We analyzed 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 (ie, before boosting)

We analyzed 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 (ie, before boosting). Beyond case ascertainment and contact tracing, previous infection knowledge determines reinfection 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 postviral 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 (Wlfl-Duchek et al., 2022). Another major limitation of these methods is the short 710 day window of opportunity (from shortly before symptom onset CVT 6883 to a few days after) to detect infection (Murad CVT 6883 et al., 2021), beyond which the opportunity to detect infection through Rabbit Polyclonal to ZNF329 these modalities is lost in most cases, although viral RNA remains detectable for longer period of time in some 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. Antinuclocapsid (N) IgG antibodies are natural infectionspecific but can wane as quickly as 12 weeks (Shrotri et al., 2021), whereas antispike (S) antibodies last longer (Levin et al., 2021) but are generated either as a result of natural infection or vaccination. Anti-S assays are more commonly available and used than anti-N assays. We analyzed 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 (ie, before 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 before initiating vaccination (n = 119) or through PCR at various points following the initiation of vaccination (n = 103). PCR tests were conducted upon COVID-19 clinical suspicion. To identify asymptomatic infections, individuals with no documented infection and unexpected rises in anti-S IgG were tested using an additional N-antibody assay shortly after the detected anti-S IgG increase to exclude previous infection. Our longitudinal data suggest that in the first 6 months following the second dose, it is difficult to discriminate between vaccine-induced and infection-induced immunity (Figure 1A). However, as time passes, 2 phenomena occur: (i) vaccine-induced IgG antibody wane faster than infection induced and (ii) breakthrough infections cause a boost-like anamnestic response, leading to very high IgG levels that is in excess of what can be induced by vaccination in most cases (Figure 1A). Focusing on participants who were serologically tested 190250 days after dose 2 and before dose 3 (n = 535), 2/430 (0.46%) uninfected individuals had IgG levels above 1000 AU/ml (chosen as an arbitrary threshold), whereas 15/17 (88%) individuals who were infected in the previous 3 months had IgG levels above the threshold (Table 1,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 CVT 6883 with IgG levels above 1000 AU/ml 68 months after 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 the overall negative predictive value was 84.7%. In other words, high IgG levels are predictive of a previous infection when tested 68 months after dose 2, and lower.