Qualification sanitaire des troupeaux, représentations du risque selon les acteurs et les disciplines

La qualification sanitaire vise à établir de manière objective et fiable le statut sanitaire d'un animal ou d'un ensemble d'animaux au regard d'une maladie infectieuse. Concevoir une qualification sanitaire repose sur des connaissances biologiques concernant l'agent pathogène, ses voies de transmission et les moyens de détection de la maladie. Les modèles mathématiques et les outils statistiques et probabilistes permettent d'intégrer ces connaissances tout en prenant en compte l'incertitude et la variabilité des données biologiques. Les sciences humaines apportent un éclairage sur les enjeux, les perceptions et les logiques des individus et des collectifs, afin d'étudier la demande et l'acceptabilité de la qualification sanitaire. Chaque discipline apporte ainsi son point de vue sur la notion de risque sous-jacente à la démarche de qualification. Cette approche interdisciplinaire nécessite une coconstruction de la recherche, qui doit dépasser les différences culturelles et épistémologiques entre disciplines. Elle n'obéit pas à un seul type de rationalité, scientifique ou juridico-administrative ; elle mobilise nécessairement des connaissances savantes et des savoirs empiriques et dépend de nombreuses décisions pouvant engendrer convergences ou contradictions. (Résumé d'auteur

Vaccine breakthrough hypoxemic COVID-19 pneumonia in patients with auto-Abs neutralizing type I IFNs

Life-threatening `breakthrough' cases of critical COVID-19 are attributed to poor or waning antibody response to the SARS- CoV-2 vaccine in individuals already at risk. Pre-existing autoantibodies (auto-Abs) neutralizing type I IFNs underlie at least 15% of critical COVID-19 pneumonia cases in unvaccinated individuals; however, their contribution to hypoxemic breakthrough cases in vaccinated people remains unknown. Here, we studied a cohort of 48 individuals ( age 20-86 years) who received 2 doses of an mRNA vaccine and developed a breakthrough infection with hypoxemic COVID-19 pneumonia 2 weeks to 4 months later. Antibody levels to the vaccine, neutralization of the virus, and auto- Abs to type I IFNs were measured in the plasma. Forty-two individuals had no known deficiency of B cell immunity and a normal antibody response to the vaccine. Among them, ten (24%) had auto-Abs neutralizing type I IFNs (aged 43-86 years). Eight of these ten patients had auto-Abs neutralizing both IFN-a2 and IFN-., while two neutralized IFN-omega only. No patient neutralized IFN-ss. Seven neutralized 10 ng/mL of type I IFNs, and three 100 pg/mL only. Seven patients neutralized SARS-CoV-2 D614G and the Delta variant (B.1.617.2) efficiently, while one patient neutralized Delta slightly less efficiently. Two of the three patients neutralizing only 100 pg/mL of type I IFNs neutralized both D61G and Delta less efficiently. Despite two mRNA vaccine inoculations and the presence of circulating antibodies capable of neutralizing SARS-CoV-2, auto-Abs neutralizing type I IFNs may underlie a significant proportion of hypoxemic COVID-19 pneumonia cases, highlighting the importance of this particularly vulnerable population

Epidemiological modeling in a branching population. Particular case of a general SIS model with two age classes

International audienceThis paper covers the elaboration of a general class of multitype branching processes for modeling in a branching population, the evolution of a disease with horizontal and vertical transmissions. When the size of the population may tend to ∞, normalization must be carried out. As the initial size tends to infinity, the normalized model converges a.s. to a dynamical system the solution of which is the probability law of the state of health for an individual ancestors line. The focal point of this study concerns the transient and asymptotical behaviors of a SIS model with two age classes in a branching population. We will compare the asymptotical probability of extinction on the scale of a finite population and on the scale of an individual in an infinite population: when the rates of transmission are small compared to the rate of renewing the population of susceptibles, the two models lead to a.s. extinction, giving consistent results, which no longer applies to the opposite situation of important transmissions. In that case the size of the population plays a crucial role in the spreading of the disease

