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501 results on '"Alizon, Samuel"'

1. COVFlow: phylodynamics analyses of viruses from selected SARS-CoV-2 genome sequences

Author

Danesh, Gonché, Boennec, Corentin, Verdurme, Laura, Roussel, Mathilde, Trombert-Paolantoni, Sabine, Visseaux, Benoit, Haim-Boukobza, Stéphanie, and Alizon, Samuel

Subjects
COVID-19, molecular epidemiology, sequence database, phylogenetics, public health, Archaeology, CC1-960, Science
Abstract

Phylodynamic analyses can generate important and timely data to optimise public health response to SARS-CoV-2 outbreaks and epidemics. However, their implementation is hampered by the massive amount of sequence data and the difficulty to parameterise dedicated software packages. We introduce the COVFlow pipeline, accessible at https://gitlab.in2p3.fr/ete/CoV-flow, which allows a user to select sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID) database according to user-specified criteria, to perform basic phylogenetic analyses, and to produce an XML file to be run in the Beast2 software package. We illustrate the potential of this tool by studying two sets of sequences from the Delta variant in two French regions. This pipeline can facilitate the use of virus sequence data at the local level, for instance, to track the dynamics of a particular lineage or variant in a region of interest.

Published
2023
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2. Estimating dates of origin and end of COVID-19 epidemics

Author

Beneteau, Thomas, Elie, Baptiste, Sofonea, Mircea T., and Alizon, Samuel

Subjects
Archaeology, CC1-960, Science
Abstract

Estimating the date at which an epidemic started in a country and the date at which it can end depending on interventions intensity are important to guide public health responses. Both are potentially shaped by similar factors including stochasticity (due to small population sizes), superspreading events, and memory effects (the fact that the occurrence of some events, e.g. recovering from an infection, depend on the past, e.g. the number of days since the infection). Focusing on COVID-19 epidemics, we develop and analyse mathematical models to explore how these three factors may affect early and final epidemic dynamics. Regarding the date of origin, we find limited effects on the mean estimates, but strong effects on their variances. Regarding the date of extinction following lockdown onset, mean values decrease with stochasticity or with the presence of superspreading events. These results underline the importance of accounting for heterogeneity in infection history and transmission patterns to accurately capture early and late epidemic dynamics.

Published
2021
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3. Early phylodynamics analysis of the COVID-19 epidemic in France

Author

Danesh, Gonché, Elie, Baptiste, Michalakis, Yannis, Sofonea, Mircea T, Bal, Antonin, Behillil, Sylvie, Destras, Grégory, Boutolleau, David, Burrel, Sonia, Marcelin, Anne-Geneviève, Plantier, Jean-Christophe, Thibault, Vincent, Simon-Loriere, Etienne, van der Werf, Sylvie, Lina, Bruno, Josset, Laurence, Enouf, Vincent, and Alizon, Samuel

Subjects
Archaeology, CC1-960, Science
Abstract

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 and ℛt are 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.

Published
2021
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4. Treating symptomatic infections and the co-evolution of virulence and drug resistance

Author

Alizon, Samuel

Subjects
Archaeology, CC1-960, Science
Abstract

Antimicrobial therapeutic treatments are by definition applied after the onset of symptoms, which tend to correlate with infection severity. Using mathematical epidemiology models, I explore how this link affects the coevolutionary dynamics between the virulence of an infection, measured via host mortality rate, and its susceptibility to chemotherapy. I show that unless resistance pre-exists in the population, drug-resistant infections are initially more virulent than drug-sensitive ones. As the epidemic unfolds, virulence is more counter-selected in drug-sensitive than in drug-resistant infections. This difference decreases over time and, eventually, the exact shape of genetic trade-offs govern long-term evolutionary dynamics. Using adaptive dynamics, I show that two types of evolutionary stable strategies (ESS) may be reached in the context of this simple model and that, depending on the parameter values, an ESS may only be locally stable. In general, the more the treatment rate increases with virulence, the lower the ESS value. Overall, both on the short-term and long-term, having treatment rate depend on infection virulence tend to favour less virulent strains in drug-sensitive infections. These results highlight the importance of the feedbacks between epidemiology, public health policies and parasite evolution, and have implications for the monitoring of virulence evolution.

