Hospital-based Surveillance to Evaluate the Impact of Rotavirus Vaccination in Sao Paulo, Brazil

Background: Brazil implemented routine immunization with the human rotavirus vaccine, Rotarix, in 2006 and vaccination coverage reached 81% in 2008 in Sao Paulo. Our aim was to assess the impact of immunization on the incidence of severe rotavirus acute gastroenteritis (AGE). Methods: We performed a 5-year (2004-2008) prospective surveillance at a sentinel hospital in Sao Paulo, with routine testing for rotavirus in all children less than 5 years of age hospitalized with AGE. Genotypes of positive samples were determined by reverse transcription polymerase chain reaction. Results: During the study, 655 children hospitalized with AGE were enrolled; of whom 169 (25.8%) were positive for rotavirus. In the post-vaccine period, a 59% reduction in the number of hospitalizations of rotavirus AGE and a 42.2% (95% confidence interval [CI], 18.6%-59.0%; P = 0.001) reduction in the proportion of rotavirus-positive results among children younger than 5 years were observed, with the greatest decline among infants (69.2%; 95% CI, 24.7%-87.4%; P = 0.004). Furthermore, the number of all-cause hospitalizations for AGE was reduced by 29% among children aged <5 years. The onset and peak incidences of rotavirus AGE occurred 3 months later in the 2007 and 2008 seasons compared with previous years. Genotype G2 accounted for 15%, 70%, and 100% of all cases identified, respectively, in 2006, 2007, and 2008. Conclusions: After vaccine implementation, a marked decline in rotavirus AGE hospitalizations was demonstrated among children younger than 5 years of age, with the greatest reduction in the age groups targeted for vaccination. The predominance of genotype G2P[4] highlights the need of continued postlicensure surveillance studies.

Using non-homogeneous Poisson models with multiple change-points to estimate the number of ozone exceedances in Mexico City

In this paper, we consider some non-homogeneous Poisson models to estimate the probability that an air quality standard is exceeded a given number of times in a time interval of interest. We assume that the number of exceedances occurs according to a non-homogeneous Poisson process (NHPP). This Poisson process has rate function lambda(t), t >= 0, which depends on some parameters that must be estimated. We take into account two cases of rate functions: the Weibull and the Goel-Okumoto. We consider models with and without change-points. When the presence of change-points is assumed, we may have the presence of either one, two or three change-points, depending of the data set. The parameters of the rate functions are estimated using a Gibbs sampling algorithm. Results are applied to ozone data provided by the Mexico City monitoring network. In a first instance, we assume that there are no change-points present. Depending on the adjustment of the model, we assume the presence of either one, two or three change-points. Copyright (C) 2009 John Wiley & Sons, Ltd.

An entropy-based approach to automatic image segmentation of satellite images

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.