What can phylodynamics bring to animal health research?

Guinat, Claire; Vergne, Timothée; Kocher, Arthur; Chakraborty, Debapryio; Paul, Mathilde; Ducatez, Mariette; Stadler, Tanja

doi:10.1016/j.tree.2021.04.013

Cited by 12 publications

(8 citation statements)

References 101 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further confirmation of the role of interhost transmission in epidemic propagation can be achieved through phylodynamic approaches, where phylogenetics is coupled with epidemiological data. Such an approach demonstrates particular promise at elucidating transmission parameters and quantifying spillover events (32). However, the choice of use of such methods has dependence on viral genetic characteristics, and ASFV, being a large double-stranded DNA virus-therefore subject to very slow mutation rates-may currently limit successes of this approach.…”

Section: Estimated Parameters and Replicated Dynamicsmentioning

confidence: 99%

A multi-host mechanistic model of African swine fever emergence and control in Romania

Hayes,

Vergne,

Rose

et al. 2024

Preprint

View full text Add to dashboard Cite

African swine fever (ASF) has devastating effects on swine production, farmer livelihood, animal welfare, and biodiversity. Extremely difficult to control, epidemic management is further complicated when spillover between domestic pig and wild boar populations is suspected. To quantify ASF viral transmission between domestic pigs and wild boar, a spatially-explicit stochastic mechanistic model was constructed using village centroids to represent aggregated backyard pig herds and a hexagonal raster of forest coverage to represent wild boar abundance. The model was parameterized to the initial six months of the ongoing Romanian epidemic through approximate Bayesian computation. It was estimated that a median of 69.4% (interquartile range: 53.0–80.0%) of domestic pig herd cases came from other infected domestic pig herds while 20.4% (11.2–33.8%) originated from infected wild boar sources, and 8.4% (4.7–14.2%) stemmed from external sources not explicitly represented. Also, 31.9% of infected wild boar habitat (16.7–56.2%) originated from domestic pig herds and 68.1% (43.8–83.3%) came from neighboring infected wild boar populations. Furthermore, it was found that habitats with a forest coverage greater than 15% were 2.6 times more infectious and 5.3 times more susceptible than other habitats. All alternative control scenarios, including culling domestic pig herds upon local domestic pig or wild boar case detection, improved epidemic outcomes, with the greatest decrease in final epidemic size being observed from the reactive culling of entire villages following case detection. These results can be used to further inform policy recommendations in ASF-epidemic regions.Significance StatementThe current African swine fever (ASF) pandemic is devastating to affected nations, and quantifying transmission parameters is critical to informing control strategies. Disease spillover between wild and domestic hosts further complicates control efforts, yet the influence of spillover events on epidemic propagation remains unknown. Using the context of Romania—one of the European nations with the most severe epidemic and where spillover transmission is strongly suspected—we show that targeting spillover mechanisms is critical for achieving holistic disease control, and then demonstrate the impact of alternative control scenarios had they been enacted. These results can inform control strategy policy decisions in the many nations at-risk for or actively experiencing ASF epidemics.

show abstract

Section: Estimated Parameters and Replicated Dynamicsmentioning

confidence: 99%

A multi-host mechanistic model of African swine fever emergence and control in Romania

Hayes,

Vergne,

Rose

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Pathogen whole-genome sequencing (WGS) is an invaluable tool for understanding transmission patterns in infectious diseases [1][2][3][4]. Underpinning such use of pathogen WGS data is the relationship between the rates at which evolutionary processes occur (the "molecular clock" [5]), and the timescale of epidemiological processes of interest (e.g.…”

Section: Introductionmentioning

confidence: 99%

The utility of whole-genome sequencing to identify likely transmission pairs for pathogens with slow and variable evolution

Wood,

Benton,

Delahay

et al. 2024

Preprint

View full text Add to dashboard Cite

Pathogen whole-genome sequencing (WGS) has been used to track the transmission of infectious diseases in extraordinary detail, especially for pathogens that undergo fast and steady evolution, as is the case with many RNA viruses. However, for other pathogens evolution is less predictable, making interpretation of these data to inform our understanding of their epidemiology more challenging and the value of densely collected pathogen genome data uncertain. Here, we assess the utility of WGS for one such pathogen, in the "who-infected-whom" identification problem. We study samples from hosts (130 cattle, 111 badgers) with confirmed infection of M. bovis (causing bovine Tuberculosis), which has an estimated clock rate as slow as ~0.1-1 variations per year. For each potential pathway between hosts, we calculate the likelihood that such a transmission event occurred. This is informed by an epidemiological model of transmission, and host life history data. By including WGS data, we shrink the number of plausible pathways significantly, relative to those deemed likely on the basis of life history data alone. Despite our uncertainty relating to the evolution of M. bovis, the WGS data are therefore a valuable adjunct to epidemiological investigations, especially for wildlife species whose life history data are sparse.

show abstract

“…They have been used extensively for fast-evolving organisms, in particular human RNA viruses, as they can identify nucleotide variations in genomes that serve to estimate pathogen evolution and transmission dynamics over the course of a single epidemic [2,3]. A recent review highlighted the value of phylodynamic approaches to help understand patterns of disease transmission and design more effective control strategies in OPEN ACCESS animal health research [4]. Phylodynamic methods can also be employed to monitor outbreaks caused by bacteria or other slow-evolving pathogens, although with some limitations [5].…”

Section: Introductionmentioning

confidence: 99%

Genome-wide phylodynamic approach reveals the epidemic dynamics of the main Mycoplasma bovis subtype circulating in France

et al. 2023

View full text Add to dashboard Cite

Mycoplasma bovis is a major aetiological agent of bovine respiratory disease worldwide. Genome-based analyses are increasingly being used to monitor the genetic diversity and global distribution of M. bovis , complementing existing subtyping schemes based on locus sequencing. However, these analyses have so far provided limited information on the spatiotemporal and population dynamics of circulating subtypes. Here we applied a genome-wide phylodynamic approach to explore the epidemic dynamics of 88 French M. bovis strains collected between 2000 and 2019 in France and belonging to the currently dominant polC subtype 2 (st2). A strong molecular clock signal detected in the genomic data enabled robust phylodynamic inferences, which estimated that the M. bovis st2 population in France is composed of two lineages that successively emerged from independent introductions of international strains. The first lineage appeared around 2000 and supplanted the previously established antimicrobial-susceptible polC subtype 1. The second lineage, which is likely more transmissible, progressively replaced the first M. bovis st2 lineage population from 2005 onward and became predominant after 2010. Analyses also showed a brief decline in this second M. bovis st2 lineage population in around 2011, possibly due to the challenge from the concurrent emergence of M. bovis polC subtype 3 in France. Finally, we identified non-synonymous mutations in genes associated with lineages, which raises prospects for identifying new surveillance molecular markers. A genome-wide phylodynamic approach provides valuable resources for monitoring the evolution and epidemic dynamics of circulating M. bovis subtypes, and may prove critical for developing more effective surveillance systems and disease control strategies.

show abstract

What can phylodynamics bring to animal health research?

Cited by 12 publications

References 101 publications

A multi-host mechanistic model of African swine fever emergence and control in Romania

A multi-host mechanistic model of African swine fever emergence and control in Romania

The utility of whole-genome sequencing to identify likely transmission pairs for pathogens with slow and variable evolution

Genome-wide phylodynamic approach reveals the epidemic dynamics of the main Mycoplasma bovis subtype circulating in France

Contact Info

Product

Resources

About