Published
2021
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5. Episome partitioning and symmetric cell divisions: quantifying the role of random events in the persistence of HPV infections

Author

Beneteau, Thomas, Selinger, Christian, Sofonea, Mircea T., and Alizon, Samuel

Subjects
Quantitative Biology - Populations and Evolution
Abstract

Human Papillomaviruses (HPV) are one of the most prevalent sexually transmitted infections (STI) and the most oncogenic viruses known to humans. The vast majority of HPV infections clear in less than 3 years, but the underlying mechanisms, especially the involvement of the immune response, are still poorly known. Building on earlier work stressing the potential importance of stochasticity in HPV infection clearance, we develop a stochastic mathematical model of HPV dynamics with an explicit description of the intracellular level. We show that the random partitioning of virus episomes upon stem cell division and the occurrence of symmetric divisions greatly affect viral persistence. These results call for more detailed within-host studies to better understand the relative importance of stochasticity and immunity in HPV infection clearance.

Published
2021
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6. Within-host bacterial growth dynamics with both mutation and horizontal gene transfer

Author

Djidjou-Demasse, Ramsès, Alizon, Samuel, and Sofonea, Mircea T.

Subjects
Quantitative Biology - Populations and Evolution, Mathematics - Dynamical Systems, Mathematics - Functional Analysis
Abstract

The evolution and emergence of antibiotic resistance is a major public health concern. The understanding of the within-host microbial dynamics combining mutational processes, horizontal gene transfer and resource consumption, is one of the keys to solve this problem. We analyze a generic model to rigorously describe interactions dynamics of four bacterial strains: one fully sensitive to the drug, one with mutational resistance only, one with plasmidic resistance only and one with both resistances. By dening thresholds numbers (i.e. each strain's eective reproduction and each strain's transition thresholds numbers), we rst express conditions for the existence of non trivial stationary states. We nd that these thresholds mainly depend on bacteria quantitative traits such as nutrient consumption ability, growth conversion factor, death rate, mutation (forward or reverse) and segregational loss of plasmid probabilities (for plasmid-bearing strains). Next, with respect to the order in the set of strain's eective reproduction thresholds numbers, we show that the qualitative dynamics of the model range from the extinction of all strains, coexistence of sensitive and mutational resistance strains to the coexistence of all strains at equilibrium. Finally, we go through some applications of our general analysis depending on whether bacteria strains interact without or with drug action (either cytostatic or cytotoxic).

Published
2020

8. Analyzing and Modeling the Spread of SARS-CoV-2 Omicron Lineages BA.1 and BA.2, France, September 2021--February 2022

Author

Sofonea, Mircea T., Roquebert, Benedicte, Foulongne, Vincent, Morquin, David, Verdurme, Laura, Trombert-Paolantoni, Sabine, Roussel, Mathilde, Bonetti, Jean-Christophe, Zerah, Judith, Haim-Boukobza, Stephanie, and Alizon, Samuel

Subjects
Epidemics -- Distribution -- Forecasts and trends -- France, Market trend/market analysis, Company distribution practices, Health
Abstract

The Omicron SARS-CoV-2 variant of concern (Pango lineage B.1.1.529, GISAID clade GR/484A) was detected in South Africa on November 26, 2021 (1). Rapid analyses demonstrated its increased transmissibility (C.A.B. Pearson [...]

Published
2022
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10. Factors shaping vaginal microbiota community long-term dynamics

Author

Kamiya, Tsukushi, primary, Tessandier, Nicolas, additional, Elie, Baptiste, additional, Bernat, Claire, additional, Boúe, Vanina, additional, Grasset, Sophie, additional, Groc, Soraya, additional, Rahmoun, Massilva, additional, Selinger, Christian, additional, Humphrys, Michael S., additional, Bonneau, Marine, additional, Graf, Christelle, additional, Foulongne, Vincent, additional, Reynes, Jacques, additional, Tribout, Vincent, additional, Segondy, Michel, additional, Boulle, Nathalie, additional, Ravel, Jacques, additional, Murall, Carmen Ĺıa, additional, and Alizon, Samuel, additional

Published
2024
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13. Factors associated with human papillomavirus (HPV) virus load variations in genital infections in young women

Author

Tessandier, Nicolas, primary, Boué, Vanina, additional, Kamyia, Tsukushi, additional, Supplisson, Olivier, additional, Murall, Carmen Lia, additional, Reyné, Bastien, additional, Selinger, Christian, additional, Bernat, Claire, additional, Grasset, Sophie, additional, Groc, Soraya, additional, Rahmoun, Massilva, additional, Bonneau, Marine, additional, Foulongne, Vincent, additional, Graf, Christelle, additional, Tribout, Vincent, additional, Prétet, Jean-Luc, additional, Reynes, Jacques, additional, Segondy, Michel, additional, Bravo, Ignacio G, additional, Boulle, Nathalie, additional, and Alizon, Samuel, additional

