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The diagnosis of rubella is mainly made in pregnant women and the newborn by specific IgG and/or IgM detection. In addition to HAI and ELISA techniques, new immunoanalytical methods have been developed. This study aimed to evaluate two chemiluminescence platforms, Architect i2000SR and Maglumi 800 for rubella biological diagnosis in Cote d'Ivoire. Blood samples were taken from 113 pregnant women aged 15 to 30 in prenatal care. Samples were analyzed for Rubella IgG detection at the NBTS laboratory on the evaluated platforms and the Cobas e601 used as a reference. The majority of women were in their second trimester of pregnancy. Among them, only 13.3% were vaccinated against rubella. The evaluated platforms showed good precision with coefficients of variation >10%. Regarding analytical performances, sensitivities were 97.53% and 96.29% whereas specificities were 100% and 96.88% for Architect I2000SR and Maglumi800, respectively. Both platforms showed good agreement with cobas e601 for antibody levels

International audience; This paper describes a new computational method for recursive least squares (RLS) algorithm. It is well known that the initial values for computing RLS estimates should be chosen to guarantee the existence of the estimates at each step, that the initial covariance matrix may affect the convergence rate, and that a blow-up phenomenon (infinite increase of the covariance matrix) can appear. Much research has focused on each of these problems, but heavy computations and different specific design parameters result from the most common solutions. We propose an alternative simple algorithm that reaches a trade-off between the advantages of the well-known RLS algorithms and of the more complex computations. The proposed algorithm modifies the prior additional term used in the cost function. This modified term is updated during the recursion, in the context of a differential formalism. The aim of this formalism is, first, to provide valid computations and properties in both discrete and continuous time domains, and to yield the variations of the parameters at each step. Second, in the particular case of discrete time this formalism provides very good numerical properties. The methodology in developing this approach is quite different from the previous work on RLS estimation. We demonstrate that our algorithm, compared with RLS algorithm, leads to a higher convergence rate. It also offers a closer tracking of parameters in nonstationary case and satisfactory results in the presence of blow-up situations. This goal is achieved without significant additional computations, and the behaviour of the approach is illustrated through simulations.