Estimating the population effectiveness of interventions against COVID-19 in France: a modelling study (preprint)

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 6pm 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 194% (95% prediction interval (PI) 74-424) more deaths and 1,488,000 or 340% (136-689) 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 CEPI initiative for vaccine availability.

Impact of variants of concern on SARS-CoV-2 viral dynamics in non-human primates. (preprint)

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.

Design, immunogenicity, and efficacy of a pan-sarbecovirus dendritic-cell targeting vaccine (preprint)

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. Keywords: COVID-19, SARS-CoV-2, vaccine, pre-clinical model, sarbecoviruses

SARS-CoV-2 mechanistic correlates of protection: insight from modelling response to vaccines (preprint)

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.

Modeling brings additional insights into the kinetics of SARS-CoV-2 neutralizing antibody (preprint)

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.

Barrier gesture relaxation during vaccination campaign in France: modelling impact of waning immunity (preprint)

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.

Using population based Kalman estimator to model COVID-19 epidemics in France: estimating the burden of SARS-CoV-2 and the effects of NPI. (preprint)

In response to the ongoing COVID-19 pandemics caused by SARS-CoV-2, governments are taking a wide range of non-pharmaceutical interventions (NPI). These measures include interventions as stringent as strict lockdown but also school closure, bars and restaurants closure, curfews and barrier gestures. Disentangling the effectiveness of each NPI is crucial to inform response to future outbreaks. To this end, we first develop a multi-level estimation of the French COVID-19 epidemic over a period of one year. We rely on a global extended Susceptible-Infectious-Recovered (SIR) mechanistic model of the infection including a dynamics over time for the transmission rate containing a Wiener process accounting for modeling error. Random effects are integrated by following an innovative population approach based on Kalman-type filter where the log-likelihood functional couples data across French regions. We then fit the estimated time-varying transmission rate using a regression model depending on NPI while accounting for the vaccination coverage, the apparition of variants of concern (VOC) and the seasonal weather conditions. We show that all NPI considered have an independent significant effect on the transmission rate. We additionally demonstrate a strong effect of weather condition, decreasing the transmission during the summer period, and also estimated an increased transmissibility of VOC.

Targeting SARS-CoV-2 receptor-binding domain to cells expressing CD40 improves protection to infection in convalescent macaques (preprint)

Controlling the circulation of the recently emerged SARS-CoV-2 in the human populations requires massive vaccination campaigns. Achieving sufficient worldwide vaccination coverage will require additional approaches to first generation of approved viral vector and mRNA vaccines. Subunit vaccines have excellent safety and efficacy records and may have distinct advantages, in particular when immunizing individuals with vulnerabilities or when considering the vaccination of children and pregnant women.. We have developed a new generation of subunit vaccines with enhanced immunogenicity by the targeting of viral antigens to CD40-expressing antigen-presenting cells, thus harnessing their intrinsic immune-stimulant properties. Here, we demonstrate that targeting the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein to CD40 (αCD40.RBD) induces significant levels of specific T and B cells, with a long-term memory phenotype, in a humanized mouse model. In addition, we demonstrate that a single dose of the αCD40.RBD vaccine, injected without adjuvant, is sufficient to boost a rapid increase in neutralizing antibodies in convalescent non-human primates (NHPs) exposed six months previously to SARS-CoV-2. Such vaccination thus significantly improved protection against a new high-dose virulent challenge versus that in non-vaccinated convalescent animals. Viral dynamics modelling showed the high efficiency of the vaccine at controlling the viral dissemination.

EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models (preprint)

Epidemiologists model the dynamics of epidemics in order to propose control strategies based on pharmaceutical and non-pharmaceutical interventions (contact limitation, lock down, vaccination, etc). Hand-designing such strategies is not trivial because of the number of possible interventions and the difficulty to predict long-term effects. This task can be cast as an optimization problem where state-of-the-art machine learning algorithms such as deep reinforcement learning, might bring significant value. However, the specificity of each domain -- epidemic modelling or solving optimization problem -- requires strong collaborations between researchers from different fields of expertise. This is why we introduce EpidemiOptim, a Python toolbox that facilitates collaborations between researchers in epidemiology and optimization. EpidemiOptim turns epidemiological models and cost functions into optimization problems via a standard interface commonly used by optimization practitioners (OpenAI Gym). Reinforcement learning algorithms based on Q-Learning with deep neural networks (DQN) and evolutionary algorithms (NSGA-II) are already implemented. We illustrate the use of EpidemiOptim to find optimal policies for dynamical on-off lock-down control under the optimization of death toll and economic recess using a Susceptible-Exposed-Infectious-Removed (SEIR) model for COVID-19. Using EpidemiOptim and its interactive visualization platform in Jupyter notebooks, epidemiologists, optimization practitioners and others (e.g. economists) can easily compare epidemiological models, costs functions and optimization algorithms to address important choices to be made by health decision-makers.

Population modeling of early COVID-19 epidemic dynamics in French regions and estimation of the lockdown impact on infection rate (preprint)

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.