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Listed below, are sorted by year, the publications appearing in the HAL open archive.

2021

  • Propagation for KPP bulk-surface systems in a general cylindrical domain
    • Bogosel Beniamin
    • Giletti Thomas
    • Tellini Andrea
    Nonlinear Analysis: Theory, Methods and Applications, Elsevier, 2021, 213, pp.42. In this paper, we investigate propagation phenomena for KPP bulk-surface systems in a cylindrical domain with general section and heterogeneous coefficients. As for the scalar KPP equation, we show that the asymptotic spreading speed of solutions can be computed in terms of the principal eigenvalues of a family of self-adjoint elliptic operators. Using this characterization, we analyze the dependence of the spreading speed on various parameters, including diffusion rates and the size and shape of the section of the domain. In particular, we provide new theoretical results on several asymptotic regimes like small and high diffusion rates and sections with small and large sizes. These results generalize earlier ones which were available in the radial homogeneous case. Finally, we numerically investigate the issue of shape optimization of the spreading speed. By computing its shape derivative, we observe, in the case of homogeneous coefficients, that a disk either maximizes or minimizes the speed, depending on the parameters of the problem, both with or without constraints. We also show the results of numerical shape optimization with non homogeneous coefficients, when the disk is no longer an optimizer. (10.1016/j.na.2021.112528)
    DOI : 10.1016/j.na.2021.112528
  • State-constrained control-affine parabolic problems II: second order sufficient optimality conditions
    • Aronna Maria Soledad
    • Frédéric Bonnans Joseph
    • Kröner Axel
    SIAM Journal on Control and Optimization, Society for Industrial and Applied Mathematics, 2021. In this paper we consider an optimal control problem governed by a semilinear heat equation with bilinear control-state terms and subject to control and state constraints. The state constraints are of integral type, the integral being with respect to the space variable. The control is multidimensional. The cost functional is of a tracking type and contains a linear term in the control variables. We derive second order sufficient conditions relying on the Goh transform. (10.1137/19M1286906)
    DOI : 10.1137/19M1286906
  • Dissipation-enhanced collapse singularity of a nonlocal fluid of light in a hot atomic vapor
    • Azam Pierre
    • Fusaro Adrien
    • Fontaine Quentin
    • Garnier Josselin
    • Bramati Alberto
    • Picozzi Antonio
    • Kaiser Robin
    • Glorieux Quentin
    • Bienaimé Tom
    Physical Review A, American Physical Society, 2021, 104 (1), pp.013515. We study the out-of-equilibrium dynamics of a two-dimensional paraxial fluid of light using a near-resonant laser propagating through a hot atomic vapor. We observe a double shock-collapse instability: a shock (gradient catastrophe) for the velocity, as well as an annular (ring-shaped) collapse singularity for the density. We find experimental evidence that this instability results from the combined effect of the nonlocal photon-photon interaction and the linear photon losses. The theoretical analysis based on the method of characteristics reveals the main result that dissipation (photon losses) is responsible for an unexpected enhancement of the collapse instability. Detailed analytical modeling makes it possible to evaluate the nonlocality range of the interaction. The nonlocality is controlled by adjusting the atomic vapor temperature and is seen to increase dramatically when the atomic density becomes much larger than one atom per cubic wavelength. Interestingly, such a large range of the nonlocal photon-photon interaction has not been observed in an atomic vapor so far and its microscopic origin is currently unknown. (10.1103/PhysRevA.104.013515)
    DOI : 10.1103/PhysRevA.104.013515
  • Stochastic Preconditioning of Domain Decomposition Methods for Elliptic Equations with Random Coefficients
    • Reis Joao Felício Dos
    • Le Maître Olivier P
    • Congedo Pietro M
    • Mycek Paul
