University of Extremadura

About: University of Extremadura is a education organization based out in Badajoz, Spain. It is known for research contribution in the topics: Population & Hyperspectral imaging. The organization has 7856 authors who have published 18299 publications receiving 396126 citations. The organization is also known as: Universidad de Extremadura.

Increased detrimental effects of ectoparasites on their bird hosts during adverse environmental conditions

Abstract: Parasites are usually assumed to negatively affect fitness components of their hosts, particularly during adverse environmental conditions. We experimentally tested whether the ectoparasitic house martin bug (Oeciacus hirundinis) had larger negative effects on its house martin (Delichon urbica) host during second clutches. Conditions for reproduction decreased during the season, being less favourable for the second clutch than the first clutch. This was demonstrated by smaller clutch sizes, lower breeding success and smaller and lighter nestlings during the second clutch, as compared to the first, in the absence of parasites. Experimental manipulation of the intensity of parasitism resulted in the reproductive success of the host being reduced with increasing numbers of house martin bugs. This effect was much stronger during the second, as compared to the first, clutch. The house martin bug therefore had a greater detrimental effect on the reproduction of its host when conditions for reproduction were poor.

Data envelopment analysis applied to quality in primary health care

Abstract: The performance of primary care should ultimately be judged on its effect on the health outcome of individual patients. However, for the foreseeable future, it is inconceivable that the outcome data necessary to come to a judgement on performance will be available. And in any case, specification of the statistical model necessary to analyze outcome is fraught with difficulty. This paper therefore sets out a model of primary care performance which is based on the premise that certain measurable quality indicators can act as proxies for outcome. This being the case, a model of performance can be deduced which takes into account the effect of resources and patient characteristics on outcome. The most appropriate analytic technique to make this model operational is data envelopment analysis (DEA). It is argued that DEA can handle multiple dimensions of performance more comfortably, and is less vulnerable to the misspecification bias that afflicts statistically based models. The issues are illustrated with an example from English Family Health Service Authorities.