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Preprint Dans Anglais | medRxiv | ID: ppmedrxiv-21266786


Serological surveillance studies of infectious diseases provide population-level estimates of infection and antibody prevalence, generating crucial insight into population-level immunity, risk factors leading to infection, and effectiveness of public health measures. These studies traditionally rely on detection of pathogen-specific antibodies in samples derived from venipuncture, an expensive and logistically challenging aspect of serological surveillance. During the COVID-19 pandemic, guidelines implemented to prevent the spread of SARS-CoV-2 infection made collection of venous blood logistically difficult at a time when SARS-CoV-2 serosurveillance was urgently needed. Dried blood spots (DBS) have generated interest as an alternative to venous blood for SARS-CoV-2 serological applications due to their stability, low cost, and ease of collection; DBS samples can be self-generated via fingerprick by community members and mailed at ambient temperatures. Here, we detail the development of four DBS-based SARS-CoV-2 serological methods and demonstrate their implementation in a large serological survey of community members from 12 cities in the East Bay region of the San Francisco metropolitan area using at- home DBS collection. We find that DBS perform similarly to plasma/serum in enzyme-linked immunosorbent assays and commercial SARS-CoV-2 serological assays. In addition, we show that DBS samples can reliably detect antibody responses months post-infection and track antibody kinetics after vaccination. Implementation of DBS enabled collection of valuable serological data from our study population to investigate changes in seroprevalence over an eight-month period. Our work makes a strong argument for the implementation of DBS in serological studies, not just for SARS-CoV-2, but any situation where phlebotomy is inaccessible.

Preprint Dans Anglais | medRxiv | ID: ppmedrxiv-21265622


BackgroundCOVID-19 convalescent plasma (CCP) was widely used as passive immunotherapy during the first waves of SARS-CoV-2 infection in the US. However, based on observational studies and randomized controlled trials, beneficial effects of CCP were limited, and its use was virtually discontinued early in 2021, in concurrence with increased vaccination rates and availability of monoclonal antibody (mAb) therapeutics. However, as new variants of the SARS-CoV-2 spread, interest in CCP derived from vaccine-boosted CCP donors is resurging. The effect of vaccination of previously infected CCP donors on antibodies against rapidly spreading variants of concern (VOC) is still under investigation. Study Design/MethodsIn this study, paired samples from 11 CCP donors collected before and after vaccination were tested to measure binding antibodies levels and neutralization activity against the ancestral and SARS-CoV-2 variants (Wuhan-Hu-1, B.1.1.7, B.1.351, P.1, D614G, B.1.617.2, B.1.427) on the Ortho Vitros Spike Total Ig and IgG assays, the MSD V-PLEX SARS-CoV-2 Panel 6 arrays for IgG binding and ACE2 inhibition, and variant-specific Spike Reporter Viral Particle Neutralization (RVPN) assays. Results/FindingsBinding and neutralizing antibodies were significantly boosted by vaccination, with several logs higher neutralization for all the variants tested post-vaccination compared to the pre-vaccination samples, with no difference found among the individual variants. DiscussionVaccination of previously infected individuals boosts antibodies including neutralizing activity against all SARS-CoV-2 VOC, including the current spreading delta (B.1.617.2) variant. Animal model and human studies to assess clinical efficacy of vaccine boosted CCP are warranted, especially since 15-20% of current donations in the US are from previously infected vaccine-boosted donors.

Preprint Dans Anglais | medRxiv | ID: ppmedrxiv-21264573


BackgroundAs COVID-19 vaccines continue to be rolled-out, the "double burden" of health disparities in both exposure to infection and vaccination coverage intersect to determine the current and future patterns of infection, immunity, and mortality. Serology provides a unique opportunity to measure biomarkers of infection and vaccination simultaneously, and to relate these metrics to demographic and geographic factors. MethodsLeveraging algorithmically selected residual serum samples from two hospital networks in San Francisco, we sampled 1014 individuals during February 2021, capturing transmission during the first 11 months of the epidemic and the early roll out of vaccination. These samples were tested using two serologic assays: one detecting antibodies elicited by infection, and not by vaccines, and one detecting antibodies elicited by both infection and vaccination. We used Bayesian statistical models to estimate the proportion of the population that was naturally infected and the proportion protected due to vaccination. FindingsWe estimated that the risk of prior infection of Latinx residents was 5.3 (95% CI: 3.2 - 10.3) times greater than the risk of white residents aged 18-64 and that white San Francisco residents over the age of 65 were twice as likely (2.0, 95% CI: 1.1 - 4.6) to be vaccinated as Black residents. We also found socioeconomically deprived zipcodes in the city had high probabilities of natural infections and lower vaccination coverage than wealthier zipcodes. InterpretationUsing a platform we created for SARS-CoV-2 serologic data collection in San Francisco, we characterized and quantified the stark disparities in infection rates and vaccine coverage by demographic groups over the first year of the pandemic. While the arrival of the SARS-CoV-2 vaccine has created a light at the end of the tunnel for this pandemic, ongoing challenges in achieving and maintaining equity must also be considered. FundingNIH, NIGMS, Schmidt Science Fellows in partnership with the Rhodes Trust and the Chan Zuckerberg Biohub.

