outcomes, population health. The term PRIMARY CARE is thought to date back to about1920, when the Dawson Report was released in the UnitedKingdom. That report, an official “white paper, ” mentioned “primary health care centres, ” intended to become the hub of region-alized services in that country

-low the users on the net to access territorial data. In accordance to this aim it has been planned and re-alized a digital archive and the aerial photos of the Veneto region have been published on the WebGIS; so a more qualified service is now offered to a more demanding and various public com-posed of public

. This sense of margin-alization leads to a number of questions which are important for social workers practising in northern, hinterland regions. What does the concept of ‘north ’ mean today? Does the northern envi-ronment create special considerations for the delivery of human services and social work

tackle the problem of person-alized expert recommendation, to identify experts who have spe-cial personal appeal and importance to users. One of the key in-sights motivating our approach is to leverage the geo-spatial pref-erences of users and the variation of these preferences across differ-ent regions

, and there was optimism that elimination of indigenous respiratory diphtheria could be achieved in the European Region by 1990 by main-taining and strengthening immunization services [1]. However, a striking resurgence of epidemic diphtheria in the Newly Independent States (NIS) of the former Soviet Union has drawn

Abstract not found

Abstract | This review provides an introduction to Sup-

Abstract. The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood protection. This ar-ticle reviews recent progress in the statistical modeling of spatial extremes, starting with sketches of the necessary elements of extreme value statistics and geostatistics. The main types of statistical models thus far proposed, based on latent variables, on copulas and on spatial max-stable processes, are described and then are compared by application to a data set on rain-fall in Switzerland. Whereas latent variable modeling allows a better fit to marginal distributions, it fits the joint distributions of extremes poorly, so appropriately-chosen copula or max-stable models seem essential for suc-cessful spatial modeling of extremes.

de nationalité suisse et originaire de Zurich (ZH) et Lucerne (LU) acceptée sur proposition du jury: