In the São Paulo State, Brazil, where the Biomphalaria tenagophila is the intermediate host, the Ribeira Valley is an important endemic schistosomiasis mansoni area. During last eleven years there has been intense control measures focusing on schistosomiasis. The efforts have been concentrated in the municipalities of Pedro de Toledo and Itariri. We determined the susceptibility of B. tenagophila to sympatric strain of S. mansoni, both recently isolated from Itariri field. In 1988, this strain was isolated and maintained in the experimental model: Swiss mice - sympatric B. tenagophila. The second generation of the worm was evaluated. The snail were divided in the three groups of 60 snails each. One group was exposed to 1 miracidium and other to 10. The third group was the control. The mortality and the shedding of cercariae were checked during 78 days. After that, the positive snails were observed until they ceased to shed cercariae. The exposed molluscs showed mortality rates of 23% and 31% and infection indexes were of 8% and 60% to 1 and 10 miracidia respectively. The mortality was of 22% in the control group. The periods of shedding cercariae in the two groups were 82 and 104 days. We can conclude that B. tenagophila is an effective intermediate host to the sympatric strain of S. mansoni sympatric strain
In the health and social sciences, researchers often encounter categorical data for which complexities come from a nested hierarchy and/or crossclassification for the sampling structure. A common feature of these studies is a non-standard data structure with repeated measurements which may have some degree of clustering. In this paper, methodology is presented for the joint estimation of quantities of interest in the context of a stratified two-stage sample with bivariate dichotomous data. These quantities are the mean value n of an observed dichotomous response for a certain condition or time-point and a set of correlation coefficients for intra-cluster association for each condition or time period and for inter-condition correlation within and among clusters. The methodology uses the cluster means and pairwise joint probability parameters from each cluster. They together provide appropriate information across clusters for the estimation of the correlation coefficients.
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