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Given widespread use of spike antibody in generating coronavirus disease vaccines, SARS-CoV-2 nucleocapsid antibodies are increasingly used to indicate previous infection in serologic surveys. However, longitudinal kinetics and seroreversion are poorly defined. We found substantial seroreversion of nucleocapsid total immunoglobulin, underscoring the need to account for seroreversion in seroepidemiologic studies.

Ebola virus disease remains a threat in different Sub-Saharan African countries more particularly in the Democratic Republic of Congo, where persistent outbreaks are driven by human populations living in close proximity to animal reservoirs. While vaccines like Ad26.ZEBOV and MVA-BN-Filo are safe and immunogenic, the dynamics of antibody responses after the two-dose regimen and booster vaccination are not fully understood. Within-host mathematical models offer valuable insights into disease dynamics and waning immunity, but data-driven mechanistic models of antibody kinetics remain scarce. The present study seeks to elucidate the processes involved in antibody kinetics after the two-dose vaccine regimen with Ad26.ZEBOV and MVA-BN-Filo vaccines, followed by a booster dose vaccination with Ad26.ZEBOV, addressing challenges in inference for and implementation of within-host approaches. By integrating established theoretical frameworks with recent empirical findings on antibody kinetics following Ebola vaccination, we illustrate how mechanistic modeling can enhance and refine our understanding of antibody dynamics. Specifically, we emphasize the distinction in the half-life of antibody responses at different vaccination time points and explore the role of vaccine antigens in eliciting an immunological response through the formation and activation of germinal center mediated response. Careful consideration was given to the development of a model that is both interpretable and practically feasible. The half-life of the antibody response was found to be longer after booster vaccination compared to after the second vaccine dose, indicating a steadier decay process. This may be due to the improved quality of antibodies generated, the formation of memory B cells sustaining antibody production, and antigen-antibody binding. This study highlights critical considerations for implementing within-host mechanistic models and the need for robust data to accurately estimate model parameters. Further research is essential to elucidate the decay dynamics of memory B cells and long-lived plasma cells, as these processes play a pivotal role in sustaining antibody-mediated immunity.

Epidemiological studies suggest that heterogeneity in influenza vaccine antibody response can be associated with specific host factors, including pre-vaccination immune status, age, gender, and vaccination history. However, the pattern of reported associations varies between studies. To better understand the underlying influences on antibody responses, we combined host factors and vaccine-induced in-host antibody kinetics from a cohort study conducted across multiple seasons with a unified analysis framework. We developed a flexible individual-level Bayesian model to estimate associations and interactions between host factors, including pre-vaccine HAI titre, age, sex, vaccination history and study setting, and vaccine-induced HAI titre antibody boosting and waning. We applied the model to derive population-level and individual effects of post-vaccine antibody kinetics for A(H1N1) and A(H3N2) influenza subtypes. We found that post-vaccine HAI titre dynamics were significantly influenced by pre-vaccination HAI titre and vaccination history and that lower pre-vaccination HAI titre results in longer durations of seroprotection (HAI titre equal to 1:40 or higher). We also observed that the effect of vaccination history on antibody boosting was stronger for egg-grown A(H1N1) vaccinating strains in individuals with higher pre-vaccination HAI titres, whereas this effect diminished for egg-grown A(H3N2) vaccinating strains. Consequently, for cell-grown A(H1N1), our inference finds that the expected duration of seroprotection post-vaccination was 171 (95 % Posterior Predictive Interval[PPI] 128–220) and 159 (95 % PPI 120–200) days longer for those who are infrequently vaccinated (<2 vaccines in last five years) compared to those who are frequently vaccinated (2 or more vaccines in the last five years) at pre-vaccination HAI titre values of 1:10 and 1:20 respectively. In addition, we found significant differences in the empirical distributions that describe the individual-level duration of seroprotection for A(H1N1) cell-grown strains. In future, studies that rely on serological endpoints should include the impact of pre-vaccine HAI titre and prior vaccination status on seropositivity and seroconversion estimates, as these can significantly influence an individual's post-vaccination antibody kinetics.

Background & objectives: The global pandemic caused by SARS-CoV-2 virus has challenged public health system worldwide due to the unavailability of approved preventive and therapeutic options. Identification of neutralizing antibodies (NAb) and understanding their role is important. However, the data on kinetics of NAb response among COVID-19 patients are unclear. To understand the NAb response in COVID-19 patients, we compared the findings of microneutralization test (MNT) and plaque reduction neutralization test (PRNT) for the SARS-CoV-2. Further, the kinetics of NAb response among COVID-19 patients was assessed. Methods: A total of 343 blood samples (89 positive, 58 negative for SARS-CoV-2 and 17 cross-reactive and 179 serum from healthy individuals) were collected and tested by MNT and PRNT. SARS-CoV-2 virus was prepared by propagating the virus in Vero CCL-81 cells. The intra-class correlation was calculated to assess the correlation between MNT and PRNT. The neutralizing endpoint as the reduction in the number of plaque count by 90 per cent (PRNT90) was also calculated. Results: The analysis of MNT and PRNT quantitative results indicated that the intra-class correlation was 0.520. Of the 89 confirmed COVID-19 patients, 64 (71.9%) showed NAb response. Interpretation & conclusions: The results of MNT and PRNT were specific with no cross-reactivity. In the early stages of infection, the NAb response was observed with variable antibody kinetics. The neutralization assays can be used for titration of NAb in recovered/vaccinated or infected COVID-19 patients.

