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### Détail de l'auteur

### Auteur Denis JB

### Documents disponibles écrits par cet auteur

Ajouter le résultat dans votre panier Affiner la rechercheA bayesian evidence synthesis for estimating campylobacteriosis prevalence. / Albert Iin Risk analysis [Risk Anal], Vol.31, N° 7 (Juillet 2011)

[article]inRisk analysis [Risk Anal] > Vol.31, N° 7 (Juillet 2011) . - 1141-55

Titre : A bayesian evidence synthesis for estimating campylobacteriosis prevalence. Type de document : Article scientifique Auteur(s) : Albert I ; Espie E ; de Valk H ; Denis JB Appartenance auteur(s) InVS DMI Année de publication : 2011 Article en page(s) : 1141-55 Langues : Anglais ( eng)Mots-clés : Campylobactériose ; Prévalence ; Estimation ; Statistique ; Méthode Résumé : Stakeholders making decisions in public health and world trade need improved estimations of the burden-of-illness of foodborne infectious diseases. In this article, we propose a Bayesian meta-analysis or more precisely a Bayesian evidence synthesis to assess the burden-of-illness of campylobacteriosis in France. Using this case study, we investigate campylobacteriosis prevalence, as well as the probabilities of different events that guide the disease pathway, by (i) employing a Bayesian approach on French and foreign human studies (from active surveillance systems, laboratory surveys, physician surveys, epidemiological surveys, and so on) through the chain of events that occur during an episode of illness and (ii) including expert knowledge about this chain of events. We split the target population using an exhaustive and exclusive partition based on health status and the level of disease investigation. We assume an approximate multinomial model over this population partition. Thereby, each observed data set related to the partition brings information on the parameters of the multinomial model, improving burden-of-illness parameter estimates that can be deduced from the parameters of the basic multinomial model. This multinomial model serves as a core model to perform a Bayesian evidence synthesis. Expert knowledge is introduced by way of pseudo-data. The result is a global estimation of the burden-of-illness parameters with their accompanying uncertainty. (R.A) PMID Pubmed : Pubmed : 21231950 Lien externe DOI : DOI : 10.1111/j.1539-6924.2010.01572.x Corpus : Production scientifique InVS Permalink : http://opac.invs.sante.fr/index.php?lvl=notice_display&id=379 [article]A quantitative risk assessment of waterborne cryptosporidiosis in France using second-order Monte Carlo simulation / Pouillot Rin Risk analysis [Risk Anal], Vol. 24, N° 1 (02/2004)

[article]inRisk analysis [Risk Anal] > Vol. 24, N° 1 (02/2004) . - 1-18

Titre : A quantitative risk assessment of waterborne cryptosporidiosis in France using second-order Monte Carlo simulation Type de document : Article scientifique Auteur(s) : Pouillot R ; Beaudeau P ; Denis JB ; Derouin F Appartenance auteur(s) InVS DSE Année de publication : 2004 Article en page(s) : 1-18 Langues : Anglais ( eng)Mots-clés : France ; Pollution hydrique ; Parasitose ; Protozoaire ; Distribution eau ; Eau consommation humaine ; Qualité eau Mots-clés : CRYPTOSPORIDIOSE Résumé : A pragmatic quantitative risk assessment (QRA) of the risks of waterborne Cryptosporidium parvum infection and cryptosporidiosis inimmunocompetent and immunodeficient French populations is proposed. The model takes into account French specificities such as the French technique for oocyst enumeration performance and tap water consumption. The proportion of infective oocysts is based on literature review and expert knowledge. The probability of infection for a given number of ingested viable oocysts is modeled using the exponential dose-response model applied on published data from experimental infections in immunocompetent human volunteers challenged with the IOWA strain. Second-order Monte Carlo simulations are used to characterize the uncertainty and variability of the risk estimates. Daily risk of infection and illness for the immunocompetent and the immunodeficient populations are estimated according to the number of oocysts observed in a single storage reservoir water sample. As an example, the mean daily risk of infection in the immunocompetent population is estimated to be 1.08 x 10(-4) (95% confidence interval: [0.20 x 10(-4); 6.83 x 10(-4)]) when five oocysts are observed in a 100 L storage reservoir water sample. Annual risks of infection and disease are estimated from a set of oocyst enumeration results from distributed water samples, assuming a negative binomial distribution of day-to-day contamination variation. The model and various assumptions used in the model are fully explained and discussed. While caveats of this model are well recognized, this pragmatic QRA could represent a useful tool for the French Food Safety Agency (AFSSA) to define recommendations in case of water resource contamination by C. parvum whose infectivity is comparable to the IOWA strain. PMID Pubmed : Pubmed : 15027996 Corpus : Production scientifique InVS Permalink : http://opac.invs.sante.fr/index.php?lvl=notice_display&id=5666 [article]