    Computer Methods in Applied Mechanics and Engineering, Elsevier, 2021, 381, pp.113845. This paper aims at developing an efficient preconditioned iterative domain decomposition (DD) method for the sampling of linear stochastic elliptic equations. To this end, we consider a non-overlapping DD method resulting in a Symmetric Positive Definite (SPD) Schur system for almost every sampled problem. To accelerate the iterative solution of the Schur system, we propose a new stochastic preconditioning strategy that produces a preconditioner adapted to each sampled problem and converges toward the ideal preconditioner (i.e., the Schur operator itself) when the numerical parameters increase. The construction of the stochastic preconditioner is trivially parallel and takes place in an off-line stage, while the evaluation of the sample's preconditioner during the sampling stage has a low and fixed cost. One key feature of the proposed construction is a factorized form combined with Polynomial Chaos expansions of local operators. The factorized form guaranties the SPD character of the sampled preconditioners while the local character of the PC expansions ensures a low computational complexity. The stochastic preconditioner is tested on a model problem in 2 space dimensions. In these tests, the preconditioner is very robust and significantly more efficient than the deterministic median-based preconditioner, requiring, on average, up to 7 times fewer iterations to converge. Complexity analysis suggests the scalability of the preconditioner with the number of subdomains. (10.1016/j.cma.2021.113845)
    DOI : 10.1016/j.cma.2021.113845
  • Size matters for OTC market makers: General results and dimensionality reduction techniques
    • Bergault Philippe
    • Guéant Olivier
    Mathematical Finance, Wiley, 2021, 31 (1), pp.279-322. (10.1111/mafi.12286)
    DOI : 10.1111/mafi.12286
  • Duality and approximation of stochastic optimal control problems under expectation constraints
    • Pfeiffer Laurent
    • Tan Xiaolu
    • Zhou Yulong
    SIAM Journal on Control and Optimization, Society for Industrial and Applied Mathematics, 2021, 59 (5), pp.3231–3260. We consider a continuous time stochastic optimal control problem under both equality and inequality constraints on the expectation of some functionals of the controlled process. Under a qualification condition, we show that the problem is in duality with an optimization problem involving the Lagrange multiplier associated with the constraints. Then by convex analysis techniques, we provide a general existence result and some a priori estimation of the dual optimizers. We further provide a necessary and sufficient optimality condition for the initial constrained control problem. The same results are also obtained for a discrete time constrained control problem. Moreover, under additional regularity conditions, it is proved that the discrete time control problem converges to the continuous time problem, possibly with a convergence rate. This convergence result can be used to obtain numerical algorithms to approximate the continuous time control problem, which we illustrate by two simple numerical examples. (10.1137/20M1349886)
    DOI : 10.1137/20M1349886
  • Abnormal acoustic transmission in a waveguide with perforated screens
    • Chesnel Lucas
    • Nazarov Sergei
    Comptes Rendus. Mécanique, Académie des sciences (Paris), 2021. We consider the propagation of the piston mode in an acoustic waveguide obstructed by two screens with small holes. In general, due to the features of the geometry, almost no energy of the incident wave is transmitted through the structure. The goal of this article is to show that tuning carefully the distance between the two screens, which form a resonator, one can get almost complete transmission. We obtain an explicit criterion, not so obvious to intuit, for this phenomenon to happen. Numerical experiments illustrate the analysis. (10.5802/crmeca.70)
    DOI : 10.5802/crmeca.70
  • A semi-supervised method for the characterization of degradation of nuclear power plants steam generators
    • Pinciroli Luca
    • Baraldi Piero
    • Shokry Ahmed
    • Zio Enrico
    • Seraoui Redouane
    • Mai Carole
    Progress in Nuclear Energy, Elsevier, 2021, 131, pp.103580. (10.1016/j.pnucene.2020.103580)
    DOI : 10.1016/j.pnucene.2020.103580
  • Regenerative properties of the linear Hawkes process with unbounded memory
    • Graham Carl
    The Annals of Applied Probability, Institute of Mathematical Statistics (IMS), 2021, 31 (6), pp.2844-2863. We prove regenerative properties for the linear Hawkes process under minimal assumptions on the transfer function, which may have unbounded support. These results are applicable to sliding window statistical estimators. We exploit independence in the Poisson cluster point process decomposition, and the regeneration times are not stopping times for the Hawkes process. The regeneration time is interpreted as the renewal time at zero of a M/G/infinity queue, which yields a formula for its Laplace transform. When the transfer function admits some exponential moments, we stochastically dominate the cluster length by exponential random variables with parameters expressed in terms of these moments. This yields explicit bounds on the Laplace transform of the regeneration time in terms of simple integrals or special functions yielding an explicit negative upper-bound on its abscissa of convergence. These regenerative results allow, e.g., to systematically derive long-time asymptotic results in view of statistical applications. This is illustrated on a concentration inequality previously obtained with coauthors. (10.1214/21-AAP1664)