Preprint Dans Anglais | medRxiv | ID: ppmedrxiv-21262414


SARS-CoV-2 serosurveys can estimate cumulative incidence for monitoring epidemics but require characterization of employed serological assays performance to inform testing algorithm development and interpretation of results. We conducted a multi-laboratory evaluation of 21 commercial high-throughput SARS-CoV-2 serological assays using blinded panels of 1,000 highly-characterized blood-donor specimens. Assays demonstrated a range of sensitivities (96%-63%), specificities (99%-96%) and precision (IIC 0.55-0.99). Durability of antibody detection in longitudinal samples was dependent on assay format and immunoglobulin target, with anti-spike, direct, or total Ig assays demonstrating more stable, or increasing reactivity over time than anti-nucleocapsid, indirect, or IgG assays. Assays with high sensitivity, specificity and durable antibody detection are ideal for serosurveillance. Less sensitive assays demonstrating waning reactivity are appropriate for other applications, including characterizing antibody responses after infection and vaccination, and detection of anamnestic boosting by reinfections and vaccine breakthrough infections. Assay performance must be evaluated in the context of the intended use.

Preprint Dans Anglais | medRxiv | ID: ppmedrxiv-21263139


Serosurveys are a key resource for measuring SARS-CoV-2 cumulative incidence. A growing body of evidence suggests that asymptomatic and mild infections (together making up over 95% of all infections) are associated with lower antibody titers than severe infections. Antibody levels also peak a few weeks after infection and decay gradually. We developed a statistical approach to produce adjusted estimates of seroprevalence from raw serosurvey results that account for these sources of spectrum bias. We incorporate data on antibody responses on multiple assays from a post-infection longitudinal cohort, along with epidemic time series to account for the timing of a serosurvey relative to how recently individuals may have been infected. We applied this method to produce adjusted seroprevalence estimates from five large-scale SARS-CoV-2 serosurveys across different settings and study designs. We identify substantial differences between reported and adjusted estimates of over two-fold in the results of some surveys, and provide a tool for practitioners to generate adjusted estimates with pre-set or custom parameter values. While unprecedented efforts have been launched to generate SARS-CoV-2 seroprevalence estimates over this past year, interpretation of results from these studies requires properly accounting for both population-level epidemiologic context and individual-level immune dynamics.

Preprint Dans Anglais | medRxiv | ID: ppmedrxiv-21256644


BackgroundThe city of Manaus, north Brazil, was stricken by a second epidemic wave of SARS-CoV-2 despite high seroprevalence estimates, coinciding with the emergence of the Gamma (P.1) variant. Reinfections were postulated as a partial explanation for the second surge. However, accurate calculation of reinfection rates is difficult when stringent criteria as two time-separated RT-PCR tests and/or genome sequencing are required. To estimate the proportion of reinfections caused by the Gamma variant during the second wave in Manaus and the protection conferred by previous infection, we analyzed a cohort of repeat blood donors to identify anti-SARS-CoV-2 antibody boosting as a means to infer reinfection. MethodsWe tested serial blood samples from unvaccinated repeat blood donors in Manaus for the presence of anti-SARS-CoV-2 IgG antibody. Donors were required to have three or more donations and at least one donation during each epidemic wave. Donors were tested with two assays that display waning in early convalescence, enabling the detection of reinfection-induced boosting. The serial samples were used to divide donors into six groups defined based on the inferred sequence of infection and reinfection with non-Gamma and Gamma variants. ResultsFrom 3,655 repeat blood donors, 238 met all inclusion criteria, and 223 had enough residual sample volume to perform both serological assays. Using a strict serological definition of reinfection, we found 13.6% (95% CI 7.0% - 24.5%) of all presumed Gamma infections that were observed in 2021 were reinfections. If we also include cases of probable or possible reinfections, these percentages increase respectively to 22.7% (95% CI 14.3% - 34.2%) and 39.3% (95% CI 29.5% - 50.0%). Previous infection conferred a protection against reinfection of 85.3% (95% CI 71.3% - 92.7%), decreasing to respectively 72.5% (95% CI 54.7% - 83.6%) and 39.5% (95% CI 14.1% - 57.8%) if probable and possible reinfections are included. ConclusionsReinfection due to Gamma is common and may play a significant role in epidemics where Gamma is prevalent, highlighting the continued threat variants of concern pose even to settings previously hit by substantial epidemics.

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