Genomic sequence data of viruses can greatly improve our understanding of viral spread within and between populations. These data provide insights into transmission links between humans or animals, which are undetectable by epidemiological data. By integrating genetic, epidemiological and immunological data, we can study the processes shaping phylogenetic trees (Grenfell et al. 2004). This upcoming field, called phylodynamics, has proven useful in understanding outbreaks of, for instance, Covid-19. In PROVED, these models will enhance our knowledge of two viruses in swine.
Your job Phylodynamic studies can aid control of infectious diseases in animals, which is crucial to improve animal health and welfare and human health in case of zoonoses. However, phylodynamic models are not yet frequently applied to viruses in animal populations (Guinat et al. 2021), even though animal populations are interesting to study in light of contact structures that are incomparable to human populations.
We have a unique genomic dataset of two viruses in swine. Swine Influenza A virus (SIV) and Porcine Reproductive and Respiratory Syndrome virus (PRRSv) are significant causes of respiratory disease in swine and have been circulating in swine herds for decades, even though vaccines are available for both pathogens. Control of these viruses is hampered by extensive genetic diversity and continuous evolution by mutations, reassortment and recombination. By tracking the evolution of SIV and PRRSv within individual pigs, farms, and regions, and connecting this to vaccination status and epidemiological parameters, this project will provide novel means to decipher the transmission dynamics of the viruses in swine populations. The results of this research will contribute to the development and application of phylodynamic models in animal populations and to the control of respiratory viruses in swine herds. The findings will ultimately contribute to protecting animal and human health.
As PhD candidate in this project, you will use existing genomic data of SIV and PRRSv, movement data of pigs, and farm characteristics and locations, to model transmission of the viruses across countries, between farms, and within farms. Moreover, you will gather information about current vaccination practices applied by farmers, and evaluate the impact of vaccination protocols and other management factors on the evolution and dynamics of the viruses in farms. You will work in close partnership with
Wageningen Bioveterinary Research for access to genomic data and expertise in virology, and with
Royal GD for surveillance data from affected swine farms. Throughout the project, you will develop core skills in epidemiology and phylodynamics, and gain familiarity with virus genomics and animal infectious diseases.