Effectiveness of prior infection in preventing reinfection with SARS-CoV-2 Omicron BA.2.75 sublineage

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In a recent study posted to the bioRxiv* server, researchers used a test-negative, case-control study design to estimate the effectiveness of prior infection in preventing reinfection with Omicron BA.2.75.2 subvariant in the Qatar population.

Study: Protection against reinfection with SARS-CoV-2 omicron BA.2.75* sublineage. Image Credit: creativeneko/Shutterstock
Study: Protection against reinfection with SARS-CoV-2 omicron BA.2.75* sublineage. Image Credit: creativeneko/Shutterstock

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Background

The Omicron wave started in Qatar on December 19, 2021. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Omicron BA.2.75.2 became the dominant sublineage in Qatar by September 10, 2022. In Qatar, they classified prior Omicron infections by subvariant according to when each dominated incidence. For instance, BA.1 and BA.2, and BA.4/BA.5 dominated incidence from December 19, 2021, to June 7, 2022, and June 8, 2022-September 9, 2022, respectively.

About the study

In the present study, researchers analyzed data from Qatar's federated databases for coronavirus disease 2019 (COVID-19) laboratory testing, vaccination, clinical infection, hospitalization, and death. The Qatar government maintains this integrated nationwide digital-health information platform to collate all SARS-CoV2-related data. This database documents all reverse transcription-polymerase chain reactions (RT-PCR) and rapid antigen testing (RAT) conducted in Qatar. 

They classified infections as pre-Omicron if they occurred before the onset of the Omicron wave on December 19, 2021, and the remaining were Omicron cases. The primary study objective was to determine the effectiveness of prior infection in preventing reinfection (PES). PES measures the proportional reduction in susceptibility to SARS-CoV-2 infection among infected vis-a-vis uninfected individuals.

They derived estimates of PES in the following four groups:

 i) unvaccinated population,

ii) vaccinated population,

iii) unvaccinated and vaccinated individuals combined, and

iv) lastly, in unvaccinated and vaccinated populations, stratified by time since prior infection.

The team exact-matched SARS-CoV-2-positive cases and controls in a 1:5 ratio for PES assessments. While they considered only the first SARS-CoV-2-positive test during the study period for case(s), all SARS-CoV-2-negative tests of controls were included in the analysis. They stratified results by gender, 10-year age group, nationality, comorbidities, vaccine doses at the time of COVID-19 testing, time of testing, method of testing (PCR or RA), and reason for testing.

The researchers estimated the PES by comparing odds of prior infection in all cases diagnosed when BA.2.75 dominated incidence based on RT-PCR variant screening and viral genome sequencing, done between September 10, 2022, and October 18, 2022 (end of the study period), to odds of prior infection among controls. PES was computed as one minus the ratio of the odds of prior infection in cases to the odds of prior infection in controls.

They used the conditional logistic regression model to compute odds ratios (ORs) and associated 95% confidence intervals (CIs). Within the 487 BA.2- like subvariants identified between September 11, 2022, and October 15, 2022, by SARS-CoV-2 whole genome sequencing, 93% were BA.2.75.X. Thus, the team identified BA.2.75.X cases using RT-PCR variant screening for BA.2-like viruses as a proxy.

Study findings

Previous pre-Omicron infections had protective effectiveness of 6% against BA.2.75 reinfections. The combined effectiveness of pre-Omicron infection and BA.1/BA.2 infection against BA.2.75 reinfection was 56.4%. Likewise, the effectiveness of prior BA.1/BA.2 and BA.4/BA.5 infections in preventing BA.2.75 reinfection were 49.9% and 80.6%, respectively. However, the highest was the efficacy of prior pre-Omicron infection, followed by BA.4/BA.5 infection, at 91.6%.

The study analyses stratified by time since prior infection and vaccination status indicated waning of protection and protection from prior infection was higher among those vaccinated, respectively. As expected, the effect of index-virus-type vaccination and a prior Omicron infection was the highest.

Of all BA.2.75 cases, only six patients developed severe COVID-19. Remarkably,  among those with a prior Omicron infection, none developed severe, critical, or fatal COVID-19. In the absence of such cases, an estimation of the effectiveness of prior infection against severe COVID-19 following reinfection with BA.2.75* was not feasible.

Conclusions

Although Omicron barely caused severe COVID-19, a history of Omicron infections broadened protection against future Omicron breakthrough infections. Yet, protection against BA.2.75.2 reinfection was lower than that protection against BA.4/BA.5 reinfection. Furthermore, protection of prior Omicron infection grew from moderate to high (50% to 80%) when the prior infection was with BA.1/BA.2 and BA.4/BA.5, respectively. The study findings reflected progressive immune evasion and gradual natural immunity waning.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Journal references:

Article Revisions

  • May 15 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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