Long-term detection of SARS-CoV-2 antibodies after infection and risk of re-infection

Elevated BMI reduces the humoral response to SARS-CoV-2 infection

Objective

Class III obesity (body mass index [BMI] ≥ 40 kg m-2) significantly impairs the immune response to SARS-CoV-2 vaccination. However, the effect of an elevated BMI (≥ 25 kg m-2) on humoral immunity to SARS-CoV-2 infection and COVID-19 vaccination remains unclear.

Methods

We collected blood samples from people who recovered from SARS-CoV-2 infection approximately 3 and 13 months of post-infection (noting that these individuals were not exposed to SARS-CoV-2 or vaccinated in the interim). We also collected blood samples from people approximately 5 months of post-second dose COVID-19 vaccination (the majority of whom did not have a prior SARS-CoV-2 infection). We measured their humoral responses to SARS-CoV-2, grouping individuals based on a BMI greater or less than 25 kg m-2.

Results

Here, we show that an increased BMI (≥ 25 kg m-2), when accounting for age and sex differences, is associated with reduced antibody responses after SARS-CoV-2 infection. At 3 months of post-infection, an elevated BMI was associated with reduced antibody titres. At 13 months of post-infection, an elevated BMI was associated with reduced antibody avidity and a reduced percentage of spike-positive B cells. In contrast, no significant association was noted between a BMI ≥ 25 kg m-2 and humoral immunity to SARS-CoV-2 at 5 months of post-secondary vaccination.

Conclusions

Taken together, these data showed that elevated BMI is associated with an impaired humoral immune response to SARS-CoV-2 infection. The impairment of infection-induced immunity in individuals with a BMI ≥ 25 kg m-2 suggests an added impetus for vaccination rather than relying on infection-induced immunity.

Incidence and outcome of SARS-CoV-2 reinfection in the pre-Omicron era: A global systematic review and meta-analysis

Background

With the emergence of new variants and sub-lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), reinfections can significantly impact herd immunity, vaccination policies, and decisions on other public health measures. We conducted a systematic review and meta-analysis to synthesise the global evidence on SARS-CoV-2 reinfections in the pre-Omicron era.

Methods

We searched five global databases (MEDLINE, Embase, CINAHL Plus, Global Health, WHO COVID-19) on 12 May 2022 and 28 July 2023 and three Chinese databases (CNKI, Wanfang, CQvip) on 16 October 2022 for articles reporting incidence and outcomes of SARS-CoV-2 reinfection before the period of Omicron (B.1.1.529) predominance. We assessed risk of bias using Joanna Briggs Institute critical appraisal tools and conducted meta-analyses with random effects models to estimate the proportion of SARS-CoV-2 reinfection among initially infected cases and hospitalisation and mortality proportions among reinfected ones.

Results

We identified 7593 studies and extracted data from 64 included ones representing 21 countries. The proportion of SARS-CoV-2 reinfection was 1.16% (95% confidence interval (CI) = 1.01-1.33) based on 11 639 247 initially infected cases, with ≥45 days between the two infections. Healthcare providers (2.28%; 95% CI = 1.37-3.40) had a significantly higher risk of reinfection than the general population (1.00%; 95% CI = 0.81-1.20), while young adults aged 18 to 35 years (1.01%; 95% CI = 0.8-1.25) had a higher reinfection burden than other age groups (children <18 years old: 0.57%; 95% CI = 0.39-0.79, older adults aged 36-65 years old: 0.53%; 95% CI = 0.41-0.65, elderly >65 years old: 0.37%; 95% CI = 0.15-0.66). Among the reinfected cases, 8.12% (95% CI = 5.30-11.39) were hospitalised, 1.31% (95% CI = 0.29-2.83) were admitted to the intensive care unit, and 0.71% (95% CI = 0.02-2.01) died.

Conclusions

Our data suggest a relatively low risk of SARS-CoV-2 reinfection in the pre-Omicron era, but the risk of hospitalisation was relatively high among the reinfected cases. Considering the possibility of underdiagnosis, the reinfection burden may be underestimated.

Registration

PROSPERO: CRD42023449712.

The Detection of SARS-CoV-2 Antibodies in an Exposed Human Population Is Biased by the Immunoassay Used: Implications in Serosurveillance

The presence of SARS-CoV-2 antibodies was examined over 7 months in a population of essential service workers exposed during the first epidemic wave in Madrid (Spain). Results obtained with different serological assays were compared. Firstly, serum samples obtained in April 2020 were analyzed using eleven SARS-CoV-2 antibody detection methods, including seven ELISAs, two CLIAs and two LFAs. While all of the ELISA tests and the Roche eCLIA method showed good performance, it was poorer for the Abbott CLIA and LFA tests. Sera from 115 workers with serologically positive results in April were collected 2 and 7 months after the first sampling and were analyzed using five of the tests previously assessed. The results showed that while some ELISA tests consistently detected the presence of anti-SARS-CoV-2 antibodies even 7 months after first detection, other methods, such as the Abbott CLIA test, showed an important reduction in sensitivity for these mature antibodies. The sensitivity increased after establishing new cut-off values, calculated taking into account both recent and old infections, suggesting that an adjustment of assay parameters may improve the detection of individuals exposed to the infection.