Durability of SARS-CoV-2 Spike antibody responses after infection provides information relevant to understanding protection against COVID-19 in humans. We report the results of a sequential evaluation of anti-SARS-CoV-2 antibodies in convalescent patients with a median follow-up of 14 months (range 12.4-15.4) post first symptom onset. We report persistence of antibodies for all four specificities tested [Spike, Spike Receptor Binding Domain (Spike-RBD), Nucleocapsid, Nucleocapsid RNA Binding Domain (N-RBD)]. Anti-Spike antibodies persist better than anti-Nucleocapsid antibodies. The durability analysis supports a bi-phasic antibody decay with longer half-lives of antibodies after 6 months and antibody persistence for up to 14 months. Patients infected with the Wuhan (WA1) strain maintained strong cross-reactive recognition of Alpha and Delta Spike-RBD but significantly reduced binding to Beta and Mu Spike-RBD. Sixty percent of convalescent patients with detectable WA1-specific NAb also showed strong neutralization of the Delta variant, the prevalent strain of the present pandemic. These data show that convalescent patients maintain functional antibody responses for more than one year after infection, suggesting a strong long-lasting response after symptomatic disease that may offer a prolonged protection against re-infection. One patient from this cohort showed strong increase of both Spike and Nucleocapsid antibodies at 14 months post-infection indicating SARS-CoV-2 re-exposure. These antibodies showed stronger cross-reactivity to a panel of Spike-RBD including Beta, Delta and Mu and neutralization of a panel of Spike variants including Beta and Gamma. This patient provides an example of strong anti-Spike recall immunity able to control infection at an asymptomatic level. Together, the antibodies from SARS-CoV-2 convalescent patients persist over 14 months and continue to maintain cross-reactivity to the current variants of concern and show strong functional properties.

•Point estimates of the half-life of transplacental anti-GBS IgG were 23–28 days.•Strong correlation between IgG concentrations at birth and one month of age.•Antibody kinetics may help in defining a correlate of protection against GBS LOD. Capsular polysaccharide (CPS) serotype-specific Immunoglobulin G (IgG) in cord blood has been proposed as a correlate of protection against invasive Group B Streptococcus (iGBS) disease. Although protective levels are required in infants throughout the window of vulnerability up to 3 months of age, little is known regarding the kinetics of GBS-specific IgG over this period. We enrolled 33 healthy infants born to mothers colonized with GBS. We collected cord blood and infant blood samples either at one (21–35 days), two (49–63 days), or three months of age (77–91 days). We measured GBS serotype-specific CPS IgG concentrations and calculated the decay rate using a mixed-effects model. We further explored whether the antibody kinetics were affected by common maternal and infant factors and estimated the correlation between IgG concentration at birth and one, two, and three months of age. The half-life estimate of IgG concentration for homologous and non-homologous GBS serotypes in paired samples with detectable IgG levels at both time points was 27.4 (95 % CI: 23.5–32.9) days. The decay rate did not vary by maternal age (p = 0.7), ethnicity (p = 0.1), gravida (p = 0.1), gestation (p = 0.7), and infant sex (p = 0.1). Predicted IgG titres above the assay lower limit of quantification on day 30 strongly correlated with titres at birth (Spearman correlation coefficient 0.71 [95 % CI: 0.60–0.80]). Our results provide a basis for future investigations into the use of antibody kinetics in defining a serocorrelate of protection against late-onset iGBS disease.

