Modeling the kinetics of the neutralizing antibody response against SARS-CoV-2 variants after several administrations of Bnt162b2

A multiscale model of the action of a capsid assembly modulator for the treatment of chronic hepatitis B

Chronic hepatitis B virus (HBV) infection is strongly associated with increased risk of liver cancer and cirrhosis. While existing treatments effectively inhibit the HBV life cycle, viral rebound frequently occurs following treatment interruption. Consequently, functional cure rates of chronic HBV infection remain low and there is increased interest in a novel treatment modality, capsid assembly modulators (CAMs). Here, we develop a multiscale mathematical model of CAM treatment in chronic HBV infection. By fitting the model to participant data from a phase I trial of the first-generation CAM vebicorvir, we estimate the drug's dose-dependent effectiveness and identify the physiological mechanisms that drive the observed biphasic decline in HBV DNA and RNA, and mechanistic differences between HBeAg-positive and negative infection. Finally, we demonstrate analytically and numerically that the relative change of HBV RNA more accurately reflects the antiviral effectiveness of a CAM than the relative change in HBV DNA.

Serodynamics: A primer and synthetic review of methods for epidemiological inference using serological data

We present a review and primer of methods to understand epidemiological dynamics and identify past exposures from serological data, referred to as serodynamics. We discuss processing and interpreting serological data prior to fitting serodynamical models, and review approaches for estimating epidemiological trends and past exposures, ranging from serocatalytic models applied to binary serostatus data, to more complex models incorporating quantitative antibody measurements and immunological understanding. Although these methods are seemingly disparate, we demonstrate how they are derived within a common mathematical framework. Finally, we discuss key areas for methodological development to improve scientific discovery and public health insights in seroepidemiology.

Ensemble modeling of SARS-CoV-2 immune dynamics in immunologically naïve rhesus macaques predicts that potent, early innate immune responses drive viral elimination

Introduction

An unprecedented breadth of longitudinal viral and multi-scale immunological data has been gathered during SARS-CoV-2 infection. However, due to the high complexity, non-linearity, multi-dimensionality, mixed anatomic sampling, and possible autocorrelation of available immune data, it is challenging to identify the components of the innate and adaptive immune response that drive viral elimination. Novel mathematical models and analytical approaches are required to synthesize contemporaneously gathered cytokine, transcriptomic, flow cytometry, antibody response, and viral load data into a coherent story of viral control, and ultimately to discriminate drivers of mild versus severe infection.

Methods

We investigated a dataset describing innate, SARS-CoV-2 specific T cell, and antibody responses in the lung during early and late stages of infection in immunologically naïve rhesus macaques. We used multi-model inference and ensemble modeling approaches from ecology and weather forecasting to compare and combine various competing models.

Results and discussion

Model outputs suggest that the innate immune response plays a crucial role in controlling early infection, while SARS-CoV-2 specific CD4+ T cells correspond to later viral elimination, and anti-spike IgG antibodies do not impact viral dynamics. Among the numerous genes potentially contributing to the innate response, we identified IFI27 as most closely linked to viral load decline. A 90% knockdown of the innate response from our validated model resulted in a ~10-fold increase in peak viral load during infection. Our approach provides a novel methodological framework for future analyses of similar complex, non-linear multi-component immunologic data sets.

Vaccine and antiviral drug promise for preventing post-acute sequelae of COVID-19, and their combination for its treatment

Introduction

Most healthy individuals recover from acute SARS-CoV-2 infection, whereas a remarkable number continues to suffer from unexplained symptoms, known as Long COVID or post-acute COVID-19 syndrome (PACS). It is therefore imperative that methods for preventing and treating the onset of PASC be investigated with the utmost urgency.

Methods

A mathematical model of the immune response to vaccination and viral infection with SARS-CoV-2, incorporating immune memory cells, was developed.

Results and discussion

Similar to our previous model, persistent infection was observed by the residual virus in the host, implying the possibility of chronic inflammation and delayed recovery from tissue injury. Pre-infectious vaccination and antiviral medication administered during onset can reduce the acute viral load; however, they show no beneficial effects in preventing persistent infection. Therefore, the impact of these treatments on the PASC, which has been clinically observed, is mainly attributed to their role in preventing severe tissue damage caused by acute viral infections. For PASC patients with persistent infection, vaccination was observed to cause an immediate rapid increase in viral load, followed by a temporary decrease over approximately one year. The former was effectively suppressed by the coadministration of antiviral medications, indicating that this combination is a promising treatment for PASC.

