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Human papillomavirus (HPV) infections drive one in twenty new cancer cases. Despite the potential for improving treatment, screening, and vaccination strategies, little is known as to why most HPV infections clear spontaneously within two years. To untangle the dynamics of these non-persisting infections, we performed a combined quantitative analysis of virological, immunological, and clinical data from an original longitudinal cohort of 189 women with high temporal resolution. We find that HPV viral load reaches a plateau within two months, and clears within a median time of 14 months. Furthermore, we identify immune correlates associated with infection clearance, especially TCR-gamma-delta cells. Our results open new perspectives for understanding the frontier between acute and chronic infections and for controlling HPVassociated diseases.

The present study addresses the first steps of development and validation of a coupled Finite Volume-Blade Element Model (FV-BEM) simulation tool dedicated to offshore wind turbine farm modeling. The fluid domain is solved using the incompressible formulation of the CFD solver Grid-flow. The turbines are taken into account using FAST (from NREL) and their effects are imposed into the fluid domain through an actuator line model (ALM) for which specific enhancements are proposed. The Grid-flow solver and its two-way coupling with the aero-elastic modules from FAST is introduced and detailed. The simulation of the case of two in-line wind turbines using the FV-BEM coupling proposed is presented, together with comparisons against experimental results for validation purposes. Finally, a discussion on performances, advantages and limitations of the formulation proposed is provided.

The vaginal ecosystem is a key component of women's health. It also represents an ideal system for ecologists to investigate the consequence of perturbations on species diversity and emerging properties between organizational levels. Here, we study how exposure to different types of menstrual products is linked to microbial, immunological, demographic, and behavioural measurements in a cohort of young adult women who reported using more often tampons (n = 107) or menstrual cups (n = 31). We first found that cup users were older and smoked less than tampon users. When analysing health indicators, we detected potential associations between cups use reporting and fungal genital infection. A multivariate analysis confirmed that in our cohort, reporting using cups over tampons was associated with the higher odds ratio to report a fungal genital infection diagnosis by a medical doctor within the last 3 months. We did not detect significant differences between groups in terms of their bacterial vaginal microbiota composition and found marginal differences in the level of expression of 20 cytokines. However, a multivariate analysis of these biological data identified some level of clustering based on the menstrual product type preferred (cups or tampons). These results suggest that exposure to different types of menstrual products could influence menstrual health. Larger studies and studies with a more powered setting are needed to assess the robustness of these associations and identify causal mechanisms.

International audience; Infectious disease transmission patterns in some outbreaks can be more heterogeneous than in others, with striking effects on the way epidemics unfold. Some studies show that the biological sources of heterogeneity may matter, but they tend to do so without controlling for the overall heterogeneity in the number of secondary cases caused by an infection. Here, we control for this important bias to explore the role of individual variation in infection duration and transmission rate on parasite emergence and spread. We simulate outbreaks using a stochastic SIR model, with and without parasite evolution. Consistently with existing studies, we show that the variance in the number of secondary infections has the strongest effect on outbreak emergence probability but has little effect on the epidemic dynamic once emergence is certain. The origin of heterogeneity also affects the probability of emergence, but its more striking effects are about properties of epidemics that do emerge. In particular, assuming more realistic variances in infection duration distributions lead to faster outbreaks and a higher peak of incidence. When the parasite requires evolutionary changes to be able to spread, the impact of heterogeneity depends on the underlying evolutionary model. If the parasite evolves within the host, decreasing the infection duration variance decreases the probability of emergence. These results show that using realistic distributions for infection duration is necessary to accurately capture the effect of individual heterogeneity on epidemiological dynamics, which has implications for the monitoring and control of infectious diseases, as well as data collection.

Since early 2021, SARS-CoV-2 variants of concern (VOCs) have been causing epidemic rebounds in many countries. Their properties are well characterized at the epidemiological level but the potential underlying within-host determinants remain poorly understood. We analyze a longitudinal cohort of 6944 individuals with 14 304 cycle threshold (Ct) values of reverse-transcription quantitative polymerase chain reaction (RT-qPCR) VOC screening tests performed in the general population and hospitals in France between February 6 and August 21, 2021. To convert Ct values into numbers of virus copies, we performed an additional analysis using droplet digital PCR (ddPCR). We find that the number of viral genome copies reaches a higher peak value and has a slower decay rate in infections caused by Alpha variant compared to that caused by historical lineages. Following the evidence that viral genome copies in upper respiratory tract swabs are informative on contagiousness, we show that the kinetics of the Alpha variant translate into significantly higher transmission potentials, especially in older populations. Finally, comparing infections caused by the Alpha and Delta variants, we find no significant difference in the peak viral copy number. These results highlight that some of the differences between variants may be detected in virus load variations.

ObjectiveTo determine if the use of menstrual cups rather than tampons is associated with more or less health risk.DesignAnalysing biological, demographic, and behavioural data in a cohort of women who reported using mostly tampons (n = 81) or menstrual cups (n = 22).SettingA cross-sectional analysis using the inclusion data of a single centre longitudinal study.Population149 women from 18 to 25 years old living in the area of Montpellier (France) who reported having at least one new sexual partner over the last year.MethodsStatistical modelling (mainly binomial regression models and factor analyses of mixed data).Main Outcome MeasuresSelf-reported data from questionnaires (fungal infection, urinary tract infection, stress level) and biological data (HPV screening, vaginal microbiota profiling, circulating antibodies titration, and local cytokine concentrations).ResultsWe identify an increased risk of reporting fungal infections for women using menstrual cups over tampons. We do not detect significant differences in terms of vaginal microbiota composition or local cytokines expression profile but find that women fall into two different clusters in a factor analysis of mixed data depending on the type of menstrual product they use more (cups or tampons).ConclusionsThese results point to potential health risks in the use of menstrual cups and differences in local vaginal environments. In-depth studies are needed to better understand potential associations between menstrual product use and women’s health.FundingEuropean Research Council (EVOLPROOF, grant 648963)EthicsThe PAPCLEAR study ClinicalTrials.gov identifier is NCT02946346.Tweetable abstractA cross-sectional study finds a significant association between menstrual cup use and fungal infection risk.

Since early 2021, SARS-CoV-2 variants of concern (VOCs) have been causing epidemic rebounds in many countries. Their properties are well characterised at the epidemiological level but the potential underlying within-host determinants remain poorly understood. We analyse a longitudinal cohort of 6,944 individuals with 14,304 cycle threshold (Ct) values of qPCR VOC screening tests performed in the general population and hospitals in France between February 6 and August 21, 2021. To convert Ct values into numbers of virus copies, we performed an additional analysis using droplet digital PCR (ddPCR). We find that the number of viral genome copies reaches a higher peak value and has a slower decay rate in infections caused by Alpha variant compared to that caused by historical lineages. Following the evidence that viral genome copies in upper respiratory tract swabs are informative on contagiousness, we show that the kinetics of the Alpha variant translate into significantly higher transmission potentials, especially in older populations. Finally, comparing infections caused by the Alpha and Delta variants, we find no significant difference in the peak viral copy number. These results highlight that some of the differences between variants may be detected in virus load variations.

France was one of the first countries to be reached by the COVID-19 pandemic. Here, we analyse 196 SARS-Cov-2 genomes collected between Jan 24 and Mar 24 2020, and perform a phylodynamics analysis. In particular, we analyse the doubling time, reproduction number (ℛt) and infection duration associated with the epidemic wave that was detected in incidence data starting from Feb 27. Different models suggest a slowing down of the epidemic in Mar, which would be consistent with the implementation of the national lock-down on Mar 17. The inferred distributions for the effective infection duration andℛtare in line with those estimated from contact tracing data. Finally, based on the available sequence data, we estimate that the French epidemic wave originated between mid-Jan and early Feb. Overall, this analysis shows the potential to use sequence genomic data to inform public health decisions in an epidemic crisis context and calls for further analyses with denser sampling.

International audience; SARS-CoV-2 virus has spread over the world rapidly creating one of the largest pandemics ever. The absence of immunity, presymptomatic transmission, and the relatively high level of virulence of the COVID-19 infection led to a massive flow of patients in intensive care units (ICU). This unprecedented situation calls for rapid and accurate mathematical models to best inform public health policies. We develop an original parsimonious discrete-time model that accounts for the effect of the age of infection on the natural history of the disease. Analysing the ongoing COVID-19 in France as a test case, through the publicly available time series of nationwide hospital mortality and ICU activity, we estimate the value of the key epidemiological parameters and the impact of lock-down implementation delay. This work shows that including memory-effects in the modelling of COVID-19 spreading greatly improves the accuracy of the fit to the epidemiological data. We estimate that the epidemic wave in France started on Jan 20 [Jan 12, Jan 28] (95% likelihood interval) with a reproduction number initially equal to 2.99 [2.59, 3.39], which was reduced by the national lock-down started on Mar 17 to 24 [21, 27] of its value. We also estimate that the implementation of the latter a week earlier or later would have lead to a difference of about respectively −13k and +50k hospital deaths by the end of lock-down. The present parsimonious discrete-time framework constitutes a useful tool for now-and forecasting simultaneously community incidence and ICU capacity strain.

