Contrasting animal movement and spatial connectivity networks in shaping transmission pathways of a genetically diverse virus

VanderWaal, Kimberly; Paploski, Igor Adolfo Dexheimer; Makau, Dennis N.; Corzo, Cesar

doi:10.1016/j.prevetmed.2020.104977

Cited by 27 publications

(32 citation statements)

References 42 publications

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“…The important contribution of the local transmission route in spreading PRRSV into sow, GDU and finisher farms was consistent with previous studies, which demonstrated that farms located close to infected sites were more likely to report PRRSV outbreaks (Velasova et al, 2012; Phoo-ngurn et al, 2019; Silva et al, 2019; Jara et al, 2020), while others suggested that contact networks was the preferred transmission route (Amirpour Haredasht et al, 2017; Lee et al, 2017; Bastard et al, 2020; VanderWaal et al, 2020). Our approach to model the local PRRSV spread was unique in that we considered the effect of vegetation around each farm location as a physical barrier against mainly airborne transmission (Van Ryswyk et al, 2019; Jara et al, 2020).…”

Section: Discussionsupporting

confidence: 89%

Modeling the transmission and vaccination strategy for porcine reproductive and respiratory syndrome virus

Galvis

Prada

Jones

et al. 2020

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14 15 In the monitoring of porcine reproductive and respiratory syndrome virus (PRRSv), 16 knowledge about between-farm transmission dynamics is still lacking. Our objective was 17 to assess the relative contribution of between-farm PRRSv transmission routes through a 18 mechanistic epidemiological model calibrated with PRRSv occurrence, identify risk 19 areas, and estimate the impact of immunization strategies in the disease spread. We 20 developed a mathematical model of PRRSv transmission accounting for spatial 21 proximity, pig movements, and re-breaks in sow farms, parametrized on data collected 22 routinely by commercial pig farms. We then used the model to simulate the weekly 23 frequency of cases and built risk maps, and compared with the observed cases. We 24 simulated the implementation of two immunization strategies (preventive and reactive) to 25 mitigate the between-farm transmission. Our results indicated for sow and GDU farms' 26 local spread on average was above 60%, while for nurseries between-farm movements 27 represented 83% of transmissions and in finisher farms it was distributed almost 50% 28 local and 50% between-farm movement, the model allowed reproduce the weekly 29 frequency of observed cases and the risk maps built allowed the identification of 30 observed cases in the space. The increase in vaccine efficacy was the most important 31 parameter to mitigate between-farm transmission. Also, the implementation of 32 immunization by a preventive and reactive strategy combined had the better result to 33 mitigate between-farm transmission than implement these strategies individually. These 34 immunization strategies had a better performance with the use of rigorous protocols, such 35

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Section: Discussionsupporting

confidence: 89%

Modeling the transmission and vaccination strategy for porcine reproductive and respiratory syndrome virus

Galvis

Prada

Jones

et al. 2020

Preprint

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“…However these lineages have continued to diversify, and using a dataset from a single U.S. region from years 2009-2017, at least three sub-lineages within Lineage 1 have been documented, with sequential turnover in the dominant lineages through time [23]. In addition, the emergence of new sub-lineages can occur on time scales as short as two years (as observed for the 1A sub-lineage associated with RFLP-type 1-7-4) [23], with rapid spread of emerging sub-lineages driven by animal movements and local area spread [26,27].…”

Section: Introductionmentioning

confidence: 98%

Phylogenetic Structure and Sequential Dominance of Sub-Lineages of PRRSV Type-2 Lineage 1 in the United States

et al. 2021

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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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“…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 ).…”

Section: Introductionmentioning

confidence: 99%

Integrating animal movements with phylogeography to model the spread of PRRSV in the USA

et al. 2021

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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.

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Contrasting animal movement and spatial connectivity networks in shaping transmission pathways of a genetically diverse virus

Cited by 27 publications

References 42 publications

Modeling the transmission and vaccination strategy for porcine reproductive and respiratory syndrome virus

Modeling the transmission and vaccination strategy for porcine reproductive and respiratory syndrome virus

Phylogenetic Structure and Sequential Dominance of Sub-Lineages of PRRSV Type-2 Lineage 1 in the United States

Integrating animal movements with phylogeography to model the spread of PRRSV in the USA

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