After the cases of COVID-19 skyrocketed, showing that it was no longer possible to contain the spread of the disease, the governments of many countries launched mitigation strategies, trying to slow the spread of the epidemic and flatten its curve. The Spanish Government adopted physical distancing measures on March 14; 13 days after the epidemic outbreak started its exponential growth. Our objective in this paper was to evaluate ex-ante (before the flattening of the curve) the effectiveness of the measures adopted by the Spanish Government to mitigate the COVID-19 epidemic. Our hypothesis was that the behavior of the epidemic curve is very similar in all countries. We employed a time series design, using information from January 17 to April 5, 2020 on the new daily COVID-19 cases from Spain, China and Italy. We specified two generalized linear mixed models (GLMM) with variable response from the Gaussian family (i.e. linear mixed models): one to explain the shape of the epidemic curve of accumulated cases and the other to estimate the effect of the intervention. Just one day after implementing the measures, the variation rate of accumulated cases decreased daily, on average, by 3.059 percentage points, (95% credibility interval: −5.371, −0.879). This reduction will be greater as time passes. The reduction in the variation rate of the accumulated cases, on the last day for which we have data, has reached 5.11 percentage points. The measures taken by the Spanish Government on March 14, 2020 to mitigate the epidemic curve of COVID-19 managed to flatten the curve and although they have not (yet) managed to enter the decrease phase, they are on the way to do so.
Abstract.Wildfires have been studied in many ways, for instance as a spatial point pattern or through modelling the size of fires or the relative risk of big fires. Lately a large variety of complex statistical models can be fitted routinely to complex data sets, in particular wildfires, as a result of widely accessible high-level statistical software, such as R. The objective in this paper is to model the occurrence of big wildfires (greater than a given extension of hectares) using an adapted two-part econometric model, specifically a hurdle model. The methodology used in this paper is useful to determine those factors that help any fire to become a big wildfire.Our proposal and methodology can be routinely used to contribute to the management of big wildfires.
(un facteur d'impact)ACLInternational audienceA multi-scale and multi-disciplinary method was tested in the Catalan pre-Pyrenees in order to understand the relationship between landscape change, landscape processes, and ecological and social characteristics of landscapes. The three scales, and their corresponding methods, help us understand the processes of landscape change: on a general scale, a standardisation due to forest spread; on a detailed scale, a fragmentation of non-forest habitats; and on a local scale, the regeneration and scattering of woody species. Major landscape alterations have been observed through remotely sensed data. Closed forest area grew 140% at the expense of non-forest habitats such as pastures (-75%) and cultivated lands (-95%) during the past 50 years. Ecological metrics show a landscape standardisation (SHDI divided by 3) and a fragmentation of farmed landscapes. These changes, following a spatial pattern based on topography, explain the dynamic of the woody species in residual pastures, despite the persistence of cattle grazing as observed during field surveys. Yet, the forest, which constitutes the matrix of landscape, is not stable because of competition between species. The landscape change is related to the decline of the population (divided by 4.5 during the past 50 years) and the agricultural activities (number of farms divided by 2 or 3 during the past 20 years), and the favourable mild climate. The sustainable development of this territory should make the objectives of conservation, biodiversity and landscape protection and the preservation of their Mediterranean features compatible, and support agricultural activities that will contribute to this biological diversity and cultural identity
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