ABSTRACT
The impact of variants of concern (VoC) on SARS-CoV-2 viral dynamics remains poorly understood and essentially relies on observational studies subject to various sorts of biases. In contrast, experimental models of infection constitute a powerful model to perform controlled comparisons of the viral dynamics observed with VoC and better quantify how VoC escape from the immune response. Here we used molecular and infectious viral load of 78 cynomolgus macaques to characterize in detail the effects of VoC on viral dynamics. We first developed a mathematical model that recapitulate the observed dynamics, and we found that the best model describing the data assumed a rapid antigen-dependent stimulation of the immune response leading to a rapid reduction of viral infectivity. When compared with the historical variant, all VoC except beta were associated with an escape from this immune response, and this effect was particularly sensitive for delta and omicron variant (p<10-6 for both). Interestingly, delta variant was associated with a 1.8-fold increased viral production rate (p=0.046), while conversely omicron variant was associated with a 14-fold reduction in viral production rate (p<10-6). During a natural infection, our models predict that delta variant is associated with a higher peak viral RNA than omicron variant (7.6 log10 copies/mL 95% CI 6.8 - 8 for delta; 5.6 log10 copies/mL 95% CI 4.8 - 6.3 for omicron) while having similar peak infectious titers (3.7 log10 PFU/mL 95% CI 2.4 - 4.6 for delta; 2.8 log10 PFU/mL 95% CI 1.9 - 3.8 for omicron). These results provide a detailed picture of the effects of VoC on total and infectious viral load and may help understand some differences observed in the patterns of viral transmission of these viruses.
ABSTRACT
The emergence of SARS-CoV-2 variants of concern (VOCs) that escape pre-existing antibody neutralizing responses increases the need for vaccines that target conserved epitopes and induce cross-reactive B- and T-cell responses. We used a computational approach and sequence alignment analysis to design a new-generation subunit vaccine targeting conserved sarbecovirus B- and T-cell epitopes from Spike (S) and Nucleocapsid (N) to antigen-presenting cells expressing CD40 (CD40.CoV2). We demonstrate the potency of CD40.CoV2 to elicit high levels of cross-neutralizing antibodies against SARS-CoV-2, VOCs, and SARS-CoV-1 in K18-hACE2 transgenic mice, associated with improved viral control and survival after challenge. In addition, we demonstrate the potency of CD40.CoV2 in vitro to recall human multi-epitope, functional, and cytotoxic SARS-CoV-2 S- and N-specific T-cell responses that are unaffected by VOC mutations and cross-reactive with SARS-CoV-1 and, to a lesser extent, MERS epitopes. Overall, these findings provide a framework for a pan-sarbecovirus vaccine.
ABSTRACT
The definition of correlates of protection is critical for the development of next generation SARS-CoV-2 vaccine platforms. Here, we propose a new framework for identifying mechanistic correlates of protection based on mathematical modelling of viral dynamics and data mining of immunological markers. The application to three different studies in non-human primates evaluating SARS-CoV-2 vaccines based on CD40-targeting, two-component spike nanoparticle and mRNA 1273 identifies and quantifies two main mechanisms that are a decrease of rate of cell infection and an increase in clearance of infected cells. Inhibition of RBD binding to ACE2 appears to be a robust mechanistic correlate of protection across the three vaccine platforms although not capturing the whole biological vaccine effect. The model shows that RBD/ACE2 binding inhibition represents a strong mechanism of protection which required significant reduction in blocking potency to effectively compromise the control of viral replication. One Sentence SummaryA framework for modelling the immune control of viral dynamics is applied to quantify the effect of several SARS-CoV-2 vaccine platforms and to define mechanistic correlates of protection.