Published
2024
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17. Detecting Rapid Spread of SARS-CoV-2 Variants, France, January 26-February 16, 2021

Author

Haim-Boukobza, Stephanie, Roquebert, Benedicte, Trombert-Paolantoni, Sabine, Lecorche, Emmanuel, Verdurme, Laura, Foulongne, Vincent, Selinger, Christian, Michalakis, Yannis, Sofonea, Mircea T., and Alizon, Samuel

Subjects
Epidemics -- Statistics -- France, Disease transmission -- Statistics -- Risk factors, Company distribution practices, Health
Abstract

Since the end of 2020, at least 3 strains, or 'variants,' of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) bearing a high number of mutations have been associated with rapid [...]

Published
2021
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19. Real-time forecasting of COVID-19-related hospital strain in France using a non-Markovian mechanistic model.

Author

Massey, Alexander, Boennec, Corentin, Restrepo-Ortiz, Claudia Ximena, Blanchet, Christophe, Alizon, Samuel, and Sofonea, Mircea T.

Subjects
COVID-19 pandemic, INTENSIVE care units, STATISTICAL smoothing, MEDICAL personnel, FORECASTING, STATISTICAL models, HOSPITALS
Abstract

Projects such as the European Covid-19 Forecast Hub publish forecasts on the national level for new deaths, new cases, and hospital admissions, but not direct measurements of hospital strain like critical care bed occupancy at the sub-national level, which is of particular interest to health professionals for planning purposes. We present a sub-national French framework for forecasting hospital strain based on a non-Markovian compartmental model, its associated online visualisation tool and a retrospective evaluation of the real-time forecasts it provided from January to December 2021 by comparing to three baselines derived from standard statistical forecasting methods (a naive model, auto-regression, and an ensemble of exponential smoothing and ARIMA). In terms of median absolute error for forecasting critical care unit occupancy at the two-week horizon, our model only outperformed the naive baseline for 4 out of 14 geographical units and underperformed compared to the ensemble baseline for 5 of them at the 90% confidence level (n = 38). However, for the same level at the 4 week horizon, our model was never statistically outperformed for any unit despite outperforming the baselines 10 times spanning 7 out of 14 geographical units. This implies modest forecasting utility for longer horizons which may justify the application of non-Markovian compartmental models in the context of hospital-strain surveillance for future pandemics. Author summary: The US and European Covid-19 Forecast Hubs focus on metrics such as deaths, new cases, and hospital admissions, but do not offer measurements of hospital strain like critical care bed occupancy, which was essential for the provisioning of healthcare resources during the COVID-19 pandemic. Furthermore, forecasting support was only guaranteed on the national level leaving many countries to look elsewhere for valuable sub-national forecasts. In France statistical modelling approaches were proposed to anticipate hospital stain at the sub-national level but these were limited by a two-week forecast horizon. We present a sub-national French modelling framework and online application for anticipating hospital strain at the four-week horizon that can account for abrupt changes in key epidemiological parameters. It was the only publicly available real-time non-Markovian mechanistic model for the French epidemic when implemented in January 2021 and, to our knowledge, it still was at the time it stopped in early 2022. Further adaptations of this surveillance system can serve as an anticipation tool for hospital strain across sub-national localities to aid in the prevention of short-noticed ward closures and patient transfers. [ABSTRACT FROM AUTHOR]

Published
2024
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21. HPV detection patterns in young women from the PAPCLEAR longitudinal study: implications for HPV screening policies

Author

Bénéteau, Thomas, primary, Groc, Soraya, additional, Murall, Carmen Lia, additional, Boué, Vanina, additional, Élie, Baptiste, additional, Tessandier, Nicolas, additional, Bernat, Claire, additional, Bonneau, Marine, additional, Foulongne, Vincent, additional, Graf, Christelle, additional, Grasset, Sophie, additional, Rahmoun, Massilva, additional, Segondy, Michel, additional, Tribout, Vincent, additional, Reynes, Jacques, additional, Selinger, Christian, additional, Boulle, Nathalie, additional, Bravo, Ignacio G., additional, Sofonea, Mircea T., additional, and Alizon, Samuel, additional

