Evidence map›Paper›PMID 39211889›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Strength and durability of indirect protection against SARS-CoV-2 infection through vaccine and infection-acquired immunity.

Sophia T Tan, Isabel Rodríguez-Barraquer, Ada T Kwan, Seth Blumberg, Hailey J Park, Justine Hutchinson, David Leidner, Joseph A Lewnard, David Sears, Nathan C Lo

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Isabel Rodríguez-Barraquer
Seth Blumberg
Hailey J Park
Justine Hutchinson
Joseph A Lewnard
David Sears
Nathan C Lo

Funding

MUTIDISCIPLINARY TRAINING PROGRAM IN LUNG DISEASEST32HL007185 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI David J Erle, LAURENCE HUANG · 1985 to 2026
$24.6M
NHLBI NIH HHS T32 HL007185
6 · The paper itself

Abstract

Early investigation revealed that COVID-19 vaccines confer indirect protection to fully susceptible and unvaccinated persons, defined as a reduced risk of SARS-CoV-2 infection among social contacts of vaccinated individuals. However, indirect protection from infection-acquired immunity and its comparative strength and durability to vaccine-derived indirect protection in the current epidemiologic context of high levels of vaccination, prior infection, and novel variants are not well characterized. Here, we show that both infection-acquired and vaccine-derived immunity independently yield indirect protection to close social contacts with key differences in their strength and waning. Analyzing anonymized data from a system-wide SARS-CoV-2 surveillance program of 177,319 residents across 35 California state prisons from December 2021 to December 2022 in a case-control design, we find that vaccine-derived indirect protection against Omicron SARS-CoV-2 infection is strongest within three months post-vaccination [30% (95% confidence interval: 20-38%)] with subsequent modest protection, whereas infection-acquired immunity provides 38% (24-50%) indirect protection to roommates for 6 months after SARS-CoV-2 infection, with moderate indirect protection persisting for over one year. Variant-targeted vaccines (bivalent formulation including Omicron subvariants BA.4/BA.5) confer strong indirect protection for at least three months [40% (3-63%)]. These results have important implications for understanding the long-term transmission dynamics of SARS-CoV-2 and can guide vaccine policy and public health measures, especially in high-risk environments such as prisons.

Identifiers

PMID39211889
PMCPMC11361209

What OpenQuestion holds

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Registered trials

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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.