Contrôle d'épidémies dans des populations de branchement avec transmissions horizontales et verticales. Exemples des modèles SIS et SEIR. Application à l'ESB

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Illustration of some limits of the Markov assumption for transition between groups in models of spread of an infectious pathogen in a structured herd

International audienceIn epidemic models concerning a structured population, sojourn times in a group are usually described by an exponential distribution. For livestock populations, realistic distributions may be preferred for group changes (e.g. depending on sojourn time). We illustrated the effect on pathogen spread of the use of an exponential distribution, instead of the true distribution of the transition time, between groups for a population separated into two groups (youngstock, adults) when this true distribution is a triangular one. Concerning the epidemic process, two assumptions were defined: one type of excreting animal (SIR model), and two types of excreting animals (transiently or persistently infected animals). The study was conducted with two indirect-transmission levels between groups. Among the adults, the epidemic size and the last infection time were significantly different. For persistence, epidemic sizes (in the entire population and in youngstock) and first infection time, results varied according to models (excretion assumption, indirect-trans mission level)

A tractable Leader-Follower MDP model for animal disease management

International audienceSustainable animal disease management requires to design and implement control policies at the regional scale. However, for diseases which are not regulated, individual farmers are responsible for the adoption and successful application of control policies at the farm scale. Organizations (groups of farmers, health institutions...) may try to influence farmers' control actions through financial incentives, in order to ensure sustainable (from the health and economical point of views) disease management policies. Economics / Operations Research frameworks have been proposed for modeling the effect of incentives on agents. The Leader-Follower Markov Decision Processes framework is one such framework, that combines Markov Decision Processes (MDP) and stochastic games frameworks. However, since finding equilibrium policies in stochastic games is hard when the number of players is large, LF-MDP problems are intractable. Our contribution, in this article, is to propose a tractable model of the animal disease management problem. The tractable model is obtained through a few simple modeling approximations which are acceptable when the problem is viewed from the organization side. As a result, we design a polynomial-time algorithm for animal disease management, which we evaluate on a case study inspired from the problem of controlling the spread of the Porcine Reproductive and Respiratory Syndrome (PRRS)

A new class of stochastic processes for representing and generalizing individual-based semi-Markov models: the Semi-Semi-Markov Processes

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Stochastic dynamics of immunity in small populations: A general framework

International audienceAssessment of immunological status is a powerful tool in the surveillance and control of infectious pathogens in livestock and human populations. The distribution of immunity levels in the population provides information on time and age dependent transmission. A stochastic model is developed for a livestock population which relates the dynamics of the distribution of immunity levels at the population level to those of pathogen transmission. A general model with K immunity level categories is first proposed, taking into account the increase of the immunity level due to an infection or a re-exposure, the decrease of the immunity level with time since infection or exposure, and the effect of immunity level on the susceptibility and the infectivity of individuals. Numerical results are presented in the particular cases with K = 2 and K = 3 immunity level categories. We demonstrate that for a given distribution of the immunity levels at the population level, the model can be used to identify quantities such as most likely periods of time since introduction of infection. We discuss this approach in relation to analysis of serological data

Semi-semi-Markov processes : a new class of processes for formalizing and generalizing state-dependent individual-based models

National audienceIndividual-based models are a “bottom-up” approach for calculating empirical distributions at the level of the population from simulated individual trajecto- ries. We build a new class of stochastic processes for mathematically formalizing and generalizing these simulation models according to a “top-down” approach, when the individual state changes occur at countable random times. We allow individual population-dependent semi-Markovian transitions in a non closed population such as a branching population. These new processes are called Semi-Semi-Markov Processes (SSMP) and are generalizations of Semi-Markov processes. We calculate their kernel and their probability law, and we build a simulation algorithm from the kernel. The starting point of this work was the modelling of the propagation of a disease (stochastic process) in a branching population with interactions (nonbounded random graph)