Risk of reinfection and disease after SARS-CoV-2 primary infection: Meta-analysis

INTRODUCTION

A precise estimate of the frequency and severity of SARS-CoV-2 reinfections would be critical to optimize restriction and vaccination policies for the hundreds of millions previously infected subjects. We performed a meta-analysis to evaluate the risk of reinfection and COVID-19 following primary infection.

METHODS

We searched MedLine, Scopus and preprint repositories for cohort studies evaluating the onset of new infections among baseline SARS-CoV-2-positive subjects. Random-effect meta-analyses of proportions were stratified by gender, exposure risk, vaccination status, viral strain, time between episodes, and reinfection definition.

RESULTS

Ninety-one studies, enrolling 15,034,624 subjects, were included. Overall, 158,478 reinfections were recorded, corresponding to a pooled rate of 0.97% (95% CI: 0.71%-1.27%), with no substantial differences by definition criteria, exposure risk or gender. Reinfection rates were still 0.66% after ≥12 months from first infection, and the risk was substantially lower among vaccinated subjects (0.32% vs. 0.74% for unvaccinated individuals). During the first 3 months of Omicron wave, the reinfection rates reached 3.31%. Overall rates of severe/lethal COVID-19 were very low (2-7 per 10,000 subjects according to definition criteria) and were not affected by strain predominance.

CONCLUSIONS

A strong natural immunity follows the primary infection and may last for more than one year, suggesting that the risk and health care needs of recovered subjects might be limited. Although the reinfection rates considerably increased during the Omicron wave, the risk of a secondary severe or lethal disease remained very low. The risk-benefit profile of multiple vaccine doses for this subset of population needs to be carefully evaluated.

Seroprevalence and infection fatality rate of the SARS-CoV-2 Omicron variant in Denmark: A nationwide serosurveillance study

Background

Introduction of the Omicron variant caused a steep rise in SARS-CoV-2 infections despite high vaccination coverage in the Danish population. We used blood donor serosurveillance to estimate the percentage of recently infected residents in the similarly aged background population with no known comorbidity.

Methods

To detect SARS-CoV-2 antibodies induced due to recent infection, and not vaccination, we assessed anti-nucleocapsid (anti-N) immunoglobulin G (IgG) in blood donor samples. Individual level data on SARS-CoV-2 RT-PCR results and vaccination status were available. Anti-N IgG was measured fortnightly from January 18 to April 3, 2022. Samples from November 2021 were analysed to assess seroprevalence before introduction of the Omicron variant in Denmark.

Findings

A total of 43 088 donations from 35 309 Danish blood donors aged 17–72 years were screened. In November 2021, 1·2% (103/8 701) of donors had detectable anti-N IgG antibodies. Adjusting for test sensitivity (estimates ranging from 74%–81%) and November seroprevalence, we estimate that 66% (95% confidence intervals (CI): 63%–70%) of the healthy, similarly aged Danish population had been infected between November 1, 2021, and March 15, 2022. One third of infections were not captured by SARS-CoV-2 RT-PCR testing. The infection fatality rate (IFR) was 6·2 (CI: 5·1–7·5) per 100 000 infections.

Interpretation

Screening for anti-N IgG and linkage to national registers allowed us to detect recent infections and accurately assess assay sensitivity in vaccinated or previously infected individuals during the Omicron outbreak. The IFR was lower than during previous waves.

Funding

The Danish Ministry of Health.

Reinfection, recontamination and revaccination for SARS-CoV-2

The reports on coronavirus disease 2019 (COVID-19) describe the pandemic in waves. Similar to the ocean’s waves, the frequency and amplitude of the number of new cases and the number of deaths were globally quite regular; nevertheless, they showed important regional irregularities and the direction of spread has been generally rather unpredictable for COVID-19. One of the major reasons for the repeated outbreaks is the mutating capacity of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that allows the virus to infect persons who have natural immunity or have been vaccinated. Vaccination began in vast campaigns from the second year of the pandemic that was supposed to decrease the magnitude of the waves. Although it reduced the complications, the expected attenuation of the disease expansion has not yet been met. This paper provides a short overview of the most recent data on the rate of reinfection in vaccinated and non-vaccinated individuals. It points out that testing positive for a second time for SARS-CoV-2 does not necessarily mean a reinfection; it can also be interpreted as recontamination. The symptom free outcome as well as the rapid reconversion of the polymerase chain reaction test may help to determine the difference between reinfection and recontamination. Awareness of this phenomenon may be valuable in times of human resource difficulties. The available evidence may suggest that the protective value of a prior infection could be better considered for vaccine distribution in the future.