Persistence of anti-SARS-CoV-2 antibodies: immunoassay heterogeneity and implications for serosurveillance

Abstract

Objectives: Serological studies have been critical in tracking the evolution of the COVID-19 pandemic. Data on anti-SARS-CoV-2 antibodies persistence remain sparse, especially from infected individuals with few to no symptoms. The objective of the study was to quantify the sensitivity for detecting historic SARS-CoV-2 infections as a function of time since infection for three commercially available SARS-CoV-2 immunoassays and to explore the implications of decaying immunoassay sensitivity in estimating seroprevalence.

Methods: We followed a cohort of mostly mild/asymptomatic SARS-CoV-2-infected individuals (n = 354) at least 8 months after their presumed infection date and tested their serum for anti-SARS-CoV-2 antibodies with three commercially available assays: Roche-N, Roche-RBD and EuroImmun-S1. We developed a latent class statistical model to infer the specificity and time-varying sensitivity of each assay and show through simulations how inappropriately accounting for test performance can lead to biased serosurvey estimates.

Results: Antibodies were detected at follow-up in 74-100% of participants, depending on immunoassays. Both Roche assays maintain high sensitivity, with the EuroImmun assay missing 40% of infections after 9 months. Simulations reveal that without appropriate adjustment for time-varying assay sensitivity, seroprevalence surveys may underestimate infection rates.

Discussion: Antibodies persist for at least 8 months after infection in a cohort of mildly infected individuals with detection depending on assay choice. Appropriate assay performance adjustment is important for the interpretation of serological studies in the case of diminishing sensitivity after infection.

Keywords: Latent class model; SARS-CoV-2; Seroepidemiology; Seroprevalence; Serosurveillance.

Fig. 1

Study recruitment with respect to the SARS-CoV-2 epidemic curve in Geneva, Switzerland. (A) Weekly reported number of virologically-confirmed SARS-CoV-2 infections in the canton of Geneva (blue bars) and study timing for both the baseline (light grey) and follow-up (dark grey) visits. (B) Histogram of days between study visits for the EI-positive cohort (N = 354).

Fig. 2

Test readout trajectories between baseline and follow-up visits. The cohort was composed of 354 participants with positive Euroimmun anti-S1 (EI) test at baseline. Test readout units and thresholds for positivity are assay-specific, Roche-RBD values below the limit of quantitation (0.4 U/mL) were set to the limit of quantitation for plotting and analysis. The dynamic range of both the EI and Roche-N tests are limited compared to the Roche-RBD thus leading to censoring of extremely high and low values. Baseline and follow-up samples were tested with different reagent lots of the EI immunoassay whereas the same Roche-N and Roche-RBD reagent lots were used for all samples (supplementary material). Trajectories for the EI-negative cohort are given in Fig. S4.

Fig. 3

Model test performance estimates and simulation. (A) Model estimates of sensitivity changes with time post infection. Due to EI reagent inter-lot variability (please see supplementary material) results are shown for the whole sample (N = 354), as well as for a subsample for which assay internal positive quality control (IQC) readout values were similar for baseline and follow-up reagent lots (N = 127, matched low IQC lot). (B–D) Simulation scenarios of seroprevalence estimation if the decay in sensitivity is not accounted for. Scenario in (B) is assumed to occur one month after the first epidemic wave peak in Geneva, with corresponding distribution of days between infection and the serosurvey; scenario in (C) the serosurvey occurs after a single wave and 180 days after the epidemic peak; and scenario in (D) assumes the serosurvey occurred one month after the peak of the second epidemic wave, yielding a bimodal distribution of days post infection (insets, vertical dashed line at x = 0 indicates infections that occurred on the serosurvey date).