Article

Effect of influenza vaccine status on winter mortality in Spanish community-dwelling elderly people during 2002-2005 influenza periods.

Primary Care Service of Tarragona-Valls, Institut Català de la Salut, Tarragona, Spain.
Vaccine (Impact Factor: 3.49). 10/2007; 25(37-38):6699-707. DOI: 10.1016/j.vaccine.2007.07.015
Source: PubMed

ABSTRACT This study assessed the relationship between the reception of conventional inactivated influenza vaccine and winter mortality in a prospective cohort that included 11,240 Spanish community-dwelling elderly individuals followed from January 2002 to April 2005. Annual influenza vaccine status was a time-varying condition and primary outcome was all-cause death during study period. Multivariable Cox proportional-hazard models adjusted by age, sex and co-morbidity were used to evaluate vaccine effectiveness. Influenza vaccination was associated with a significant reduction of 23% in winter mortality risk during overall influenza periods. The attributable mortality risk in non-vaccinated people was 24 deaths per 100,000 persons-week within influenza periods, the prevented fraction for the population was 14%, and one death was prevented for every 239 annual vaccinations (ranging from 144 in Winter 2005 to 1748 in Winter 2002).

0 Followers
 · 
66 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Poisson and ARIMA models estimate higher influenza morbidity and mortality than Serfling models.•Statistical model databases must control confounders to accurately assess vaccine effectiveness.•Influenza-like illness doesn’t measure influenza prevalence; sentinel networks test some cases.
    Vaccine 10/2014; 32(51). DOI:10.1016/j.vaccine.2014.08.090 · 3.49 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The paper presents a method for determination of the maximum throw of flyrock fragments and the estimation of safe distances. The method is based upon formulation and solution of differential equations of ballistic flight of the flyrock fragments. The equations are formulated according to Newton's law of motion. Two possible solutions are presented, an approximate numerical solution and the application of the Runge–Kutta algorithm of the fourth order. As an illustration of the presented method a post-accidental forensic analysis case study is given describing the procedure for determination of the input parameters (especially the launch velocity).
    International Journal of Rock Mechanics and Mining Sciences 10/2011; 48(7):1086-1094. DOI:10.1016/j.ijrmms.2011.07.004 · 1.42 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Soil–rock mixtures (S–RM) which formed in the quaternary period are a type of extremely inhomogeneous and loose geomaterial with a certain percentage of rock blocks. They are composed of rock blocks with various sizes and high strength, fine grained soil and pores. The meso-failure mechanism and macro-physical and mechanical characteristics of S–RM are largely controlled by its rock block proportion and the granular distribution. As we know, when the rock blocks in the S–RM are larger, it is difficult to take an in-situ sample for an on-site test. In addition, it is difficult to obtain the granular distribution of rock blocks in S–RM by traditional sieving tests. This paper uses a new method called digital image processing (DIP) in which the rock blocks in S–RM samples are separated from the soil matrix, and the proportion and distribution of the rock blocks is obtained quantitatively. The results are used for the sample preparation of the large scale direct shear tests which provide a new method for the test study of S–RM. According to the results of large scale direct shear tests the rock block size proportion controls the deformation and fracture mechanism of the S–RM. The shape of the shear stress vs horizontal displacement curve and the vertical displacement vs horizontal displacement curve of the S–RM samples are different from that of general “soil” and “rock”. With the increment of the rock block proportion the shear band of the S–RM increases. When the rock block proportion lies in the range of 25–70%, the increment of the internal friction angle linearly increases with the increment of the rock block proportion. The cohesion of the S–RM decreases compared with that of the soil. When the rock block proportion is larger than 30%, however, there is only a little decrease in the cohesion with the increment of the rock block proportion.
    International Journal of Rock Mechanics and Mining Sciences 12/2011; 48(8). DOI:10.1016/j.ijrmms.2011.09.018 · 1.42 Impact Factor