International audience; Dans la lignée des épidémies récentes des virus Ebola et Zika, la pandémie de COVID-19 a donné lieu à une avalanche de données génomiques. Celles-ci ont permis de mieux comprendre l'origine de ce virus, de dater son apparition en Chine mais aussi en France et d'analyser la propagation de l'épidémie grâce aux techniques issues du champ émergent qu'est la phylodynamique.

SARS-Cov-2 virus has spread over the world creating one of the fastest pandemics ever. The absence of immunity, asymptomatic transmission, and the relatively high level of virulence of the COVID-19 infection it causes led to a massive flow of patients in intensive care units (ICU). This unprecedented situation calls for rapid and accurate mathematical models to best inform public health policies. We develop an original parsimonious model that accounts for the effect of the age of infection on the natural history of the disease. Analysing the ongoing COVID-19 in France, we estimate the value of the key epidemiological parameters, such as the basic reproduction number , and the efficiency of the national control strategy. We then use our deterministic model to explore several scenarios posterior to lock-down lifting and compare the efficiency of non pharmaceutical interventions (NPI) described in the literature.

Travail du groupe de modélisation de l'équipe ETE

The present study addresses the first steps of development and validation of a coupled CFD-BE (Blade Element) simulation tool dedicated to offshore wind turbine farm modelling. The CFD part is performed using a weakly-compressible solver (WCCH). The turbine is taken into account using FAST (from NREL) and its effects are imposed into the fluid domain through an actuator line model. The first part of this paper is dedicated to the presentation of the WCCH solver and its coupling with the aero-elastic modules from FAST. In a second part, for validation purposes, comparisons between FAST and the WCCH-FAST coupling are presented and discussed. Finally, a discussion on the performances, advantages and limitations of the formulation proposed is provided.

International audience

International audience

The main objective of this PhD is to create a dedicated tool to optimize tidal-turbine farms. This tool should eventually allow to determine the optimal arrangement of the machines on a given site to extract energy in an effective and rational manner. This manuscript describes the first stage of this work. The tool consists of a solver dedicated to solving the Navier-Stokes equations using a weakly compressible approach. These equations are solved explicitly within a finite volume formalism applied on a fully Cartesian grid. Tidal turbines are taken in account through models based on actuator methods that are coupled to the fluid solver in order to obtain a good compromise between CPU time and accuracy. First, the solver formulation and the development of a method to take in account viscosity are presented and validated. This formulation is then adapted to our problem by introducing a first LES turbulence model. Special inlet turbulent velocity conditions are also set up so as to take into account realistic flows. A special attention is paid to the minimization of numerical diffusion, ensuring a proper description of downstream wakes. Finally, two models (actuator-disc and actuator-line) are presented and validated through numerical and experimental cases.; L'objectif principal de ce doctorat constitue la première étape de création d'un outil dédié à l'optimisation de fermes d'hydroliennes. Un tel outil devrait permettre, à terme, de déterminer l'agencement optimal des machines sur un site donné, pour en extraire la ressource de manière efficace et rationnelle. Le travail présenté dans ce manuscrit décrit cette première étape. L'outil est composé d'un solveur dédié à la résolution des équations de Navier-Stokes avec une approche faiblement compressible. Elles sont résolues de manière explicite dans un formalisme volumes-finis et sur une grille pleinement cartésienne. Afin d’obtenir un bon compromis entre temps de calcul et précision, la prise en compte des hydroliennes est réalisée par l'intermédiaire de modèles basés sur les méthodes actuatrices qui sont couplés au solveur fluide. En premier lieu, la formulation du solveur et le développement d'une méthode de prise en compte de la viscosité sont présentés et validés. Cette formulation est ensuite adaptée à notre problématique en introduisant un premier modèle de turbulence en approche LES. Des conditions de vitesses d'entrée turbulentes sont mises en place de manière à pouvoir prendre en compte des écoulements réalistes. Une attention toute particulière est portée à la minimisation de la diffusion numérique, garantissant ainsi la bonne prise en compte des sillages en aval des hydroliennes. Enfin, deux modèles (actuator-disc et actuator-line) sont présentés et validés sur des cas numériques et expérimentaux d’écoulements autour d’hydroliennes.