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Meta-Analysis
.2023 Mar 11;401(10379):833-842.
doi: 10.1016/S0140-6736(22)02465-5. Epub 2023 Feb 16.

Past SARS-CoV-2 infection protection against re-infection: a systematic review and meta-analysis

Collaborators
Meta-Analysis

Past SARS-CoV-2 infection protection against re-infection: a systematic review and meta-analysis

COVID-19 Forecasting Team. Lancet..

Abstract

Background: Understanding the level and characteristics of protection from past SARS-CoV-2 infection against subsequent re-infection, symptomatic COVID-19 disease, and severe disease is essential for predicting future potential disease burden, for designing policies that restrict travel or access to venues where there is a high risk of transmission, and for informing choices about when to receive vaccine doses. We aimed to systematically synthesise studies to estimate protection from past infection by variant, and where data allow, by time since infection.

Methods: In this systematic review and meta-analysis, we identified, reviewed, and extracted from the scientific literature retrospective and prospective cohort studies and test-negative case-control studies published from inception up to Sept 31, 2022, that estimated the reduction in risk of COVID-19 among individuals with a past SARS-CoV-2 infection in comparison to those without a previous infection. We meta-analysed the effectiveness of past infection by outcome (infection, symptomatic disease, and severe disease), variant, and time since infection. We ran a Bayesian meta-regression to estimate the pooled estimates of protection. Risk-of-bias assessment was evaluated using the National Institutes of Health quality-assessment tools. The systematic review was PRISMA compliant and was registered with PROSPERO (number CRD42022303850).

Findings: We identified a total of 65 studies from 19 different countries. Our meta-analyses showed that protection from past infection and any symptomatic disease was high for ancestral, alpha, beta, and delta variants, but was substantially lower for the omicron BA.1 variant. Pooled effectiveness against re-infection by the omicron BA.1 variant was 45·3% (95% uncertainty interval [UI] 17·3-76·1) and 44·0% (26·5-65·0) against omicron BA.1 symptomatic disease. Mean pooled effectiveness was greater than 78% against severe disease (hospitalisation and death) for all variants, including omicron BA.1. Protection from re-infection from ancestral, alpha, and delta variants declined over time but remained at 78·6% (49·8-93·6) at 40 weeks. Protection against re-infection by the omicron BA.1 variant declined more rapidly and was estimated at 36·1% (24·4-51·3) at 40 weeks. On the other hand, protection against severe disease remained high for all variants, with 90·2% (69·7-97·5) for ancestral, alpha, and delta variants, and 88·9% (84·7-90·9) for omicron BA.1 at 40 weeks.

Interpretation: Protection from past infection against re-infection from pre-omicron variants was very high and remained high even after 40 weeks. Protection was substantially lower for the omicron BA.1 variant and declined more rapidly over time than protection against previous variants. Protection from severe disease was high for all variants. The immunity conferred by past infection should be weighed alongside protection from vaccination when assessing future disease burden from COVID-19, providing guidance on when individuals should be vaccinated, and designing policies that mandate vaccination for workers or restrict access, on the basis of immune status, to settings where the risk of transmission is high, such as travel and high-occupancy indoor settings.

Funding: Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom.

Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

PubMed Disclaimer

Conflict of interest statement

Declaration of interests DMP reports support from the Bill & Melinda Gates foundation as grant payments made to the Institute for Health Metrics and Evaluation. All other authors declare no competing interests.

Figures

Figure 1
Figure 1
Data availability (number of input studies) by SARS-CoV-2 variant and outcome for the systematic review as a whole and for the analysis of time since infection (A) Number of studies available for inclusion in any component of the systematic review. (B) Number of studies available for inclusion specifically in the analysis of time since infection. Studies were included in this analysis if they included information on time since infection.
Figure 2
Figure 2
Pooled estimate of protection from past SARS-CoV-2 infection against re-infection, symptomatic disease, and severe disease by variant, and number of included studies in each meta-analysis estimate Data are pooled estimate (95% uncertainty interval). Estimates of protection against re-infection (A), symptomatic disease (B), and severe disease (C).
Figure 3
Figure 3
Estimates of protection by time since infection for ancestral, alpha, delta, omicron BA.1, and omicron BA.2 variants Each dot colour represents a different study and its data points according to week after infection. Estimates of protection by time since infection for ancestral, alpha, and delta variants are shown for re-infection (A), symptomatic disease (C), and severe disease (E). Estimates of protection by time since infection for omicron BA.1 are shown for re-infection (B), symptomatic disease (D), and severe disease (F). Estimates of protection by time since infection for omicron BA.2 re-infection (B1).
Figure 4
Figure 4
Comparison of protection efficacy from past COVID-19 infection versus protection from vaccination (by vaccine type and dose) against re-infection, symptomatic disease, and severe disease for ancestral, alpha, delta, or omicron BA.1 variants Shading indicates 95% UIs. (A) Comparison between waning of immunity with time of protection conferred by SARS-CoV-2 infection against re-infection with ancestral, alpha, or delta variant versus vaccine protection against primary infection with alpha and delta by type of vaccine and dose. (B) Comparison between waning of immunity with time of protection conferred by SARS-CoV-2 infection against re-infection with omicron variant versus vaccine protection against primary infection with omicron by type of vaccine and dose. (C) Comparison between waning of immunity with time of protection conferred by SARS-CoV-2 infection against symptomatic disease with ancestral, alpha, or delta variant versus vaccine protection against primary infection with alpha and delta by type of vaccine and dose. (D) Comparison between waning of immunity with time of the protection conferred by SARS-CoV-2 infection against symptomatic disease with omicron variant versus vaccine protection against primary infection with omicron by type of vaccine and dose. (E) Comparison between waning of immunity with time of the protection conferred by SARS-CoV-2 infection against severe disease with ancestral, alpha, or delta variant versus vaccine protection against primary infection with alpha and delta by type of vaccine and dose. (F) Comparison between waning of immunity with time of protection conferred by SARS-CoV-2 infection against severe disease with omicron variant versus vaccine protection against primary infection with omicron by type of vaccine and dose. UIs=uncertainty intervals.
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References

    1. Wang H, Paulson KR, Pease SA, et al. Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21. Lancet. 2022;399:1513–1536. - PMC - PubMed
    1. Barber RM, Sorensen RJD, Pigott DM, et al. Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis. Lancet. 2022;399:2351–2380. - PMC - PubMed
    1. Reiner RC, Jr, Collins JK, Forecasting Team C-19. Murray CJL. Social Science Research Network; Rochester, NY: 2022. Forecasting the trajectory of the COVID-19 pandemic under plausible variant and intervention scenarios: a global modelling study.
    1. IHME COVID-19 projections.https://covid19.healthdata.org/
    1. Adolph C, Amano K, Bang-Jensen B, Fullman N, Wilkerson J. Pandemic politics: timing state-level social distancing responses to COVID-19. J Health Polit Policy Law. 2021;46:211–233. - PubMed

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