ABSTRACT
Following the paper by Seow et al. published in Nature Microbiology, we reanalyzed the publicly available data using dynamical models of humoral response. The main conclusion is that, from available data, we can demonstrate that the decline of neutralizing antibodies (as measured with ID50) is biphasic, which is compatible with two types of antibody secreting cells (short lived and long lived). We found that lower bound of half life of the long-lived antibody secreting cells is 450 days. Moreover, our model predicts that the neutralizing antibody response could be more durable than suggested (up to 129 days for individuals with no requirement of supplemental oxygen and up to 175 days for others). A result which adds insight on the longevity of immune response.
ABSTRACT
Non-pharmaceutical interventions have been implemented intermittently for more than a year in most countries of the world to mitigate COVID-19 epidemic. In France, while the vaccination campaign is progressing, the French government has decided to remove many public health restrictions such as business closure, lockdowns and curfews. Nonetheless, social distancing, mask wearing, and hand washing (also called barrier gestures) are still recommended. We utilize an age-structured compartmental SEIR model that takes into account SARS-CoV-2 waning immunity, vaccination, and increased transmissibility from variants of concern, to estimate if barrier gestures can be relaxed without causing a resurgence of severe infections. This model assumes that susceptibility to infection is a function of immunity status, which depends on initial infection severity and vaccination status. It is calibrated on confirmed COVID-19 cases from the French surveillance database, and accounts for changes in contact behaviors due to implementation of nation-wide public health policies. We study partial and full relaxation of barrier gestures occurring from August to December 2021 under various immunity duration assumptions. Maintaining application of barrier gestures appears essential to avoid a resurgence of severe infections that would exceed health care capacities, while surmounting vaccine hesitancy represents the key to consider their relaxation. Immunity duration assumptions significantly influence the short-term dynamic of the epidemic which should be considered for further modelling.
ABSTRACT
SummaryIn response to the COVID-19 pandemic caused by SARS-CoV-2, governments have adopted a wide range of non-pharmaceutical interventions (NPI). These include stringent measures such as strict lockdowns, closing schools, bars and restaurants, curfews, and barrier gestures such as mask-wearing and social distancing. Deciphering the effectiveness of each NPI is critical to responding to future waves and outbreaks. To this end, we first develop a dynamic model of the French COVID-19 epidemics over a one-year period. We rely on a global extended Susceptible-Infectious-Recovered (SIR) mechanistic model of infection that includes a dynamic transmission rate over time. Multilevel data across French regions are integrated using random effects on the parameters of the mechanistic model, boosting statistical power by multiplying integrated observation series. We estimate the parameters using a new population-based statistical approach based on a Kalman filter, used for the first time in analysing real-world data. We then fit the estimated time-varying transmission rate using a regression model that depends on the NPIs while accounting for vaccination coverage, the occurrence of variants of concern (VoC), and seasonal weather conditions. We show that all NPIs considered have an independent significant association with transmission rates. In addition, we show a strong association between weather conditions that reduces transmission in summer, and we also estimate increased transmissibility of VoC.
ABSTRACT
We developed a multi-level model of the French COVID-19 epidemic at the regional level. We rely on a global extended Susceptible-Exposed-Infectious-Recovered (SEIR) mechanistic model as a simplified representation of the average epidemic process, with the addition of region specific random effects. Combining several French public datasets on the early dynamics of the epidemic, we estimate region-specific key parameters conditionally on this mechanistic model through Stochastic Approximation Expectation Maximization (SAEM) optimization using Monolix software. We thus estimate the basic reproductive numbers by region before lockdown (with a national average at 2.81 with 95% Confidence Interval [2.58; 3.07]), attack rates (i.e. percentages of infected people) over time per region which range between 1.9% and 9.9% as of May 11th, 2020, and the impact of nationwide lockdown on the infection rate which decreased the transmission rate by 76% towards reproductive numbers ranging from 0.63 to 0.73 at the end of lockdown across regions. These results confirm the low population immunity, the strong effect of the lockdown on the dynamics of the epidemics and the need for further intervention when lifting the lockdown to avoid an epidemic rebound.
