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Rabies persists via metapopulation dynamics. PhD will develop metapopulation models using epidemiological & genetic data to inform rabies elimination

Metapopulations & infectious disease dynamics – modelling rabies using epidemiological and genomic data
SUMMARY: Rabies kills thousands of people around the world every year, but a global target has now been set to eliminate human deaths from dog-mediated rabies by 2030 and large-scale mass dog vaccination programmes are being undertaken working towards this aim. Extensive epidemiological and genomic data on rabies viruses have generated valuable insights into their diversity, emergence and spread. The persistence of endemic rabies is hypothesized to occur as a result of metapopulation processes, with frequent introductions and extinctions, as well as co-circulation of viral lineages observed across a range of settings. Building on this background, this PhD will draw from detailed epidemiological and genetic data to parameterize metapopulation models of endemic rabies. These models will be used to understand the varied dynamics of rabies across heterogeneous landscapes including island populations, dense urban conurbations and sparse rural communities. Specifically, models will be applied to explicit landscapes and used to generate and test hypotheses with epidemiological and genomic data. The project aims to deliver fundamental insights into the persistence of infectious diseases and to provide recommendations for tailoring surveillance and managing national and regional rabies elimination programmes.

Background: Metapopulations are a fundamental concept in ecology whereby colonization and extinctions underpin the persistence of populations across landscapes [1]. Metapopulation dynamics have important applications in conservation and in the control and elimination of infectious diseases. Genetic and epidemiological data from the SARS-CoV-2 pandemic perfectly illustrate this theory with the emergence of viral lineages and their frequent introductions and extinctions within interconnected populations around the world. Metapopulation dynamics have been hypothesized to underlie the endemic dynamics of canine rabies, with co-circulation of viral lineages and frequent reintroductions observed in a range of settings [2,3]. We have shown how foci of rabies infection arise from individual variation in transmission and dispersal and how resulting lineages have characteristic patterns of persistence. Evidence from regional rabies elimination programmes also illustrate how metapopulation dynamics contribute to persistence and have implications for coordinated management [4].

Aims:
• To parameterize a metapopulation model of rabies dynamics using individual level data on transmission and dispersal and genomic data on viral lineage diversity
• Apply this model across spatially heterogeneous landscapes to explore patterns of viral circulation.
• Compare model outcomes with genomic data from around the world using RABV-GLUE, a platform for curation of viral sequences and metadata.
• Refine model to spatially explicit landscapes in order to investigate the optimal deployment of control efforts for elimination at national and regional scales.
• Examine how surveillance biases affect inference of disease dynamics and specifically how surveillance should be enhanced to improve disease elimination programmes.

Training outcomes:
● Development and parameterization of mathematical models and experience in application of a range of modelling frameworks from individual-based to metapopulation models.
● Computational and statistical competence for undertaking computer simulations and statistical inference
● Understanding of viral sequencing methods and phylodynamics, with skills gained in the integration and synthesis of genomic and epidemiological data
● Understanding of routine and enhanced surveillance as part of national and regional rabies control programmes including viral sequencing
● Effective communication and data visualization skills for conveying information from mathematical models and genetic and epidemiological data and to inform other scientists, policy makers, practitioners and the general public

References:
[1] Hanski I. Metapopulation dynamics. Nature 1998;396:41–9. https://doi.org/10.1038/23876.
[2] Brunker K, Marston DA, Horton DL, Cleaveland S, Fooks AR, Kazwala R, et al. Elucidating the phylodynamics of endemic rabies virus in eastern Africa using whole-genome sequencing. Virus Evol 2015;1:vev011. https://doi.org/10.1093/ve/vev011.
[3] Bourhy H, Nakouné E, Hall M, Nouvellet P, Lepelletier A, Talbi C, et al. Revealing the Micro-scale Signature of Endemic Zoonotic Disease Transmission in an African Urban Setting. PLOS Pathog 2016;12:e1005525.
[4] Rysava K, Mancero T, Caldas E, de Carvalho MF, Castro APB, Gutiérrez V, et al. Towards the elimination of dog-mediated rabies: development and application of an evidence-based management tool. BMC Infect Dis 2020;20:778. https://doi.org/10.1186/s12879-020-05457-x.

Type
PhD position
Institution
University of Glasgow
City
Glasgow
Country
United Kingdom
Closing date
January 25th, 2021
Posted on
December 9th, 2020 16:06
Last updated
December 9th, 2020 16:07
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