In a recent study posted to the medRxiv* preprint server, researchers investigated the protection conferred by previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in preventing reinfection with BA.4 or BA.5 Omicron subvariants in the residents of Qatar.
Omicron BA.4 and BA.5 (B.1.1.529) subvariants were first detected in Qatar in early May 2022 and became predominant by June 8, 2022. Both subvariants caused a surge in reinfections due to their substantial capacity to evade neutralizing antibodies elicited in response to natural infection and coronavirus disease 2019 (COVID-19) vaccination. Previous studies have also successfully used the recently developed test-negative methodology for determining SARS-CoV-2 PEs.
About the study
In the present study, researchers adopted a similar test-negative methodology and a case-control study design to determine the effectiveness of previous infections in preventing Omicron BA.4 or BA.5 reinfections. The researchers further classified previous infections as pre-Omicron vs. Omicron for PEs estimation, based on the date of the beginning of the Omicron wave in Qatar, i.e., December 19, 2021. They assessed and analyzed integrated digital-health information data of Qatar from January 5, 2022, onwards.
The data encompassed information on every reverse transcriptase-polymerase chain reaction (RT-PCR) and rapid antigen test (RAT), vaccination status, clinical infection details, hospitalization, and death records, plus associated demographic information since the pandemic onset. The researchers matched test and control groups in a 1:5 ratio by gender, 10-year age group, nationality, count of comorbidities, laboratory testing, the reason for testing, and testing method (PCR or RAT). While the team examined all records of SARS-CoV-2 testing for test and control groups, finally, they only analyzed matched samples.
They adopted two methods for the study assessments. First, they estimated the effectiveness of the previous infection in preventing reinfection (PEs) using the SARS-CoV-2 spike (S)-gene target failure (SGTF) test, which serves as a proxy for BA.4/BA.5 infections, between May 7, 2022, and July 4, 2022. They also evaluated all BA.4/BA.5 infection diagnoses between June 8, 2022, and July 4, 2022, when these subvariants dominated case incidence in Qatar, to determine PEs.
Notably, PEs is the fractional reduction in susceptibility to contracting a breakthrough SARS-CoV-2 infection among those previously infected versus those who were not. For the test subjects, the team included only the first SARS-CoV-2-positive test occurring during the study period, but all SARS-CoV-2-negative tests and vice-versa for the control group. In some cases, prolonged RT-PCR positivity misclassifies reinfection. Hence, the researchers considered a documented infection ≥90 days after an earlier infection as SARS-CoV-2 reinfection. Further, they included every test-matched control that met the inclusion criteria to minimize different types of potential bias.
The team used frequency distributions and measures of central tendency to describe cases and controls. For group comparisons, they deployed standardized mean differences, which indicated the difference in the mean of a covariate between groups divided by the pooled standard deviation. Its values <0.1 indicated optimal matching. The team computed PEs as one minus ratio of the odds of the previous infection in SARS-CoV-2-positive tests to the odds of a prior infection in controls. Further, they used conditional logistic regression to compute odds ratios (ORs) and associated 95% confidence intervals (CIs). Lastly, they performed sensitivity analyses to validate the study results accounting for vaccination status.
The team sequenced the whole genome of 82 random SARS-CoV-2-positive specimens collected between May 28, 2022, and June 10, 2022. In these samples, Omicron BA.1, BA.2, BA.4, and BA.5 caused infections in 1.2%, 46.3%, 11%, and 41.5% of cases, respectively. Further, they sequenced another 93 random SARS-CoV-2-positive specimens with RT-PCR cycle threshold (Ct) values ≤25 between June 5, 2022, and June 25, 2022. The results showed that Omicron BA.1, BA.2, BA.4, and BA.5 caused infections in 4.3%, 20.4%, 7.5%, and 67.7% of cases, respectively. For the study duration, SGTF results for 84 other random SARS-CoV-2-positive specimens showed that 96.4% ad 3.6% of infections were due to BA.4/BA.5 and BA.1, respectively.
A previous pre-Omicron infection offered 15.1% effective protection against symptomatic BA.4/BA.5 reinfection, while it increased to 28.3% for BA.4/BA.5 reinfections regardless of symptoms. A prior Omicron infection conferred higher protection against BA.4/BA.5 reinfection than a pre-Omicron infection. Accordingly, its effectiveness was 76.1% and 79.7% against symptomatic and any BA.4/BA.5 reinfection, respectively. Omicron BA.4/BA.5 sub-variants exhibit a higher potential to evade immunity than BA.1/BA.2. Thus, a previous infection conferred protection was lower against BA.4/BA.5 than against BA.1/BA.2.
The test-negative design of the current study ensured that misclassification of previous infection status had a minimal impact on estimated PEs. Also, being implemented on Qatar’s total population, the study had a minimal likelihood of bias. Overall, consistent with previous findings, it demonstrated that a previous infection due to Omicron BA.1/BA.2 subvariants conferred strong immunity against subsequent BA.4/BA.5 reinfection.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
- Altarawneh, H. et al. (2022) "Protection of SARS-CoV-2 natural infection against reinfection with the Omicron BA.4 or BA.5 subvariants". medRxiv. doi: 10.1101/2022.07.11.22277448. https://www.medrxiv.org/content/10.1101/2022.07.11.22277448v1
Posted in: Medical Science News | Medical Research News | Disease/Infection News
Tags: Antibodies, Antigen, Coronavirus, Coronavirus Disease COVID-19, covid-19, CT, Frequency, Gene, Genome, immunity, Laboratory, Omicron, Pandemic, Polymerase, Polymerase Chain Reaction, Respiratory, Reverse Transcriptase, SARS, SARS-CoV-2, Severe Acute Respiratory, Severe Acute Respiratory Syndrome, Syndrome
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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