    DOI : 10.1214/21-AAP1664
  • Optimal control techniques based on infection age for the study of the COVID-19 epidemic
    • Bonnans Joseph Frédéric
    • Gianatti Justina
    Mathematical Modelling of Natural Phenomena, EDP Sciences, 2021. We propose a model for the COVID-19 epidemic where the population is partitioned into classes corresponding to ages (that remain constant during the epidemic). The main feature is to take into account the infection age of the infected population. This allows to better simulate the infection propagation that crucially depend on the infection age. We discuss how to compute the coefficients from data available in the future, and introduce a confinement variable as control. The cost function is a compromise between confinement cost, hospitalization peak and the death toll. Our numerical experiments allow to evaluate the interest of confinement varying with age classes. (10.1051/mmnp/2020035)
    DOI : 10.1051/mmnp/2020035
  • Numerical simulation of rigid particles in Stokes flow: lubrication correction for general shapes of particles
    • Lefebvre-Lepot Aline
    • Nabet Flore
    Mathematical Modelling of Natural Phenomena, EDP Sciences, 2021, 16, pp.45. We address the problem of numerical simulation of suspensions of rigid particles in a Stokes flow. We focus on the inclusion of the singular short range interaction effects (lubrication effects) in the simulations when the particles come close one to another. The problem is solved without introducing new hypothesis nor model. As in Lefebvre-Lepot et al. [J. Fluid Mech. 769 (2015) 369–386], the key idea is to decompose the velocity and pressure flows in a sum of a singular and a regular part. In this article, the singular part is computed using an explicit asymptotic expansion of the solution when the distance goes to zero. This expansion is similar to the asymptotic expansion proposed in Hillairet and Kelai [Asymptotic Anal. 95 (2015) 187–241] but is more appropriate for numerical simulations of suspensions. It can be computed for any locally convex (that is the particles have to be convex close to the contact point) and regular shape of particles. Using Hillairet and Kelai [Asymptotic Anal. 95 (2015) 187–241] as an intermediate result, we prove that the remaining part is regular in the sense that it is bounded independently of the distance. As a consequence, only a small number of degrees of freedom are necessary to obtain accurate results. The method is tested in dimension 2 for clusters of two or three aligned particles with general rigid velocities. We show that, as expected, the convergence is independent of the distance. (10.1051/mmnp/2021037)
    DOI : 10.1051/mmnp/2021037
  • EXISTENCE, UNIQUENESS AND REGULARITY FOR THE STOCHASTIC ERICKSEN-LESLIE EQUATION
    • de Bouard Anne
    • Hocquet Antoine
    • Prohl Andreas
    Nonlinearity, IOP Publishing, 2021. We investigate existence and uniqueness for the liquid crystal flow driven by colored noise on the two-dimensional torus. After giving a natural uniqueness criterion, we prove local solvability in L p-based spaces, for every p > 2. Thanks to a bootstrap principle together with a Gyöngy-Krylov-type compactness argument, this will ultimately lead us to prove the existence of a particular class of global solutions which are partially regular, strong in the probabilistic sense, and taking values in the "critical space" L 2 × H 1 . (10.1088/1361-6544/ac022e)
    DOI : 10.1088/1361-6544/ac022e
  • Some EM-type algorithms for incomplete data model building
    • Lavielle Marc
    , 2021. We propose an extension of the EM algorithm and its stochastic versions for the construction of incomplete data models when the selected model minimizes a penalized likelihood criterion. This optimization problem is particularly challenging in the context of incomplete data, even when the model is relatively simple. However, by completing the data, the E-step of the algorithm allows us to simplify this problem of complete model selection into a classical problem of complete model selection that does not pose any major difficulties. We then show that the criterion to be minimized decreases with each iteration of the algorithm. Examples of the use of these algorithms are presented for the identification of regression mixture models and the construction of nonlinear mixed-effects models.
