Abstract
Viral sequence data coupled with phylodynamic models have become instrumental in investigating the outbreaks of human and animal diseases, and the incorporation of the hypothesized drivers of pathogen spread can enhance the interpretation from phylodynamic inference. Integrating animal movement data with phylodynamics allows us to quantify the extent to which the spatial diffusion of a pathogen is influenced by animal movements and contrast the relative importance of different types of movements in shaping pathogen distribution. We combine animal movement, spatial, and environmental data in a Bayesian phylodynamic framework to explain the spatial diffusion and evolutionary trends of a rapidly spreading sub-lineage (denoted L1A) of porcine reproductive and respiratory syndrome virus (PRRSV) Type 2 from 2014 to 2017. PRRSV is the most important endemic pathogen affecting pigs in the USA, and this particular virulent sub-lineage emerged in 2014 and continues to be the dominant lineage in the US swine industry to date. Data included 984 open reading frame 5 (ORF5) PRRSV L1A sequences obtained from two production systems in a swine-dense production region (∼85,000 mi2) in the USA between 2014 and 2017. The study area was divided into sectors for which model covariates were summarized, and animal movement data between each sector were summarized by age class (wean: 3–4 weeks; feeder: 8–25 weeks; breeding: ≥21 weeks). We implemented a discrete-space phylogeographic generalized linear model using Bayesian evolutionary analysis by sampling trees (BEAST) to infer factors associated with variability in between-sector diffusion rates of PRRSV L1A. We found that between-sector spread was enhanced by the movement of feeder pigs, spatial adjacency of sectors, and farm density in the destination sector. The PRRSV L1A strain was introduced in the study area in early 2013, and genetic diversity and effective population size peaked in 2015 before fluctuating seasonally (peaking during the summer months). Our study underscores the importance of animal movements and shows, for the first time, that the movement of feeder pigs (8–25 weeks old) shaped the spatial patterns of PRRSV spread much more strongly than the movements of other age classes of pigs. The inclusion of movement data into phylodynamic models as done in this analysis may enhance our ability to identify crucial pathways of disease spread that can be targeted to mitigate the spatial spread of infectious human and animal pathogens.
Highlights
Porcine reproductive and respiratory syndrome (PRRS) is a viral disease of swine caused by a ribonucleic acid (RNA) arterivirus broadly classified as PRRS virus (PRRSV) Type 1 (Eurpobartevirus Betaarterivirus suid 1) and Type 2 (Ampobartevirus Betaarterivirus suid 2) (Kuhn et al, 2016; Shi et al, 2010a; Stadejek et al, 2013; Walker et al, 2020)
Through integrating Bayesian phylodynamic models built with porcine reproductive and respiratory syndrome virus (PRRSV) open reading frame 5 (ORF5) sequence data with empirical pig movement data, we investigate the role of host population connectivity and the relative importance of animal movements stratified by age class in the spread of PRRSV
This suggests a single introduction of this lineage to the region. This analysis was based on the ORF5 region only, we believe that an analysis of whole genome data would result in a the most recent common ancestor (TMRCA), as viral isolates classified into lineages based on ORF5 generally maintain their phylogenetic clades when using whole genome analysis (Schroeder et al, submitted)
Summary
Porcine reproductive and respiratory syndrome (PRRS) is a viral disease of swine caused by a ribonucleic acid (RNA) arterivirus broadly classified as PRRS virus (PRRSV) Type 1 (Eurpobartevirus Betaarterivirus suid 1) and Type 2 (Ampobartevirus Betaarterivirus suid 2) (Kuhn et al, 2016; Shi et al, 2010a; Stadejek et al, 2013; Walker et al, 2020). Since the initial detection of PRRS in the USA in the early 1990s, the swine industry has made considerable efforts to understand and manage the disease These efforts have included the implementation of strict biosecurity measures on swine farms (Velasova et al, 2012; Silva et al, 2019), different immunization programs (Corzo et al, 2010), disease surveillance, and monitoring programs (Perez et al, 2019) among others. Despite these efforts, effective management and control of PRRS remain a challenge. These difficulties have been attributed to several factors, key among them being the importance of animal movements and environmental factors in between-farm spread (Otake et al, 2010; Pileri and Mateu 2016; Arruda et al, 2018a; VanderWaal et al, 2020) and rapid viral evolution resulting in substantial genetic and antigenic diversities (Charerntantanakul 2012; Paploski et al, 2019)
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