Socioeconomic and Demographic Risk Factors for SARS-CoV-2 Seropositivity Among Healthcare Workers in a UK Hospital: A Prospective Cohort Study

BACKGROUND

To protect healthcare workers (HCWs) from the consequences of disease due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is necessary to understand the risk factors that drive exposure and infection within hospitals. Insufficient consideration of key socioeconomic variables is a limitation of existing studies that can lead to bias and residual confounding of proposed risk factors for infection.

METHODS

The Co-STARs study prospectively enrolled 3679 HCWs between April 2020 and September 2020. We used multivariate logistic regression to comprehensively characterize the demographic, occupational, socioeconomic, and environmental risk factors for SARS-CoV-2 seropositivity.

RESULTS

After adjusting for key confounders, relative household overcrowding (odds ratio [OR], 1.4 [95% confidence interval {CI}, 1.1-1.9]; P = .006), Black, Black British, Caribbean, or African ethnicity (OR, 1.7 [95% CI, 1.2-2.3]; P = .003), increasing age (ages 50-60 years: OR, 1.8 [95% CI, 1.3-2.4]; P < .001), lack of access to sick pay (OR, 1.8 [95% CI, 1.3-2.4]; P < .001).

CONCLUSIONS

Socioeconomic and demographic factors outside the hospital were the main drivers of infection and exposure to SARS-CoV-2 during the first wave of the pandemic in an urban pediatric referral hospital. Overcrowding and out-of-hospital SARS-CoV-2 contact are less amenable to intervention. However, lack of access to sick pay among externally contracted staff is more easily rectifiable. Our findings suggest that providing easier access to sick pay would lead to a decrease in SARS-CoV-2 transmission and potentially that of other infectious diseases in hospital settings.

CLINICAL TRIALS REGISTRATION

NCT04380896.

The influence of time on the sensitivity of SARS-CoV-2 serological testing

Sensitive serological testing is essential to estimate the proportion of the population exposed or infected with SARS-CoV-2, to guide booster vaccination and to select patients for treatment with anti-SARS-CoV-2 antibodies. The performance of serological tests is usually evaluated at 14–21 days post infection. This approach fails to take account of the important effect of time on test performance after infection or exposure has occurred. We performed parallel serological testing using 4 widely used assays (a multiplexed SARS-CoV-2 Nucleoprotein (N), Spike (S) and Receptor Binding Domain assay from Meso Scale Discovery (MSD), the Roche Elecsys-Nucleoprotein (Roche-N) and Spike (Roche-S) assays and the Abbott Nucleoprotein assay (Abbott-N) on serial positive monthly samples collected as part of the Co-STARs study (www.clinicaltrials.gov, NCT04380896) up to 200 days following infection. Our findings demonstrate the considerable effect of time since symptom onset on the diagnostic sensitivity of different assays. Using a time-to-event analysis, we demonstrated that 50% of the Abbott nucleoprotein assays will give a negative result after 175 days (median survival time 95% CI 168–185 days), compared to the better performance over time of the Roche Elecsys nucleoprotein assay (93% survival probability at 200 days, 95% CI 88–97%). Assays targeting the spike protein showed a lower decline over the follow-up period, both for the MSD spike assay (97% survival probability at 200 days, 95% CI 95–99%) and the Roche Elecsys spike assay (95% survival probability at 200 days, 95% CI 93–97%). The best performing quantitative Roche Elecsys Spike assay showed no evidence of waning Spike antibody titers over the 200-day time course of the study. We have shown that compared to other assays evaluated, the Abbott-N assay fails to detect SARS-CoV-2 antibodies as time passes since infection. In contrast the Roche Elecsys Spike Assay and the MSD assay maintained a high sensitivity for the 200-day duration of the study. These limitations of the Abbott assay should be considered when quantifying the immune correlates of protection or the need for SARS-CoV-2 antibody therapy. The high levels of maintained detectable neutralizing spike antibody titers identified by the quantitative Roche Elecsys assay is encouraging and provides further evidence in support of long-lasting SARS-CoV-2 protection following natural infection.