Background A firm understanding of SARS-CoV-2 hybrid immunity is crucial for our ongoing efforts to protect people from severe and fatal disease and assess population vulnerability to emerging novel variants. As many components of the immune response are unobserved and complex to investigate, some ambiguities and unanswered questions remain about hybrid immunity to COVID-19, such as the duration of the antibody response in individuals. Methods To address this, we evaluated longitudinal data that spanned up to 21 months from 52 SARS-CoV-2 naive individuals and 88 SARS-CoV-2 recovered individuals. We further separated individuals according to whether they received an mRNA or non-mRNA vaccine for their primary two-dose vaccinations. A hierarchical Bayesian framework was used to fit the parameters of mono-phasic exponential decay and bi-phasic exponential decay models to the observed data to estimate the magnitude and half-life of the spike-specific and receptor-binding domain (RBD)-specific IgG responses. Results Results from both our mono-phasic and bi-phasic exponential decay models estimate that the median half-life of the spike-specific and RBD-specific IgG response in individuals with hybrid immunity is almost double that of naive individuals who were only vaccinated. Recovered mRNA recipients were estimated through the mono-phasic decay model to have a median IgG response half-life of 448 days (95% CrI: [375.08, 547.54]) to spike antigen, compared to an estimated 222 days (95% CrI: [179.90, 286.62]) for naive mRNA recipients. Posterior estimates from the bi-phasic exponential decay model show that recovered individuals who received mRNA vaccinations had a median IgG response half-life of 810 days (95% CrI: [650.91, 1031.63]) to spike antigen, compared to 451 days (95% CrI: [336.81, 618.14]) for naive mRNA recipients. A similar pattern is seen in non-mRNA vaccine recipients, with IgG response half-lives differing slightly. Our results show that, across different model assumptions, individuals with hybrid immunity have an IgG response half-life that is considerably greater than that of individuals with only infection- or vaccine-induced immunity. Conclusions Our work provides important insight into the longevity of the IgG response to SARS-CoV-2 in individuals with hybrid immunity and can guide effective immunisation approaches to maintain and improve population-level protection.

Within-host models describe the dynamics of immune cells when encountering a pathogen, and how these dynamics can lead to an individual-specific immune response. This systematic review aims to summarize which within-host methodology has been used to study and quantify antibody kinetics after infection or vaccination. In particular, we focus on data-driven and theory-driven mechanistic models. PubMed and Web of Science databases were used to identify eligible papers published until May 2022. Eligible publications included those studying mathematical models that measure antibody kinetics as the primary outcome (ranging from phenomenological to mechanistic models). We identified 78 eligible publications, of which 8 relied on an Ordinary Differential Equations (ODEs)-based modelling approach to describe antibody kinetics after vaccination, and 12 studies used such models in the context of humoral immunity induced by natural infection. Mechanistic modeling studies were summarized in terms of type of study, sample size, measurements collected, antibody half-life, compartments and parameters included, inferential or analytical method, and model selection. Despite the importance of investigating antibody kinetics and underlying mechanisms of (waning of) the humoral immunity, few publications explicitly account for this in a mathematical model. In particular, most research focuses on phenomenological rather than mechanistic models. The limited information on the age groups or other risk factors that might impact antibody kinetics, as well as a lack of experimental or observational data remain important concerns regarding the interpretation of mathematical modeling results. We reviewed the similarities between the kinetics following vaccination and infection, emphasising that it may be worth translating some features from one setting to another. However, we also stress that some biological mechanisms need to be distinguished. We found that data-driven mechanistic models tend to be more simplistic, and theory-driven approaches lack representative data to validate model results.

The immune response to dengue virus (DENV) infection is complex and not fully understood. Using longitudinal data from 181 children with dengue in Thailand who were followed for up to 3 years, we describe neutralizing antibody kinetics following symptomatic DENV infection. We observed that antibody titers varied by serotype, homotypic vs heterotypic responses, and primary versus postprimary infections. The rates of change in antibody titers over time varied between primary and postprimary responses. For primary infections, titers increased from convalescence to 6 months. By comparing homotypic and heterotypic antibody titers, we saw an increase in type specificity from convalesence to 6 months for primary DENV3 infections but not primary DENV1 infections. In postprimary cases, there was a decrease in titers from convalescence up until 6 months after infection. Beginning 1 year after both primary and postprimary infections, there was evidence of increasing antibody titers, with greater increases in children with lower titers, suggesting that antibody titers were boosted due to infection and that higher levels of neutralizing antibody may be more likely to confer a sterilizing immune response. These findings may help to model virus transmission dynamics and provide baseline data to support the development of vaccines and therapeutics.

Understanding and mitigating SARS-CoV-2 transmission hinges on antibody and viral RNA data that inform exposure and shedding, but extensive variation in assays, study group demographics and laboratory protocols across published studies confounds inference of true biological patterns. Our meta-analysis leverages 3214 datapoints from 516 individuals in 21 studies to reveal that seroconversion of both IgG and IgM occurs around 12 days post-symptom onset (range 1–40), with extensive individual variation that is not significantly associated with disease severity. IgG and IgM detection probabilities increase from roughly 10% at symptom onset to 98–100% by day 22, after which IgM wanes while IgG remains reliably detectable. RNA detection probability decreases from roughly 90% to zero by day 30, and is highest in feces and lower respiratory tract samples. Our findings provide a coherent evidence base for interpreting clinical diagnostics, and for the mathematical models and serological surveys that underpin public health policies.