Stability and sensitivity analysis of Be-CoDiS, an epidemiological model to predict the spread of human diseases between countries. Validation with data from the 2014-16 West African Ebola Virus Disease epidemic.

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.

Principal Component Analysis of Results Obtained from Finite-Difference Time-Domain Algorithms

Finite-Differences Time-Domain (FDTD) algorithms are well established tools of computational electromagnetism. Because of their practical implementation as computer codes, they are affected by many numerical artefact and noise. In order to obtain better results we propose using Principal Component Analysis (PCA) based on multivariate statistical techniques. The PCA has been successfully used for the analysis of noise and spatial temporal structure in a sequence of images. It allows a straightforward discrimination between the numerical noise and the actual electromagnetic variables, and the quantitative estimation of their respective contributions. Besides, The GDTD results can be filtered to clean the effect of the noise. In this contribution we will show how the method can be applied to several FDTD simulations: the propagation of a pulse in vacuum, the analysis of two-dimensional photonic crystals. In this last case, PCA has revealed hidden electromagnetic structures related to actual modes of the photonic crystal.

Analysis of the genome content of Lactococcus garvieae by genomic interspecies microarray hybridization

BACKGROUND Lactococcus garvieae is a bacterial pathogen that affects different animal species in addition to humans. Despite the widespread distribution and emerging clinical significance of L. garvieae in both veterinary and human medicine, there is almost a complete lack of knowledge about the genetic content of this microorganism. In the present study, the genomic content of L. garvieae CECT 4531 was analysed using bioinformatics tools and microarray-based comparative genomic hybridization (CGH) experiments. Lactococcus lactis subsp. lactis IL1403 and Streptococcus pneumoniae TIGR4 were used as reference microorganisms. RESULTS The combination and integration of in silico analyses and in vitro CGH experiments, performed in comparison with the reference microorganisms, allowed establishment of an inter-species hybridization framework with a detection threshold based on a sequence similarity of >or= 70%. With this threshold value, 267 genes were identified as having an analogue in L. garvieae, most of which (n = 258) have been documented for the first time in this pathogen. Most of the genes are related to ribosomal, sugar metabolism or energy conversion systems. Some of the identified genes, such as als and mycA, could be involved in the pathogenesis of L. garvieae infections. CONCLUSIONS In this study, we identified 267 genes that were potentially present in L. garvieae CECT 4531. Some of the identified genes could be involved in the pathogenesis of L. garvieae infections. These results provide the first insight into the genome content of L. garvieae.