2 resultados para grid-based spatial data
em Universidade Complutense de Madrid
Resumo:
Ebola virus disease is a lethal human and primate disease that requires a particular attention from the international health authorities due to important recent outbreaks in some Western African countries and isolated cases in European and North-America continents. Regarding the emergency of this situation, various decision tools, such as mathematical models, were developed to assist the authorities to focus their efforts in important factors to eradicate Ebola. In a previous work, we have proposed an original deterministic spatial-temporal model, called Be-CoDiS (Between-Countries Disease Spread), to study the evolution of human diseases within and between countries by taking into consideration the movement of people between geographical areas. This model was validated by considering numerical experiments regarding the 2014-16 West African Ebola Virus Disease epidemic. In this article, we propose to perform a stability analysis of Be-CoDiS. Our first objective is to study the equilibrium states of simplified versions of this model, limited to the cases of one an two countries, and to determine their basic reproduction ratios. Then, in order to give some recommendations for the allocation of resources used to control the disease, we perform a sensitivity analysis of those basic reproduction ratios regarding the model parameters. Finally, we validate the obtained results by considering numerical experiments based on data from the 2014-16 West African Ebola Virus Disease epidemic.
Resumo:
The objective of this study was to determine the dynamics and diversity of Escherichia coli populations in animal and environmental lines of a commercial farrow-to-finish pig farm in Spain along a full production cycle (July 2008 to July 2009), with special attention to antimicrobial resistance and the presence of integrons. In the animal line, a total of 256 isolates were collected from pregnant sows (10 samples and 20 isolates), 1-week-old piglets (20 samples and 40 isolates), unweaned piglets (20 samples and 38 isolates), growers (20 samples and 40 isolates), and the finishers' floor pen (6 samples and 118 isolates); from the underfloor pits and farm slurry tank environmental lines, 100 and 119 isolates, respectively, were collected. Our results showed that E. coli populations in the pig fecal microbiota and in the farm environment are highly dynamic and show high levels of diversity. These issues have been proven through DNA-based typing data (repetitive extragenic palindromic PCR [REP-PCR]) and phenotypic typing data (antimicrobial resistance profile comprising 19 antimicrobials). Clustering of the sampling groups based on their REP-PCR typing results showed that the spatial features (the line) had a stronger weight than the temporal features (sampling week) for the clustering of E. coli populations; this weight was less significant when clustering was performed based on resistotypes. Among animals, finishers harbored an E. coli population different from those of the remaining animal populations studied, considering REP-PCR fingerprints and resistotypes. This population, the most important from a public health perspective, demonstrated the lowest levels of antimicrobial resistance and integron presence.