The Influence of Time on the Sensitivity of SARS-CoV-2 Serological Testing

Background: Serological testing is used to quantify SARS-CoV-2 seroprevalence, guide booster vaccination and select patients for anti-SARS-CoV-2 antibodies therapy. However, our understanding of how serological tests perform as time passes after infection is limited. Methods: Four assays were compared in parallel: 1) the multiplexed spike, nucleoprotein and receptor binding domain Meso Scale Discovery (MSD) assay 2) the Roche Elecsys-Nucleoprotein assay (Roche-N) 3) the Roche Spike assay (Roche-S) and 4) the Abbott Nucleoprotein assay (Abbott-N) on serial positive monthly samples from hospital staff up to 200 days following infection as part of the Co-Stars study. Results: We demonstrate that 50% of the Abbott-N assays give a negative result after 175 days (median survival time 95% CI 168-185 days) while the Roche-N assay (93% survival probability at 200 days, 95% CI 88-97%) maintained seropositivity. The MSD spike (97% survival probability at 200 days, 95% CI 95-99%) and the Roche-S assay (95% survival probability at 200 days, 95% CI 93-97%) also remained seropositive. The best performing quantitative Roche-S assay showed no evidence of waning Spike antibody titres over 200-days. Conclusions: The Abbott-N assay fails to detect SARS-CoV-2 antibodies as time passes since infection. In contrast the Roche and the MSD assays maintained high sensitivity. The limitations of the Abbott assay must be considered in clinical decision making. The long duration of detectable neutralizing spike antibody titres by the quantitative Roche-S assay provides further evidence in support of long-lasting SARS-CoV-2 protection to pre-existing strains of SARS-CoV-2 following natural infection. Trial registration : Co-STARs study was registered with ClinicalTrials.gov on May 8th, 2020, with trial number NCT04380896 (www.clinicaltrials.gov, NCT04380896).

Long-Term Persistence of Spike Antibody and Predictive Modeling of Antibody Dynamics Following Infection with SARS-CoV-2

Background

Antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been shown to neutralize the virus in vitro and prevent disease in animal challenge models on reexposure. However, the current understanding of SARS-CoV-2 humoral dynamics and longevity is conflicting.

Methods

The COVID-19 Staff Testing of Antibody Responses Study (Co-Stars) prospectively enrolled 3679 healthcare workers to comprehensively characterize the kinetics of SARS-CoV-2 spike protein (S), receptor-binding domain, and nucleoprotein (N) antibodies in parallel. Participants screening seropositive had serial monthly serological testing for a maximum of 7 months with the Meso Scale Discovery Assay. Survival analysis determined the proportion of seroreversion, while 2 hierarchical gamma models predicted the upper and lower bounds of long-term antibody trajectory.

Results

A total of 1163 monthly samples were provided from 349 seropositive participants. At 200 days after symptoms, >95% of participants had detectable S antibodies, compared with 75% with detectable N antibodies. S antibody was predicted to remain detectable in 95% of participants until 465 days (95% confidence interval, 370–575 days) using a “continuous-decay” model and indefinitely using a “decay-to-plateau” model to account for antibody secretion by long-lived plasma cells. S-antibody titers were correlated strongly with surrogate neutralization in vitro (R² = 0.72). N antibodies, however, decayed rapidly with a half-life of 60 days (95% confidence interval, 52–68 days).

Conclusions

The Co-Stars data presented here provide evidence for long-term persistence of neutralizing S antibodies. This has important implications for the duration of functional immunity after SARS-CoV-2 infection. In contrast, the rapid decay of N antibodies must be considered in future seroprevalence studies and public health decision-making. This is the first study to establish a mathematical framework capable of predicting long-term humoral dynamics after SARS-CoV-2 infection.

Clinical Trials Registration

NCT04380896.