key: cord-0714210-z2nn4xn5
authors: Jabal, Kamal Abu; Edelstein, Michael
title: Using SARS-CoV-2 anti-S IgG levels as a marker of previous infection: Example from an Israeli Healthcare worker cohort
date: 2022-04-09
journal: Int J Infect Dis
DOI: 10.1016/j.ijid.2022.04.010
sha: 65df43e7256513bcc2e7ac3e4a225e0361540497
doc_id: 714210
cord_uid: z2nn4xn5

Objectives : determining COVID19 status is important for global epidemiology and individual-level vaccination decision-making. SARS CoV-2 Infection can generally only be detected during a 7-10 days period using PCR or rapid antigen testing, and infection specific anti nucleocapsid IgG assays are not universally available. We determined whether SARS-CoV-2 anti spike (anti-S) IgG levels could discriminate between vaccination and past infection when interpreted alongside vaccination timing. Methods : We measured SARS CoV2 IgG levels anti-spike Anti-S-IgG level in 535 vaccinated Israeli healthcare workers with known previous infection status 6-8 months post dose 2. Results : Anti-S IgG levels above 1000 AU/ml at that time point was 93.3% predictive of infection in the previous 3 months, whereas the negative predictive value for infection in the past 3 months of a level below that threshold was 99.5%. Conclusion : When interpreted alongside vaccination timing, anti-S serological assays can confirm or exclude previous infection within the previous 3 months

Objectives: determining COVID19 status is important for global epidemiology and individual-level vaccination decision-making. SARS CoV-2 Infection can generally only be detected during a 7-10 days period using PCR or rapid antigen testing, and infection specific anti nucleocapsid IgG assays are not universally available. We determined whether SARS-CoV-2 anti spike (anti-S) IgG levels could discriminate between vaccination and past infection when interpreted alongside vaccination timing.

Methods: We measured SARS CoV2 IgG levels anti-spike Anti-S-IgG level in 535 vaccinated Israeli healthcare workers with known previous infection status 6-8 months post dose 2.

Results: Anti-S IgG levels above 1000 AU/ml at that time point was 93.3% predictive of infection in the previous 3 months, whereas the negative predictive value for infection in the past 3 months of a level below that threshold was 99.5%.

Conclusion: When interpreted alongside vaccination timing , anti-S serological assays can confirm or exclude previous infection within the previous 3 months Keywords: COVID 19; SARS-CoV-2; serology; testing; public health Detecting current or past SARS-CoV-2 infection is an essential component of pandemic management. Beyond case ascertainment and contact tracing, prior infection knowledge determines re-infection risk, the number and timing of vaccine doses required (Abu Jabal et al., 2021; Hansen et al., 2021) , and can serve as evidence to attribute post-viral symptoms to infection.

Determining acute infection status relies on detecting viral DNA through polymerase chain reaction (PCR) or viral proteins through rapid antigen testing which has limited sensitivity (Wölfl-Duchek et al., 2022) . Another major limitation of these methods is the short 7-10 days window of opportunity (from shortly before symptom onset to a few days after) to detect infection (Murad et al., 2021) , beyond which the opportunity to detect infection through these modalities is lost in most cases although viral RNA remains detectable for longer period of time in a minority of cases (Sethuraman et al, 2020) . This issue is compounded by the large proportion of asymptomatic infections (Sah et al., 2021) , especially in highly vaccinated populations, for which there is no trigger to getting tested. Measuring circulating IgG immunoglobulins is another approach to determining immunity. Anti-nuclocapsid (N) IgG antibodies are natural infection-specific but can wane as quickly as 12 weeks (Shrotri et al., 2021), whereas anti-spike (S) antibodies are longer lasting (Levin et al., 2021) but generated either as a result of natural infection or vaccination. Anti-S assays are more commonly available and used than anti-N assays. We analysed serological data from vaccinated healthcare workers cohort from Ziv Medical Centre, Israel to determine whether it was possible to discriminate between natural infection and vaccination using anti-S IgG, taking circulating antibody levels and time since vaccination into consideration, using the time period between the second and third vaccine doses as an example, i.e prior to boosting. The cohort has been described elsewhere (Abu Jabal et al., 2021) .

Briefly, we measured circulating anti-S IgG levels approximately every 2 months among all consenting healthcare workers at the hospital, using a LIASON Diasorin S1/S2 assay. Of 998 enrolled participants, 222 were identified as infected, either through N IgG detection prior to initiating vaccination (n=119) or through PCR at various points following the initiation of Figure   1b ). Among those infected earlier, 75/88 (85%) had IgG levels below 1000 AU/ml. The difference between these proportions, tested using a chi square test, was statistically significant (p<0.0001). In our sample the positive predictive value for previous infection with IgG levels above 1000 AU/ml 6-8 months post dose 2 was 93.3% and the negative predictive value of IgG levels below 1000 AU/ml for infection in the last 3 months was 99.5% but overall negative predictive value was 84.7%%. In other words, high IgG levels are predictive of previous infection when tested 6-8 months post dose 2; lower IgG levels is highly predictive of no recent (< 3months) infection but cannot reliably exclude earlier infection.

These findings suggest that anti-S IgG levels could be used as markers of previous infection. This could prove useful where anti-N IgG assays and/or PCR testing is not available. Because different assays report different arbitrary levels, this approach would need to be repeated with each of the commonly used serological assays. In addition, the type of vaccine used, time from vaccination, patient age and SARS-CoV-2 variant are also likely to influence the optimal discriminatory thresholds, which would be time-specific and would need to be calculated separately following third doses. Our sample is too small to determine optimal thresholds using Receiver Operating Characteristic (ROC) Curves. Our objective in this letter is not to propose definitive diagnostic thresholds but to demonstrate through proof-of-concept that Anti-S IgG levels can be used to discriminate between natural infection and vaccination and to encourage others teams, in particular those with large immunogenicity datasets, to analyse their data in this way and possibly to pool data in order to build a reference library of IgG levels that includes different timings, vaccines and assays. A similar approach can be applied post-booster. Such an approach will enable to retrospectively identify previously infected individuals at a time in the pandemic where PCR tests are not always available and countries are moving away from mass testing and will otherwise never be able to determine whether or not individuals were infected. This could have implications for vaccine policy to determine who requires further doses, and potentially down the line for long COVID claims, where providing evidence of previous infection could be crucial.

Competing interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Role of the Funding source: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Ethics: Informed consent was obtained for all participants. The study was approved by Ziv Medical Centre's ethics committee (0133-20-ZIV).

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