Study finds Omicron variant could break through vaccine protection more effectively than the Delta variant

In a recent study posted to the medRxiv* preprint server, researchers assessed the efficacy of vaccinations against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta and Omicron variants of concern (VOCs).

Study: SARS-CoV-2 vaccine breakthrough by Omicron and Delta variants: comparative assessments with New York State genomic surveillance data. Image Credit: JIMMOYHT/Shutterstock
Study: SARS-CoV-2 vaccine breakthrough by Omicron and Delta variants: comparative assessments with New York State genomic surveillance data. Image Credit: JIMMOYHT/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

Previous studies have reported that vaccinations have provided significant protection against the original SARS-CoV-2 strain (Wuhan-Hu-1); however, recently emerged SARS-CoV-2 strains have demonstrated greater potential to cause vaccine breakthrough infections. Omicron has been found to contain several mutations responsible for its increased infectivity, enhanced immune-evasiveness, and reduced efficacy of monoclonal antibodies and plasma antibody transfers.

About the study

Researchers assessed vaccination efficacy against Delta and Omicron in the present case-control study.

For the analysis, the New York State (NYS) genomic sequence dataset was linked with the vaccination and demographic data of the participants. The adjusted associations of age, type of vaccination (Moderna, Janssen, Pfizer), the status of vaccination, and time elapsed since vaccination with SARS-CoV-2 strains were evaluated using odds ratios (OR). Data were analyzed using logistic regression models of the Delta wave and Omicron wave, and the best fit models were decided using the Akaike information criterion (AIC) scoring system.

Respiratory swabs were obtained from the study participants for real-time PCR analysis, following which SARS-CoV-2-positive swabs were subjected to whole-genome sequencing (WGS) for genomic surveillance. The samples were linked to demographic data in the communicable disease electronic surveillance system (CDESS) and vaccination records in the NYS immunization system (NYSIIS).

Omicron emergence analysis was performed between November 28, 2021, and January 24, 2022. Individuals with Omicron (all BA sublineages) infections (cases, n=1439) were matched to individuals infected with any other strain (controls, n=728) during the Omicron predominance period. Cases were matched to controls based on the date of specimen collection, sex, age, and economic regions.

Delta emergence analysis was performed between March 19, 2021, and August 15, 2021, for which cases (n=603) comprised individuals infected with Delta (all AY sublineages), and those affected with any other SARS-CoV-2 strain except Delta during the Delta predominance period were considered as controls (n=1816). Booster vaccination-associated variables were excluded from the Delta emergence analysis since booster doses were not readily available during this period.

Results

In the Omicron emergence analysis, most participants (>80%) were 18- to 69-year-old, 22% and 8% of cases and controls, respectively, had received booster vaccinations, and the corresponding proportions of unvaccinated individuals were 30% and 56%, respectively. Among vaccinated individuals, 177, 109, and 22 received Pfizer, Moderna, and Janssen vaccinations, respectively. All controls in the data set were infected by Delta.

Complete vaccinations and booster vaccinations were substantially associated with Omicron infections, with OR values of 3.1 and 6.7, respectively. The risk of Omicron infections in relation to Delta infections showed a declining trend with advancing age (OR 0.96). The higher likelihood of Omicron infections among young individuals compared to adults could be due to more socialization and other behavioral risk factors among individuals aged 18 to 29.

On limiting the analysis to only individuals who were vaccinated, the likelihood of Omicron infections reduced with increases in the time elapsed since the last vaccination (OR 0.99). Further, the likelihood of Omicron infections was lower with Janssen vaccinations (OR 0.35) compared to Pfizer vaccinations; (OR 0.4) in relation to any messenger ribonucleic acid (mRNA) vaccination.

In the Delta emergence analysis, most individuals (75%) were also 18- to 69-year-old, and 61.8% and 75% of cases and controls, respectively, were unvaccinated. Among the controls, 62%, 20%, 3.5%, and 1% of individuals were infected by the Alpha, Iota, Gamma, and Beta strains, respectively, and the remaining were infected with other SARS-CoV-2 non-VOC strains.

Neither the type of vaccination nor the time elapsed since the last vaccination showed a significantly associated with higher odds of Delta infections compared to infection with any other SARS-CoV-2 strain. However, when age was not considered for matching cases and controls, individuals who received Pfizer vaccines were 7.3-times more likely to develop Delta infections compared to any other SARS-CoV-2 strain infection.

Conclusions

Overall, the study findings showed that Omicron was more immune-evasive than Delta and could break through SARS-CoV-2 vaccine protection (including booster doses) more efficiently compared to Delta, although Delta may be better able to break through vaccines than previous SARS-CoV-2 strains such as Alpha.

However, the effect of time elapsed since vaccination was not assessed by stratifying individuals based on receival or non-receival of booster doses. The study sample population was small to assess the effects of vaccination by vaccine type. Therefore, further research with larger sample sizes and comparison between vaccine types and between boosted and non-boosted individuals is required to inform vaccine developers better.

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 13 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.
Pooja Toshniwal Paharia

Written by

Pooja Toshniwal Paharia

Pooja Toshniwal Paharia is an oral and maxillofacial physician and radiologist based in Pune, India. Her academic background is in Oral Medicine and Radiology. She has extensive experience in research and evidence-based clinical-radiological diagnosis and management of oral lesions and conditions and associated maxillofacial disorders.

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