  • Design of an acoustic energy distributor using thin resonant slits
    • Chesnel Lucas
    • Nazarov Sergei A
    Proceedings of the Royal Society of London. Series A, Mathematical and physical sciences, Royal Society, The, 2021. We consider the propagation of time harmonic acoustic waves in a device made of three unbounded channels connected by thin slits. The wave number is chosen such that only one mode can propagate. The main goal of this work is to present a device which can serve as an energy distributor. More precisely, the geometry is first designed so that for an incident wave coming from one channel, the energy is almost completely transmitted in the two other channels. Additionally, adjusting slightly two geometrical parameters, we can control the ratio of energy transmitted in the two channels. The approach is based on asymptotic analysis for thin slits around resonance lengths. We also provide numerical results to illustrate the theory. (10.1098/rspa.2020.0896)
    DOI : 10.1098/rspa.2020.0896
  • Practical computation of the diffusion MRI signal based on Laplace eigenfunctions: permeable interfaces
    • Agdestein Syver Døving
    • Tran Try Nguyen
    • Li Jing‐rebecca
    NMR in Biomedicine, Wiley, 2021. (10.1002/nbm.4646)
    DOI : 10.1002/nbm.4646
  • Analysis of the SORAS domain decomposition preconditioner for non-self-adjoint or indefinite problems
    • Bonazzoli Marcella
    • Claeys Xavier
    • Nataf Frédéric
    • Tournier Pierre-Henri
    Journal of Scientific Computing, Springer Verlag, 2021, 89. We analyze the convergence of the one-level overlapping domain decomposition preconditioner SORAS (Symmetrized Optimized Restricted Additive Schwarz) applied to a generic linear system whose matrix is not necessarily symmetric/self-adjoint nor positive definite. By generalizing the theory for the Helmholtz equation developed in [I.G. Graham, E.A. Spence, and J. Zou, SIAM J.Numer.Anal., 2020], we identify a list of assumptions and estimates that are sufficient to obtain an upper bound on the norm of the preconditioned matrix, and a lower bound on the distance of its field of values from the origin. We stress that our theory is general in the sense that it is not specific to one particular boundary value problem. Moreover, it does not rely on a coarse mesh whose elements are sufficiently small. As an illustration of this framework, we prove new estimates for overlapping domain decomposition methods with Robin-type transmission conditions for the heterogeneous reaction-convection-diffusion equation (to prove the stability assumption for this equation we consider the case of a coercive bilinear form, which is non-symmetric, though). (10.1007/s10915-021-01631-8)
    DOI : 10.1007/s10915-021-01631-8
  • A Non-Nested Infilling Strategy for Multi-Fidelity based Efficient Global Optimization
    • Sacher Matthieu
    • Le Maitre Olivier
    • Duvigneau Régis
    • Hauville Frédéric
    • Durand Mathieu
    • Lothode C.
    International Journal for Uncertainty Quantification, Begell House Publishers, 2021, 11 (1), pp.1-30. Efficient Global Optimization (EGO) has become a standard approach for the global optimization of complex systems with high computational costs. EGO uses a training set of objective function values computed at selected input points to construct a statistical surrogate model, with low evaluation cost, on which the optimization procedure is applied. The training set is sequentially enriched, selecting new points, according to a prescribed infilling strategy, in order to converge to the optimum of the original costly model. Multi-fidelity approaches combining evaluations of the quantity of interest at different fidelity levels have been recently introduced to reduce the computational cost of building a global surrogate model. However, the use of multi-fidelity approaches in the context of EGO is still a research topic. In this work, we propose a new effective infilling strategy for multi-fidelity EGO. Our infilling strategy has the particularity of relying on non-nested training sets, a characteristic that comes with several computational benefits. For the enrichment of the multi-fidelity training set, the strategy selects the next input point together with the fidelity level of the objective function evaluation. This characteristic is in contrast with previous nested approaches, which require estimation all lower fidelity levels and are more demanding to update the surrogate. The resulting EGO procedure achieves a significantly reduced computational cost, avoiding computations at useless fidelity levels whenever possible, but it is also more robust to low correlations between levels and noisy estimations. Analytical problems are used to test and illustrate the efficiency of the method. It is finally applied to the optimization of a fully nonlinear fluid-structure interaction system to demonstrate its feasibility on real large-scale problems, with fidelity levels mixing physical approximations in the constitutive models and discretization refinements. (10.1615/Int.J.UncertaintyQuantification.2020032982)
    DOI : 10.1615/Int.J.UncertaintyQuantification.2020032982
  • Outliers Detection in Networks with Missing Links
    • Gaucher Solenne
    • Klopp Olga
    • Robin Geneviève
