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.

Despite considerable effort for surveillance of wild birds for avian influenza viruses (AIVs), empirical investigations of ecological drivers of AIV prevalence in wild birds are still scarce. Here we used a continental-scale dataset, collected in tropical wetlands of 15 African countries, to test the relative roles of a range of ecological factors on patterns of AIV prevalence in wildfowl. Seasonal and geographical variations in prevalence were positively related to the local density of the wildfowl community and to the wintering period of Eurasian migratory birds in Africa. The predominant influence of wildfowl density with no influence of climatic conditions suggests, in contrast to temperate regions, a predominant role for inter-individual transmission rather than transmission via long-lived virus persisting in the environment. Higher prevalences were found in Anas species than in non-Anas species even when we account for differences in their foraging behaviour (primarily dabbling or not) or their geographical origin (Eurasian or Afro-tropical), suggesting the existence of intrinsic differences between wildfowl taxonomic groups in receptivity to infection. Birds were found infected as often in oropharyngeal as in cloacal samples, but rarely for both types of sample concurrently, indicating that both respiratory and digestive tracts may be important for AIV replication.

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