Long-Term Persistence of Spike Protein Antibody and Predictive Modeling of Antibody Dynamics After Infection With Severe Acute Respiratory Syndrome Coronavirus 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

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

BACKGROUND: In order to protect healthcare workers from the consequences of disease due to SARS-CoV-2 it is necessary to understand the risk factors that drive exposure and infection within hospitals. Insufficient consideration of key socio-economic 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 characterise the demographic, occupational, socio-economic and environmental risk factors for SARS-CoV-2 seropositivity. RESULTS: After adjusting for key confounders relative household overcrowding (OR 1.4 [CI 1.1-1.9] p = 0.006), Black, Black British, Caribbean or African ethnicity (OR 1.7 [CI 1.2-2.3] p = 0.003), increasing age (50-60 age group OR 1.8 [CI 1.3-2.4] p=<0.001), lack of access to sick pay (OR 1.8 [CI 1.3-2.4] p=<0.001) and out of hospital contact with COVID-19; staff contact (OR 1.8 [CI 1.4-2.4] p=<0.001), travel contact (OR 1.9 [CI 1.2-3.0] p = 0.008), household contact (OR 1.6 [CI 1.2-2.2] p = 0.002), other contact (OR 1.9 [CI 1.3-3.3] p = 0.029) were significantly associated with SARS-CoV-2 seropositivity. In this paediatric tertiary hospital setting, contact with known infected patients was not significantly associated with seropositivity (OR 1.2 [CI 0.6-2.1] p = 0.651). CONCLUSIONS: Socio-economic 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 paediatric 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, if addressed, 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

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 upon re-exposure. However, current understanding of SARS-CoV-2 humoral dynamics and longevity is conflicting. METHODS: The Co-Stars study prospectively enrolled 3679 healthcare workers to comprehensively characterize the kinetics of SARS-CoV-2 spike (S), receptor-binding-domain (RBD) and nucleoprotein (N) antibodies in parallel. Participants screening seropositive had serial monthly serological testing for a maximum of 7 months with the Mesoscale Discovery Assay. Survival analysis determined the proportion of sero-reversion while two 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 post-symptoms, >95% of participants had detectable S-antibodies compared to 75% with detectable N-antibodies. S-antibody was predicted to remain detectable in 95% of participants until 465 days [95%CI 370-575] 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 correlated strongly with surrogate neutralization in-vitro (R 2=0.72). N-antibodies, however, decayed rapidly with a half-life of 60 days [95%CI 52-68]. CONCLUSIONS: The Co-STAR's study data presented here provides evidence for long-term persistence of neutralizing S-antibodies. This has important implications for the duration of functional immunity following 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 following SARS-CoV-2 infection