Identification of Hotspots in the European Union for the Introduction of Four Zoonotic Arboviroses by Live Animal Trade

Live animal trade is considered a major mode of introduction of viruses from enzootic foci into disease-free areas. Due to societal and behavioural changes, some wild animal species may nowadays be considered as pet species. The species diversity of animals involved in international trade is thus increasing. This could benefit pathogens that have a broad host range such as arboviruses. The objective of this study was to analyze the risk posed by live animal imports for the introduction, in the European Union (EU), of four arboviruses that affect human and horses: Eastern and Western equine encephalomyelitis, Venezuelan equine encephalitis and Japanese encephalitis. Importation data for a five-years period (2005-2009, extracted from the EU TRACES database), environmental data (used as a proxy for the presence of vectors) and horses and human population density data (impacting the occurrence of clinical cases) were combined to derive spatially explicit risk indicators for virus introduction and for the potential consequences of such introductions. Results showed the existence of hotspots where the introduction risk was the highest in Belgium, in the Netherlands and in the north of Italy. This risk was higher for Eastern equine encephalomyelitis (EEE) than for the three other diseases. It was mainly attributed to exotic pet species such as rodents, reptiles or cage birds, imported in small-sized containments from a wide variety of geographic origins. The increasing species and origin diversity of these animals may have in the future a strong impact on the risk of introduction of arboviruses in the EU.

Spitzer's contribution to the AGN population

Infrared selection is a potentially powerful way to identify heavily obscured AGNs missed in even the deepest X-ray surveys. Using a 24 μm-selected sample in GOODS-S, we test the reliability and completeness of three infrared AGN selection methods: (1) IRAC color-color selection, (2) IRAC power-law selection, and (3) IR-excess selection; we also evaluate a number of IR-excess approaches. We find that the vast majority of non-power-law IRAC color-selected AGN candidates in GOODS-S have colors consistent with those of star-forming galaxies. Contamination by star-forming galaxies is most prevalent at low 24 μm flux densities (~100 μJy) and high redshifts (z ~ 2), but the fraction of potential contaminants is still high (~50%) at 500 μJy, the highest flux density probed reliably by our survey. AGN candidates selected via a simple, physically motivated power-law criterion ("power-law galaxies," or PLGs), however, appear to be reliable. We confirm that the IR-excess methods successfully identify a number of AGNs, but we also find that such samples may be significantly contaminated by star-forming galaxies. Adding only the secure Spitzer-selected PLG, color-selected, IR-excess, and radio/IR-selected AGN candidates to the deepest X-ray-selected AGN samples directly increases the number of known X-ray AGNs (84) by 54%-77%, and implies an increase to the number of 24 μm-detected AGNs of 71%-94%. Finally, we show that the fraction of MIR sources dominated by an AGN decreases with decreasing MIR flux density, but only down to f_24 μ m = 300 μJy. Below this limit, the AGN fraction levels out, indicating that a nonnegligible fraction (~10%) of faint 24 μm sources (the majority of which are missed in the X-ray) are powered not by star formation, but by the central engine. The fraction of all AGNs (regardless of their MIR properties) exceeds 15% at all 24 μm flux densities.