Modulation of T-Cell-Dependent Humoral Immune Response to Influenza Vaccine by Multiple Antioxidant/Immunomodulatory Micronutrient Supplementation

Notwithstanding prevalence gaps in micronutrients supporting immune functions, the significance of their deficits/supplementation for the efficacy of vaccines is underinvestigated. Thus, the influence of supplementation combining vitamins C and D, zinc, selenium, manganese, and N-acetyl cysteine on immune correlates/surrogates of protection conferred by a quadrivalent influenza vaccine (QIV) in mice was investigated. The supplementation starting 5 days before the first of two QIV injections given 28 days apart increased the serum titres of total and neutralizing IgG against each of four influenza strains from QIV. Accordingly, the frequencies of germinal center B cells, follicular CD4+ T helper (Th) cells, and IL-21-producing Th cells increased in secondary lymphoid organs (SLOs). Additionally, the supplementation improved already increased IgG response to the second QIV injection by augmenting not only neutralizing antibody production, but also IgG2a response, which is important for virus clearance, through favoring Th1 differentiation as indicated by Th1 (IFN-γ)/Th2 (IL-4) signature cytokine level ratio upon QIV restimulation in SLO cell cultures. This most likely partly reflected antioxidant action of the supplement as indicated by splenic redox status analyses. Thus, the study provides a solid scientific background for further research aimed at repurposing the use of this safe and inexpensive micronutrient combination to improve response to the influenza vaccine.

Estimating the population effectiveness of interventions against COVID-19 in France: A modelling study

BACKGROUND

Non-pharmaceutical interventions (NPIs) and vaccines have been widely used to manage the COVID-19 pandemic. However, uncertainty persists regarding the effectiveness of these interventions due to data quality issues, methodological challenges, and differing contextual factors. Accurate estimation of their effects is crucial for future epidemic preparedness.

METHODS

To address this, we developed a population-based mechanistic model that includes the impact of NPIs and vaccines on SARS-CoV-2 transmission and hospitalization rates. Our statistical approach estimated all parameters in one step, accurately propagating uncertainty. We fitted the model to comprehensive epidemiological data in France from March 2020 to October 2021. With the same model, we simulated scenarios of vaccine rollout.

RESULTS

The first lockdown was the most effective, reducing transmission by 84 % (95 % confidence interval (CI) 83-85). Subsequent lockdowns had diminished effectiveness (reduction of 74 % (69-77) and 11 % (9-18), respectively). A 6 pm curfew was more effective than one at 8 pm (68 % (66-69) vs. 48 % (45-49) reduction), while school closures reduced transmission by 15 % (12-18). In a scenario without vaccines before November 2021, we predicted 159,000 or 168 % (95 % prediction interval (PI) 70-315) more deaths and 1,488,000 or 300 % (133-492) more hospitalizations. If a vaccine had been available after 100 days, over 71,000 deaths (16,507-204,249) and 384,000 (88,579-1,020,386) hospitalizations could have been averted.

CONCLUSION

Our results highlight the substantial impact of NPIs, including lockdowns and curfews, in controlling the COVID-19 pandemic. We also demonstrate the value of the 100 days objective of the Coalition for Epidemic Preparedness Innovations (CEPI) initiative for vaccine availability.

Neutralizing Antibody Levels as a Correlate of Protection Against SARS-CoV-2 Infection: A Modeling Analysis

Although anti-severe acute respiratory syndrome-coronavirus 2 antibody kinetics have been described in large populations of vaccinated individuals, we still poorly understand how they evolve during a natural infection and how this impacts viral clearance. For that purpose, we analyzed the kinetics of both viral load and neutralizing antibody levels in a prospective cohort of individuals during acute infection with alpha variant. Using a mathematical model, we show that the progressive increase in neutralizing antibodies leads to a shortening of the half-life of both infected cells and infectious viral particles. We estimated that the neutralizing activity reached 90% of its maximal level within 11 days after symptom onset and could reduce the half-life of both infected cells and circulating virus by a 6-fold factor, thus playing a key role to achieve rapid viral clearance. Using this model, we conducted a simulation study to predict in a more general context the protection conferred by pre-existing neutralization titers, due to either vaccination or prior infection. We predicted that a neutralizing activity, as measured by 50% effective dose > 103 , could reduce by 46% the risk of having viral load detectable by standard polymerase chain reaction assays and by 98% the risk of having viral load above the threshold of infectiousness. Our model shows that neutralizing activity could be used to define correlates of protection against infection and transmission.

Prediction of long-term humoral response induced by the two-dose heterologous Ad26.ZEBOV, MVA-BN-Filo vaccine against Ebola

The persistence of the long-term immune response induced by the heterologous Ad26.ZEBOV, MVA-BN-Filo two-dose vaccination regimen against Ebola has been investigated in several clinical trials. Longitudinal data on IgG-binding antibody concentrations were analyzed from 487 participants enrolled in six Phase I and Phase II clinical trials conducted by the EBOVAC1 and EBOVAC2 consortia. A model based on ordinary differential equations describing the dynamics of antibodies and short- and long-lived antibody-secreting cells (ASCs) was used to model the humoral response from 7 days after the second vaccination to a follow-up period of 2 years. Using a population-based approach, we first assessed the robustness of the model, which was originally estimated based on Phase I data, against all data. Then we assessed the longevity of the humoral response and identified factors that influence these dynamics. We estimated a half-life of the long-lived ASC of at least 15 years and found an influence of geographic region, sex, and age on the humoral response dynamics, with longer antibody persistence in Europeans and women and higher production of antibodies in younger participants.