Published
2023
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26. Predicting epidemics on weighted networks

Author

Kamp, Christel, Moslonka-Lefebvre, Mathieu, and Alizon, Samuel

Subjects
Quantitative Biology - Populations and Evolution
Abstract

The contact structure between hosts has a critical influence on disease spread. However, most networkbased models used in epidemiology tend to ignore heterogeneity in the weighting of contacts. This assumption is known to be at odds with the data for many contact networks (e.g. sexual contact networks) and to have a strong effect on the predictions of epidemiological models. One of the reasons why models usually ignore heterogeneity in transmission is that we currently lack tools to analyze weighted networks, such that most studies rely on numerical simulations. Here, we present a novel framework to estimate key epidemiological variables, such as the rate of early epidemic expansion and the basic reproductive ratio, from joint probability distributions of number of partners (contacts) and number of interaction events through which contacts are weighted. This framework also allows for a derivation of the full time course of epidemic prevalence and contact behaviour which is validated using numerical simulations. Our framework allows for the incorporation of more realistic contact networks into epidemiological models, thus improving predictions on the spread of emerging infectious diseases., Comment: 20 pages, 3 figures

Published
2012

28. Viral and immune dynamics of HPV genital infections in young women

Author

Tessandier, Nicolas, primary, Elie, Baptiste, additional, Boué, Vanina, additional, Selinger, Christian, additional, Rahmoun, Massilva, additional, Bernat, Claire, additional, Grasset, Sophie, additional, Groc, Soraya, additional, Bedin, Anne Sophie, additional, Bénéteau, Thomas, additional, Bonneau, Marine, additional, Graf, Christelle, additional, Jacobs, Nathalie, additional, Kamiya, Tsukushi, additional, Kerioui, Marion, additional, Lajoie, Julie, additional, Melki, Imène, additional, Prétet, Jean-Luc, additional, Reyné, Bastien, additional, Schlecht-Louf, Géraldine, additional, Sofonea, Mircea, additional, Supplisson, Olivier, additional, Foulongne, Vincent, additional, Guedj, Jérémie, additional, Hirtz, Christophe, additional, Picot, Marie-Christine, additional, Reynes, Jacques, additional, Tribout, Vincent, additional, Tuaillon, Édouard, additional, Waterboer, Tim, additional, Segondy, Michel, additional, Bravo, Ignacio G, additional, Boulle, Nathalie, additional, Murall, Carmen Lia, additional, and Alizon, Samuel, additional

Published
2023
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35. Does exposure to different menstrual products affect the vaginal environment?

Author

Tessandier, Nicolas, primary, Uysal, Ilkay Başak, additional, Elie, Baptiste, additional, Selinger, Christian, additional, Bernat, Claire, additional, Boué, Vanina, additional, Grasset, Sophie, additional, Groc, Soraya, additional, Rahmoun, Massilva, additional, Reyné, Bastien, additional, Bender, Noemi, additional, Bonneau, Marine, additional, Graf, Christelle, additional, Tribout, Vincent, additional, Foulongne, Vincent, additional, Ravel, Jacques, additional, Waterboer, Tim, additional, Hirtz, Christophe, additional, Bravo, Ignacio G., additional, Reynes, Jacques, additional, Segondy, Michel, additional, Murall, Carmen Lia, additional, Boulle, Nathalie, additional, Kamiya, Tsukushi, additional, and Alizon, Samuel, additional

Published
2022
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37. Les lois de la contagion. Fake news, virus, tendances…

Author

Alizon, Samuel, Alizon, Samuel, Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), and Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)

Subjects
[SDV.MP.VIR] Life Sciences [q-bio]/Microbiology and Parasitology/Virology, [SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], [SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], [SDV.EE.IEO] Life Sciences [q-bio]/Ecology, environment/Symbiosis, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.BID.SPT] Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, [SDV.GEN.GPO] Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], [SDV.EE.ECO] Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDV.BID.EVO] Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], [SDV.EE.SANT] Life Sciences [q-bio]/Ecology, environment/Health, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract

International audience; Commentaire du livre d'Adam Kucharski.

