RESUMEN
Highly pathogenic avian influenza (HPAI) H5N8 is currently causing an epizootic in Europe, infecting many poultry holdings as well as captive and wild bird species in more than 10 countries. Given the clear clinical manifestation, passive surveillance is considered the most effective means of detecting infected wild and domestic birds. Testing samples from new species and non-previously reported areas is key to determine the geographic spread of HPAIV H5N8 2016 in wild birds. Testing limited numbers of dead wild birds in previously reported areas is useful when it is relevant to know whether the virus is still present in the area or not, e.g. before restrictive measures in poultry are to be lifted. To prevent introduction of HPAIV from wild birds into poultry, strict biosecurity implemented and maintained by the poultry farmers is the most important measure. Providing holding-specific biosecurity guidance is strongly recommended as it is expected to have a high impact on the achieved biosecurity level of the holding. This is preferably done during peace time to increase preparedness for future outbreaks. The location and size of control and in particular monitoring areas for poultry associated with positive wild bird findings are best based on knowledge of the wider habitat and flight distance of the affected wild bird species. It is recommended to increase awareness among poultry farmers in these established areas in order to enhance passive surveillance and to implement enhanced biosecurity measures including poultry confinement. There is no scientific evidence suggesting a different effectiveness of the protection measures on the introduction into poultry holdings and subsequent spread of HPAIV when applied to H5N8, H5N1 or other notifiable HPAI viruses.
RESUMEN
A major problem in risk assessment is the quantification of uncertainties. A probabilistic model was developed to consider uncertainties in the effect assessment of hazardous substances at the workplace. Distributions for extrapolation factors (time extrapolation, inter- and intraspecies extrapolation) were determined on the basis of appropriate empirical data. Together with the distribution for the benchmark dose obtained from substance-specific dose-response modelling for the exemplary substances 2,4,4-trimethylpentene (TMP) and aniline, they represent the input distributions for probabilistic modelling. These distributions were combined by Monte Carlo simulation. The resulting target distribution describes the probability that an aspired protection level for workers is achieved at a certain dose and the uncertainty associated with the assessment. In the case of aniline, substance-specific data on differences in susceptibility (between species; among humans due to genetic polymorphisms of N-acetyltransferase) were integrated in the model. Medians of the obtained target distributions of the basic models for TMP and aniline, but not of the specific aniline model are similar to deterministically derived reference values. Differences of more than one order of magnitude between the medians and the 5th percentile of the target distributions indicate substantial uncertainty associated with the effect assessment of these substances. The probabilistic effect assessment model proves to be a practical tool to integrate quantitative information on uncertainty and variability in hazard characterisation.
