The genetic diversity and frequent emergence of novel genetic variants of porcine reproductive and respiratory syndrome virus type-2 (PRRSV) hinders control efforts, yet drivers of macro-evolutionary patterns of PRRSV remain poorly documented. Utilizing a comprehensive database of >20,000 orf5 sequences, our objective was to classify variants according to the phylogenetic structure of PRRSV co-circulating in the U.S., quantify evolutionary dynamics of sub-lineage emergence, and describe potential antigenic differences among sub-lineages. We subdivided the most prevalent lineage (Lineage 1, accounting for approximately 60% of available sequences) into eight sub-lineages. Bayesian coalescent SkyGrid models were used to estimate each sub-lineage’s effective population size over time. We show that a new sub-lineage emerged every 1 to 4 years and that the time between emergence and peak population size was 4.5 years on average (range: 2–8 years). A pattern of sequential dominance of different sub-lineages was identified, with a new dominant sub-lineage replacing its predecessor approximately every 3 years. Consensus amino acid sequences for each sub-lineage differed in key GP5 sites related to host immunity, suggesting that sub-lineage turnover may be linked to immune-mediated competition. This has important implications for understanding drivers of genetic diversity and emergence of new PRRSV variants in the U.S.

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Eimeriosis is caused by a protozoan infection affecting most domestic animal species. Outbreaks in cattle are associated with various environmental factors in temperate climates but limited work has been done in tropical settings. The objective of this work was to determine the prevalence and environmental factors associated with bovine Eimeria spp. infection in a mixed farming area of western Kenya. A total of 983 cattle were sampled from 226 cattle-keeping households. Faecal samples were collected directly from the rectum via digital extraction and analysed for the presence of Eimeria spp. infection using the MacMaster technique. Individual and household level predictors of infection were explored using mixed effects logistic regression. The prevalence of individual animal Eimeria infection was 32.8% (95% CI 29.9–35.9). A positive linear relationship was found between risk of Eimeria infection and increasing temperature (OR = 1.4, 95% CI 1.06–1.86) and distance to areas at risk of flooding (OR = 1.49, 95% CI 1.17–1.91). There was weak evidence of non-linear relationship between Eimeria infection and the proportion of the area around a household that was classified as swamp (OR = 1.12, 95% CI 0.87–1.44; OR (quadratic term) = 0.85, 95% CI 0.73–1.00), and the sand content of the soil (OR = 1.18, 95% CI 0.91–1.53; OR (quadratic term) = 1.1, 95% CI 0.99–1.23). The risk of animal Eimeria spp. infection is influenced by a number of climatic and soil-associated conditions.

Viral sequence data coupled with phylodynamic models have become instrumental in investigating outbreaks of human and animal diseases, and incorporation of 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 2014-17. PRRSV is the most important endemic pathogen affecting pigs in the U.S., and this particular virulent sub-lineage emerged in 2014 and continues to be the dominant lineage in the U.S. swine industry to date. Data included 984 ORF5 PRRSV L1A sequences obtained from two production systems in a swine dense production region (~ 85,000 mi2) in the U.S. between 2014 and 2017. The study area was divided into sectors for which model covariates were summarized, and animal movement data between each sector was 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 summer months). Our study underscores the importance of animal movements and shows, for the first time, that movement of feeder pigs (8-25 weeks old) shaped spatial patterns of PRRSV spread much more strongly than 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.

Swine production in the United States is characterized by dynamic farm contacts through animal movements; such movements shape the risk of disease occurrence on farms. Pig movements have been linked to the spread of a virulent porcine reproductive and respiratory syndrome virus (PRRSV), RFLP type 1‐7‐4, herein denoted as phylogenetic sub‐lineage 1A [L1A]. This study aimed to quantify the contribution of pig movements to the risk of L1A occurrence on farms in the United States. Farms were defined as L1A‐positive in a given 6‐month period if at least one L1A sequence was recovered from the farm. Temporal network autocorrelation modelling was performed using data on animal movements and 1,761 PRRSV ORF5 sequences linked to 494 farms from a dense pig production area in the United States between 2014 and 2017. A farm's current and past exposure to L1A and other PRRSV variants was assessed through its primary and secondary contacts in the animal movement network. Primary and secondary contacts with an L1A‐positive farm increased the likelihood of L1A occurrence on a farm by 19% (p = .04) and 23% (p = .03), respectively. While the risk posed by primary contacts with PRRS‐positive farms is unsurprising, the observation that secondary contacts also increase the likelihood of infection is novel. Risk of L1A occurrence on a farm also increased by 3.0% (p = .01) for every additional outgoing shipment, possibly due to biosecurity breaches during loading and transporting pigs from the farm. Finally, use of vaccines or field virus inoculation on sow farms one year prior reduced the risk of L1A occurrence in downstream farms by 36% (p = .04), suggesting that control measures that reduce viral circulation and enhance immunological protection in sow farms have a carry‐over effect on L1A occurrence in downstream farms. Therefore, coordinated disease management interventions between farms connected via animal movements may be more effective than individual farm‐based interventions.