Published
2022

38. De Delta à Omicron, scénarios de tendances hospitalières pour l'hiver 2021-2022

Author

Alizon, Samuel, Sofonea, Mircea, Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), CNRS - Centre National de la Recherche Scientifique, IRD - Institut de recherche pour le developpement, Université de Montpellier, Travail du groupe de modélisation de l'équipe ETE, ANR-20-COVI-0098,PHYEPI,Intégration de données de séquences et d'incidence pour analyser et contrôler les épidémies virales(2020), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Alizon, Samuel, Intégration de données de séquences et d'incidence pour analyser et contrôler les épidémies virales - - PHYEPI2020 - ANR-20-COVI-0098 - COVID-19 - VALID, and Génétique et évolution des maladies infectieuses (GEMI)

Subjects
COVID19, virus, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDV.BID.SPT] Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, [SDV.BID.EVO] Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], [SDV.EE.ECO] Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDV.EE.SANT] Life Sciences [q-bio]/Ecology, environment/Health, évolution, modélisation, [SDV.MP.VIR] Life Sciences [q-bio]/Microbiology and Parasitology/Virology, [SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health, variants, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], [SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], [SDV.EE.IEO] Life Sciences [q-bio]/Ecology, environment/Symbiosis, scénarios, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], soins intensifs, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, [SDV.GEN.GPO] Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], épidémiologie, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract

Travail du groupe de modélisation de l'équipe ETE

Published
2021

39. Concomitant and productive genital infections by HSV-2 and HPV in two young women: a case report

Author

Uysal, Ilkay Basak, primary, Boue, Vanina, additional, Murall, Carmen Lia, additional, Graf, Christelle, additional, Selinger, Christian, additional, Hirtz, Christophe, additional, Bernat, Claire, additional, Ravel, Jacques, additional, Reynes, Jacques, additional, Bonneau, Marine, additional, Rahmoun, Massilva, additional, Segondy, Michel, additional, Boulle, Nathalie, additional, Grasset, Sophie, additional, Groc, Soraya, additional, Waterboer, Tim, additional, Tribout, Vincent, additional, Bravo, Ignacio G, additional, Burrel, Sonia, additional, Foulongne, Vincent, additional, Alizon, Samuel, additional, and Tessandier, Nicolas, additional

Published
2022
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45. Variant‐specific SARS‐CoV‐2 within‐host kinetics

Author

Elie, Baptiste, primary, Roquebert, Bénédicte, additional, Sofonea, Mircea T., additional, Trombert‐Paolantoni, Sabine, additional, Foulongne, Vincent, additional, Guedj, Jérémie, additional, Haim‐Boukobza, Stpéhanie, additional, and Alizon, Samuel, additional

Published
2022
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50. Cinétique intra-hôte des variants du SARS-CoV2

Author

Elie, Baptiste, Roquebert, Bénédicte, Sofonea, Mircea, Trombert-Paolantoni, Sabine, Foulongne, Vincent, Guedj, Jérémie, Haim-Boukobza, Stéphanie, Alizon, Samuel, Evolution Théorique et Expérimentale (MIVEGEC-ETE), Perturbations, Evolution, Virulence (PEV), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)-Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM), Cerballiance, Laboratoire de Virologie [CHRU Montpellier], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, SARS-Cov2, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, ddPCR, viral dynamics, variant of concern, within-host
Abstract

International audience; 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 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.; Depuis le début de l'année 2021, les variants préoccupants du SRAS-CoV-2 (VOC) provoquent des rebonds épidémiques dans de nombreux pays. Leurs propriétés sont bien caractérisées au niveau épidémiologique, mais les déterminants potentiels au niveau intra-hôte restent mal compris. Nous analysons une cohorte longitudinale de 6 944 individus avec 14 304 valeurs de cycle threshold (Ct) de tests de dépistage des COV par RT-qPCR réalisés dans la population générale et les hôpitaux en France entre le 6 février et le 21 août 2021. Pour convertir les valeurs Ct en nombre de copies virales, nous avons effectué une analyse supplémentaire en utilisant la PCR digitale. Nous constatons que le nombre de copies du génome viral atteint un pic plus élevé et présente un taux de décroissance plus lent dans les infections causées par le variant Alpha par rapport à celles causées par les lignées historiques. En se basant sur certaines observations montrant que le nombre copies virales dans les écouvillons des voies respiratoires supérieures sont informatives sur la contagiosité, nous montrons que la cinétique du variant Alpha se traduit par des potentiels de transmission significativement plus élevés, en particulier dans les populations plus âgées. Enfin, en comparant les infections causées par les variants Alpha et Delta, nous ne trouvons pas de différence significative dans le nombre maximal de copies virales. Ces résultats soulignent que certaines des différences entre les variants peuvent être détectées dans les variations de la charge virale.

Published
2022

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