    Computational Statistics and Data Analysis, Elsevier, 2021, 164, pp.107308. Outliers arise in networks due to different reasons such as fraudulent behavior of malicious users or default in measurement instruments and can significantly impair network analyses. In addition, real-life networks are likely to be incompletely observed, with missing links due to individual non-response or machine failures. Identifying outliers in the presence of missing links is therefore a crucial problem in network analysis. In this work, we introduce a new algorithm to detect outliers in a network that simultaneously predicts the missing links. The proposed method is statistically sound: we prove that, under fairly general assumptions, our algorithm exactly detects the outliers, and achieves the best known error for the prediction of missing links with polynomial computation cost. It is also computationally efficient: we prove sub-linear convergence of our algorithm. We provide a simulation study which demonstrates the good behavior of the algorithm in terms of outliers detection and prediction of the missing links. We also illustrate the method with an application in epidemiology, and with the analysis of a political Twitter network. The method is freely available as an R package on the Comprehensive R Archive Network. (10.1016/j.csda.2021.107308)
    DOI : 10.1016/j.csda.2021.107308
  • Qualitative indicator functions for imaging crack networks using acoustic waves
    • Audibert Lorenzo
    • Chesnel Lucas
    • Haddar Houssem
    • Napal Kevish
    SIAM Journal on Scientific Computing, Society for Industrial and Applied Mathematics, 2021. We consider the problem of imaging a crack network embedded in some homogeneous background from measured multi-static far field data generated by acoustic plane waves. We propose two novel approaches that can be seen as extensions of linear sampling-type methods and that provide indicator functions which are sensitive to local cracks densities. The first approach uses multiple frequencies data to compute spectral signatures associated with artificially embedded localized obstacles. The second approach also exploits the idea of incorporating an artificial background but uses data for a single frequency. The indicator function is built using a similar concept as for differential sampling methods: compare the solution of the interior transmission problem for healthy inclusion with the one with embedded cracks. The performance of the methods is tested and discussed on synthetic examples and the numerical results are compared with the ones obtained using the classical factorization method. (10.1137/20M134650X)
    DOI : 10.1137/20M134650X
  • Detecting seed bank influence on plant metapopulation dynamics
    • Louvet Apolline
    • Machon Nathalie
    • Mihoub Jean‐baptiste
    • Robert Alexandre
    Methods in Ecology and Evolution, 2021, 12 (4), pp.655-664. Seed banks are known to play a key role in plant metapopulations. However, detecting seed banks remains challenging and requires intense monitoring efforts. Assessing the genuine effect of seed banks on plant metapopulation dynamics (rather than their presence) may offer a much easier while still biologically relevant way to overcome this issue. In this study, we developed a new metric: the seed bank characteristic event (SBCE) probability. Instead of detecting seed bank directly, the SBCE probability measures seed bank contribution to the observed metapopulation dynamics. Exploring seed bank parameters (colonization, germination and seed bank death probabilities, initial proportion of patches containing a seed bank), a wide range of monitoring durations (from 3 to 10 years) and number of patches in the metapopulation (from 10 to 1,000 patches), we examined the conditions under which the SBCE probability is correctly estimated. To test the robustness of our approach, we further introduced false negatives, false positives or parameter heterogeneity between patches. Finally, we applied the SBCE probability method to the monitoring of tree bases plant species in Paris, France, to assess the applicability of the method to real‐world datasets and increase the understanding of plant metapopulation dynamics within an urban environment. Our results indicate that the SBCE probability is well‐estimated when enough monitoring years or number of patches are considered, and for probabilities of false negatives or false positives of up to 0.1. However, the SBCE probability estimation is not robust to colonization probability heterogeneity between patches. When we applied the SBCE probability method to the real monitoring dataset, we found a contrasted contribution of the seed bank to the observed metapopulation dynamics from one street and one species to another. The study suggests that the measurement of seed bank contribution is less data‐demanding than assessment of seed bank presence. Applying the estimation method to the monitoring of tree bases plant species highlights a significant contribution of the seed bank to plant metapopulation dynamics in an urban environment, and illustrates how the method can be applied on real‐world datasets. (10.1111/2041-210x.13547)
    DOI : 10.1111/2041-210x.13547
  • VARIATIONAL APPROXIMATION OF INTERFACE ENERGIES AND APPLICATIONS
    • Amstutz Samuel
    • Gourion Daniel
    • Zabiba Mohammed
    Interfaces and Free Boundaries : Mathematical Analysis, Computation and Applications, European Mathematical Society, 2021, 23 (23), pp.59-102. Minimal partition problems consist in finding a partition of a domain into a given number of components in order to minimize a geometric criterion. In applicative fields such as image processing or continuum mechanics, it is standard to incorporate in this objective an interface energy that accounts for the lengths of the interfaces between components. The present work is focused on the theoretical and numerical treatment of minimal partition problems with such interface energies. The considered approach is based on a Γ-convergence approximation combined with convex analysis techniques. (10.4171/IFB/450)
