Several Avian paramyxoviruses 1 (synonymous with Newcastle disease virus or NDV, used hereafter) classification systems have been proposed for strain identification and differentiation. These systems pioneered classification efforts; however, they were based on different approaches and lacked objective criteria for the differentiation of isolates. These differences have created discrepancies among systems, rendering discussions and comparisons across studies difficult. Although a system that used objective classification criteria was proposed by Diel and co-workers in 2012, the ample worldwide circulation and constant evolution of NDV, and utilization of only some of the criteria, led to identical naming and/or incorrect assigning of new sub/genotypes. To address these issues, an international consortium of experts was convened to undertake in-depth analyses of NDV genetic diversity. This consortium generated curated, up-to-date, complete fusion gene class I and class II datasets of all known NDV for public use, performed comprehensive phylogenetic neighbor-Joining, maximum-likelihood, Bayesian and nucleotide distance analyses, and compared these inference methods. An updated NDV classification and nomenclature system that incorporates phylogenetic topology, genetic distances, branch support, and epidemiological independence was developed. This new consensus system maintains two NDV classes and existing genotypes, identifies three new class II genotypes, and reduces the number of sub-genotypes. In order to track the ancestry of viruses, a dichotomous naming system for designating sub-genotypes was introduced. In addition, a pilot dataset and sub-trees rooting guidelines for rapid preliminary genotype identification of new isolates are provided. Guidelines for sequence dataset curation and phylogenetic inference, and a detailed comparison between the updated and previous systems are included. To increase the speed of phylogenetic inference and ensure consistency between laboratories, detailed guidelines for the use of a supercomputer are also provided. The proposed unified classification system will facilitate future studies of NDV evolution and epidemiology, and comparison of results obtained across the world.

We analyzed the highly pathogenic avian influenza (HPAI) H5 epizootic of 2016–17 in Europe by epidemiologic and genetic characteristics and compared it with 2 previous epizootics caused by the same H5 Guangdong lineage. The 2016–17 epizootic was the largest in Europe by number of countries and farms affected and greatest diversity of wild birds infected. We observed significant differences among the 3 epizootics regarding region affected, epidemic curve, seasonality, and outbreak duration, making it difficult to predict future HPAI epizootics. However, we know that in 2005–06 and 2016–17 the initial peak of wild bird detections preceded the peak of poultry outbreaks within Europe. Phylogenetic analysis of 2016–17 viruses indicates 2 main pathways into Europe. Our findings highlight the need for global surveillance of viral changes to inform disease preparedness, detection, and control.

Our study demonstrates the repeated isolation of vaccine-derived Newcastle disease viruses from different species of wild birds across four continents from 1997 through 2014. The data indicate that at least 17 species from ten avian orders occupying different habitats excrete vaccine-derived Newcastle disease viruses. The most frequently reported isolates were detected among individuals in the order Columbiformes (n = 23), followed in frequency by the order Anseriformes (n = 13). Samples were isolated from both free-ranging (n = 47) and wild birds kept in captivity (n = 7). The number of recovered vaccine-derived viruses corresponded with the most widely utilized vaccines, LaSota (n = 28) and Hitchner B1 (n = 19). Other detected vaccine-derived viruses resembled the PHY-LMV2 and V4 vaccines, with five and two cases, respectively. These results and the ubiquitous and synanthropic nature of wild pigeons highlight their potential role as indicator species for the presence of Newcastle disease virus of low virulence in the environment. The reverse spillover of live agents from domestic animals to wildlife as a result of the expansion of livestock industries employing massive amounts of live virus vaccines represent an underappreciated and poorly studied effect of human activity on wildlife.

This study reports the first incursion into European poultry of H5N1 highly pathogenic notifiable avian influenza A (HPNAI) viruses from clade 2.3.2 that affected domestic poultry and wild birds in Romania and Bulgaria, respectively. Previous occurrences in Europe of HPNAI H5N1 in these avian populations have involved exclusively viruses from clade 2.2. This represents the most westerly spread of clade 2.3.2 viruses, which have shown an apparently expanding range of geographical dispersal since mid‐2009 following confirmation of infections in wild waterfowl species in Mongolia and Eastern Russia. During March 2010, AI infection was suspected at post‐mortem examination of two hens from two backyard flocks in Tulcea Country, Romania. HPNAI of H5N1 subtype was confirmed by reverse transcription polymerase chain reaction (RT‐PCR). A second outbreak was confirmed 2 weeks later by RT‐PCR, affecting all hens from another flock located 55 km east of the first cluster. On the same day, an H5N1 HPNAI virus was detected from a pooled tissue sample collected from a dead Common Buzzard found on the Black Sea coast in Bulgaria. Detailed genetic characterization of the haemagglutinin gene revealed the cleavage site of the isolates to be consistent with viruses of high pathogenicity belonging to clade 2.3.2 of the contemporary Eurasian H5N1 lineage. Viruses from a clade other than 2.2 have apparently spread to wild birds, with potential maintenance and spread through such populations. Whilst the scale of threat posed by the apparent westward spread of the clade 2.3.2 viruses remains uncertain, ongoing vigilance for clinical signs of disease as part of existing passive surveillance frameworks for AI, and the prompt reporting of suspect cases in poultry is advised.