Past SARS-CoV-2 infection protection against re-infection: a systematic review and meta-analysis
Published February 16, 2023, in The Lancet (opens in a new window)
For people who have been infected with COVID-19 at least once before, natural immunity against severe disease (hospitalization and death) was strong and long-lasting for all variants (88% or greater at 10 months post infection).
Abstract
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.
Citation
COVID-19 Forecasting Team. Past SARS-CoV-2 infection protection against re-infection: a systematic review and meta-analysis. The Lancet. 16 February 2023. doi: 10.1016/S0140-6736(22)02465-5.
Authors
- Caroline Stein,
- Stephen Lim,
- Christopher J.L. Murray,
- Simon Hay,
- Hasan Nassereldine,
- Reed Sorensen,
- Joanne Amlag,
- Catherine Bisignano,
- Sam Byrne,
- Emma Castro,
- Kaleb Coberly,
- James Collins,
- Jeremy Dalos,
- Farah Daoud,
- Amanda Deen,
- Emmanuela Gakidou,
- John Giles,
- Erin Frame,
- Bethany Huntley,
- Kasey Kinzel,
- Rafael Lozano,
- Ali Mokdad,
- Tom Pham,
- David Pigott,
- Bobby Reiner,
- Theo Vos
Datasets
All our datasets are housed in our data catalog, the Global Health Data Exchange (GHDx). Visit the GHDx to download data from this article.