    DOI : 10.4171/IFB/450
  • Approximating the Total Variation with Finite Differences or Finite Elements
    • Chambolle Antonin
    • Pock Thomas
    , 2021, 22, pp.383--417. We present and compare various types of discretizations which have been proposed to approximate the total variation (mostly, of a grey-level image in two dimensions). We discuss the properties of finite differences and finite elements based approach and compare their merits, in particular in terms of error estimates and quality of the reconstruction. (10.1016/bs.hna.2020.10.005)
    DOI : 10.1016/bs.hna.2020.10.005
  • Fast Incremental Expectation Maximization for finite-sum optimization: nonasymptotic convergence
    • Fort Gersende
    • Gach Pierre
    • Moulines Eric
    Statistics and Computing, Springer Verlag (Germany), 2021, 31 (48). Fast Incremental Expectation Maximization (FIEM) is a version of the EM framework for large datasets. In this paper, we first recast FIEM and other incremental EM type algorithms in the {\em Stochastic Approximation within EM} framework. Then, we provide nonasymptotic bounds for the convergence in expectation as a function of the number of examples $n$ and of the maximal number of iterations $\kmax$. We propose two strategies for achieving an $\epsilon$-approximate stationary point, respectively with $\kmax = O(n^{2/3}/\epsilon)$ and $\kmax = O(\sqrt{n}/\epsilon^{3/2})$, both strategies relying on a random termination rule before $\kmax$ and on a constant step size in the Stochastic Approximation step. Our bounds provide some improvements on the literature. First, they allow $\kmax$ to scale as $\sqrt{n}$ which is better than $n^{2/3}$ which was the best rate obtained so far; it is at the cost of a larger dependence upon the tolerance $\epsilon$, thus making this control relevant for small to medium accuracy with respect to the number of examples $n$. Second, for the $n^{2/3}$-rate, the numerical illustrations show that thanks to an optimized choice of the step size and of the bounds in terms of quantities characterizing the optimization problem at hand, our results desig a less conservative choice of the step size and provide a better control of the convergence in expectation. (10.1007/s11222-021-10023-9)
    DOI : 10.1007/s11222-021-10023-9
  • Phase-field approximation for a class of cohesive fracture energies with an activation threshold
    • Chambolle Antonin
    • Crismale Vito
    Advances in Calculus of Variation, Walter de Gruyter GmbH, 2021, 14 (4), pp.475-497. We study the Γ-limit of Ambrosio-Tortorelli-type functionals Dε(u, v), whose dependence on the symmetrised gradient e(u) is different in Au and in e(u) − Au, for a C-elliptic symmetric operator A, in terms of the prefactor depending on the phase-field variable v. The limit energy depends both on the opening and on the surface of the crack, and is intermediate between the Griffith brittle fracture energy and the one considered by Focardi and Iurlano in [43]. In particular we prove that G(S)BD functions with bounded A-variation are (S)BD. (10.1515/acv-2019-0018)
    DOI : 10.1515/acv-2019-0018
  • Reciprocal association between participation to a national election and the epidemic spread of COVID-19 in France: nationwide observational and dynamic modeling study.
    • Zeitoun Jean-David
    • Faron Matthieu
    • Manternach Sylvain
    • Fourquet Jerome
    • Lavielle Marc
    • Lefevre Jeremie
    European Journal of Public Health, Oxford University Press (OUP): Policy B - Oxford Open Option D, 2021. Objective: To investigate possible reciprocal associations between the intensity of the COVID-19 epidemic in France and the level of participation at national elections. Design: Observational study and dynamic modelling using a sigmoidal mixed effects model. Setting: All hospitals where patients were admitted for COVID-19. Participants: All admitted patients from March 18, 2020 to April 17, 2020. Main outcome measures: Abstention and admission rate for COVID-19. Results: Mean abstention rate in 2020 among departments was 52.5%+/-6.4 and had increased by a mean of 18.8% as compared with the 2014 election. There was a high degree of similarity of abstention between the two elections among the departments (p<0.001). Among departments with a high outbreak intensity before the election, those with a higher participation were not affected by a significantly higher number of COVID-19 admissions after the elections. The sigmoidal model fitted the data from the different departments with a high degree of consistency. The covariate analysis showed that a significant association between participation and number of admitted patients was observed for both elections (2020: B=-5.36, p<1e-9 and 2014: B=-3.15, p<1e-6) contradicting a direct specific causation of the 2020 election. Participation was not associated with the position of the inflexion point suggesting no effect in the speed of spread. Conclusions: Our results suggest that the surrounding intensity of the COVID-19 epidemic in France did not have any local impact on citizens participation to a national election. The level of participation to the 2020 election had no impact on the spread of the pandemic. (10.1101/2020.05.14.20090100)
    DOI : 10.1101/2020.05.14.20090100