Sentence examples for territorial cluster from inspiring English sources

Based on a large epidemiological surveillance system of incident malignant mesothelioma cases this study is the first to integrate a Bayesian territorial cluster analysis with standardized exposure data collection.

Geographically, the Palatinate was divided between two small territorial clusters: the Rhenish, or Lower, Palatinate and the Upper Palatinate.

This is due to the challenges of measurement and complexities that arise from the geographical spatiality of firms, industrial agglomeration and territorial clusters (Amin and Cohendet 2005).

Federal arrangements may not only protect existing clusters of individuals with shared values or preferences, but may also promote mobility and hence territorial clustering of individuals with similar preferences.

The geographical pattern found in the latent common component identifies territorial clusters with particularly high risk.

Several studies have shown the usefulness of identifying territorial clusters of MM for public health policies in Italy [ 7, 8] and elsewhere [ 9, 10].

Taken together our data support the existence of shared exposure patterns in territorial clusters of malignant mesothelioma due to single or multiple industrial sources.

This study aims to identify territorial clusters of malignant mesothelioma through a Bayesian spatial analysis and to characterize them by the integrated use of asbestos exposure information retrieved from the Italian national mesothelioma registry (ReNaM).

Our study demonstrates shared exposure patterns in territorial clusters of malignant mesothelioma due to single or multiple industrial sources, with major implications for public health policies, health surveillance, compensation procedures and site remediation programs.

This study aims to identify territorial clusters of MM cases in Italy through a Bayesian spatial analysis and to characterize them for exposure patterns by integrated use of individual asbestos exposure information retrieved from the Italian national mesothelioma registry (ReNaM).

After mapping the RR estimates, territorial MM clusters were defined based on the following criteria: a group of neighboring municipalities (a) all showing RR > 1 and (b) including one or more municipalities with a 90% credibility interval for RR entirely above 1.