Twin digital short period seismic Array Experiment at Stromboli Volcano

Two small arrays composed by short period (1 Hz) digital seismic stations, with an aperture of approximately 400 meters, were set up at Stromboli volcano (one at semaforo Labronzo, the other at Ginostra- Timpone del Fuoco) with the purpose of the spatial location of the high frequency source of the explosion quakes. About 75 explosion-quakes were recorded at both arrays, and constitute the available data base. We have planned to apply the zero-lag cross-correlation technique to the whole data set in order to obtain back-azimuth and apparent slowness of the coherent seismic phases. A preliminary analysis for both arrays show that the predominant back-azimuth for the first phase is oriented in the direction of , but not strictly coincident to, the crater area. Moreover some back-scattered arrivals are quite evident in the seismogram.INGV - Osservatorio VesuvianoUnpublishedope

Twin digital short period seismic Array Experiment at Stromboli Volcano

Two small arrays composed by short period (1 Hz) digital seismic stations, with an aperture of approximately 400 meters, were set up at Stromboli volcano (one at semaforo Labronzo, the other at Ginostra- Timpone del Fuoco) with the purpose of the spatial location of the high frequency source of the explosion quakes. About 75 explosion-quakes were recorded at both arrays, and constitute the available data base. We have planned to apply the zero-lag cross-correlation technique to the whole data set in order to obtain back-azimuth and apparent slowness of the coherent seismic phases. A preliminary analysis for both arrays show that the predominant back-azimuth for the first phase is oriented in the direction of , but not strictly coincident to, the crater area. Moreover some back-scattered arrivals are quite evident in the seismogram

The spatial resolution of epidemic peaks

The emergence of novel respiratory pathogens can challenge the capacity of key health care resources, such as intensive care units, that are constrained to serve only specific geographical populations. An ability to predict the magnitude and timing of peak incidence at the scale of a single large population would help to accurately assess the value of interventions designed to reduce that peak. However, current disease-dynamic theory does not provide a clear understanding of the relationship between: epidemic trajectories at the scale of interest (e.g. city); population mobility; and higher resolution spatial effects (e.g. transmission within small neighbourhoods). Here, we used a spatially-explicit stochastic meta-population model of arbitrary spatial resolution to determine the effect of resolution on model-derived epidemic trajectories. We simulated an influenza-like pathogen spreading across theoretical and actual population densities and varied our assumptions about mobility using Latin-Hypercube sampling. Even though, by design, cumulative attack rates were the same for all resolutions and mobilities, peak incidences were different. Clear thresholds existed for all tested populations, such that models with resolutions lower than the threshold substantially overestimated population-wide peak incidence. The effect of resolution was most important in populations which were of lower density and lower mobility. With the expectation of accurate spatial incidence datasets in the near future, our objective was to provide a framework for how to use these data correctly in a spatial meta-population model. Our results suggest that there is a fundamental spatial resolution for any pathogen-population pair. If underlying interactions between pathogens and spatially heterogeneous populations are represented at this resolution or higher, accurate predictions of peak incidence for city-scale epidemics are feasible

An evidence-based recommendation on bed head elevation for mechanically ventilated patients

A semi-upright position in ventilated patients is recommended to prevent ventilator-associated pneumonia (VAP) and is one of the components in the Ventilator Bundle of the Institute for Health Care Improvement. This recommendation, however, is not an evidence-based one.status: publishe

A Theoretical Analysis of the Geography of Schistosomiasis in Burkina Faso Highlights the Roles of Human Mobility and Water Resources Development in Disease Transmission

We study the geography of schistosomiasis across Burkina Faso by means of a spatially explicit model of water-based disease dynamics. The model quantitatively addresses the geographic stratification of disease burden in a novel framework by explicitly accounting for drivers and controls of the disease, including spatial information on the distributions of population and infrastructure, jointly with a general description of human mobility and climatic/ecological drivers. Spatial patterns of disease are analysed by the extraction and the mapping of suitable eigenvectors of the Jacobian matrix subsuming the stability of the disease-free equilibrium. The relevance of the work lies in the novel mapping of disease burden, a byproduct of the parametrization induced by regional upscaling, by model-guided field validations and in the predictive scenarios allowed by exploiting the range of possible parameters and processes. Human mobility is found to be a primary control at regional scales both for pathogen invasion success and the overall distribution of disease burden. The effects of water resources development highlighted by systematic reviews are accounted for by the average distances of human settlements from water bodies that are habitats for the parasite's intermediate host. Our results confirm the empirical findings about the role of water resources development on disease spread into regions previously nearly disease-free also by inspection of empirical prevalence patterns. We conclude that while the model still needs refinements based on field and epidemiological evidence, the proposed framework provides a powerful tool for large-scale public health planning and schistosomiasis management

Human migration: the big data perspective

How can big data help to understand the migration phenomenon? In this paper, we try to answer this question through an analysis of various phases of migration, comparing traditional and novel data sources and models at each phase. We concentrate on three phases of migration, at each phase describing the state of the art and recent developments and ideas. The first phase includes the journey, and we study migration flows and stocks, providing examples where big data can have an impact. The second phase discusses the stay, i.e. migrant integration in the destination country. We explore various data sets and models that can be used to quantify and understand migrant integration, with the final aim of providing the basis for the construction of a novel multi-level integration index. The last phase is related to the effects of migration on the source countries and the return of migrants