate, 1461 of whom were eligible to be included in our study. 333 (22·8%) of 1461 household members who were not infected with SARS-CoV-2 at baseline were infected within 21 days of follow-up. The baseline (pre-exposure) IgG and neutralising antibodies were higher in participants who remained uninfected than in those who became infected (geometric mean IgG antibody concentration 168·2 binding antibody units [BAU] per mL [95% CI 158·3-178·7] vs 130·5 BAU/mL [118·3-143·8] and geometric mean neutralising antibody titre 197·5 [181·9-214·4] vs 136 ·7 [120·3-155·4]). Increasing IgG and neutralising antibody concentrations were also significantly associated with a reduced probability of increasing disease severity. Odds of infection were significantly reduced each time baseline IgG antibody concentration increased by a factor of ten (odds ratio [OR] 0·43 [95% CI 0·26-0·70]) and each time baseline neutralising antibody titre increased by a factor of two (0·82 [0·74-0·92]). In our cohort, the probability of infection if IgG antibody concentrations were higher than 500 BAU/mL was 11% and the probability of moderate disease severity was 1%; the probability of infection if neutralising antibody titres were above or equal to 1024 was 8% and the probability of moderate disease severity was 2%. T-cell activation rates were not significantly associated with reduced probability of infection (OR 1·04, 95% CI 0·83-1·30).

interpretationBoth IgG and neutralising antibodies are correlates of protection against SARS-CoV-2 infection. Our data suggest that IgG concentrations higher than 500 BAU/mL and neutralising antibody titres of 1024 or more are thresholds for immunological protection from SARS-CoV-2 delta variant infection. Potentially, updated protective thresholds against emerging variants of concern could be calculated, which could support decision makers on administration of new vaccination strategies and on the optimal period between vaccine doses.

fundingIsraeli Ministry of Health.

Indexed as

COVID-19SARS-CoV-2AdultAntibodies, NeutralizingBNT162 VaccineHumansImmunoglobulin GIsraelProspective StudiesAntibodies, NeutralizingBNT162 VaccineImmunoglobulin G

Identifiers

PMID36963419
PMCPMC10030121
OpenAlexW4328054000

What Socratic holds

Textmetadata
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 Socratic graph.