Evolutionary dynamics and transmission patterns of Newcastle disease virus in China through Bayesian phylogeographical analysis

Abstract

The Chinese poultry industry has experienced outbreaks of Newcastle disease (ND) dating back to the 1920s. However, the epidemic has exhibited a downtrend in recent years. In this study, both observational and genetic data [fusion (F) and haemagglutinin-neuraminidase genes (HN)] were analyzed, and phylogeographic analysis based on prevalent genotypes of Newcastle disease virus (NDV) was conducted for better understanding of the evolution and spatiotemporal dynamics of ND in China. In line with the observed trend of epidemic outbreaks, the effective population size of F and HN genes of circulating NDV is no longer growing since 2000, which is supported by 95% highest posterior diversity (HPD) intervals. Phylogeographic analysis indicated that the two eastern coastal provinces, Shandong and Jiangsu were the most relevant hubs for NDV migration, and the geographical regions with active NDV diffusion seemed to be constrained to southern and eastern China. The live poultry trade may play an important role in viral spread. Interestingly, no migration links from wild birds to poultry received Bayes factor support (BF > 3), while the migration links from poultry to wild birds accounted for 64% in all effective migrations. This may indicate that the sporadic cases of ND in wild bird likely spillover events from poultry. These findings contribute to predictive models of NDV transmission, and potentially help in the prevention of future outbreaks.

Fig 1. The total number of annual outbreaks, cases, and deaths of NDV in China from 2006 to 2019.

Fig 2. Bayesian skyline plot of genotypes VI and VII NDVs in China.

Effective population size estimates are expressed on a logarithmic scale (Y-axis), and the x-axis represents time (years). The dark thick lines denote the median estimates and the light thin lines give the 95% HPD intervals of the estimate. The dark blue, red and green thick lines represent the median estimates of VI-F gene, VII-F gene and VII-HN gene, respectively. The light blue, red and green thin lines represent the 95% HPD intervals of the estimates of VI-F gene, VII-F gene and VII-HN gene, respectively.

Fig 3. Migration link map of genotypes VI and VII NDVs in China supported by Bayes factor.

(A) VI-F gene, (B) VII-F gene (subsample one), (C) VII-HN gene. The line colour represents the relative strength by which the rates are supported: very strong (BF > 100, red lines), strong (20 < BF < 100, blue lines) and positive (3 < BF < 20, green lines). The thickness of the arrows indicates increasing number of Markov jumps between locations.

Fig 4. Predictors of NDV dispersal across China.

(A), (B) and (C) represent the contributions of predictor variables to the dissemination of viral VI-F, VII-F and VII-HN genes, respectively; VI-F,VII-F and VII-HN genes are shown as green, red and blue, respectively. (Left) Circles show the estimated conditional effect sizes for the predictor coefficients (> 0 = positive association, < 0 = negative association). Error bars represent the 95% highest posterior density (HPD) credible interval for these estimates. (Right) Bars show the posterior probability of inclusion of each predictor in the model.