Strategic Project - UI 6 - 2011-2012

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Publications

The impact of winter cold weather on acute myocardial infarctions in Portugal

Publication . Vasconcelos, João; Freire, Elisabete; Almendra, Ricardo; Silva, Giovani L.; Santana, Paula

Mortality due to cardiovascular diseases shows a seasonal trend that can be associated with cold weather. Portugal is the European country with the highest excess winter mortality, but nevertheless, the relationship between cold weather and health is yet to be assessed. The main aim of this study is to identify the contribution of cold weather to cardiovascular diseases within Portugal. Poisson regression analysis based on generalized additive models was applied to estimate the influence of a human-biometeorological index (PET) on daily hospitalizations for myocardial infarction. The main results revealed a negative effect of cold weather on acute myocardial infarctions in Portugal. For every degree fall in PET during winter, there was an increase of up to 2.2% (95% CI ¼ 0.9%; 3.3%) in daily hospital admissions. This paper shows the need for public policies that will help minimize or, indeed, prevent exposure to cold.

2013Journal article

Restricted access

Known Mean, Unknown Maxima? Testing the Maximum Knowing Only the Mean

Publication . Santos, Rui; Oliveira Martins, João Paulo; Felgueiras, Miguel

In the quantitative group testing problem, the use of the group mean to identify if the group maximum is greater than a prefixed threshold (infected group) is analyzed, using n independent and identically distributed individuals. Under these conditions, it is shown that the information of the mean is sufficient to classify each group as infected or healthy with low probability of misclassification when the underline distribution is a unilateral heavy-tailed distribution.

2015-07Journal article

Restricted access

Testing the Maximum by the Mean in Quantitative Group Tests

Publication . Martins, João Paulo; Santos, Rui; Sousa, Ricardo

Group testing, introduced by Dorfman in 1943, increases the efficiency of screening individuals for low prevalence diseases. A wider use of this kind of methodology is restricted by the loss of sensitivity inherent to the mixture of samples. Moreover, as this methodology attains greater cost reduction in the cases of lower prevalence (and, consequently, a higher optimal batch size), the phenomenon of rarefaction is crucial to understand that sensitivity reduction. Suppose, with no loss of generality, that an experimental individual test consists in determining if the amount of substance overpasses some prefixed threshold l. For a pooled sample of size n, the amount of substance of interest is represented by (Y1, … , Yn), with mean (Formula Presented) and maximum Mn. The goal is to know if any of the individual samples exceeds the threshold l, that is, Mn > l. It is shown that the dependence between (Formula Presented) and Mn has a crucial role in deciding the use of group testing since a higher dependence corresponds to more information about Mn given by the observed value of (Formula Presented).

2014Book part

Open access