Metapopulations and infectious disease dynamics
Lead Research Organisation:
University of Glasgow
Department Name: College of Medical, Veterinary, Life Sci
Abstract
Studentship strategic priority area: Mathematical Biology
Keywords: Transmission, Lineages, Genomics, Inference, Statistics
Abstract:
Background: Metapopulations are a fundamental concept in ecology whereby colonization and extinctions underpin the persistence of populations across landscapes. 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. 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.
Aims of studentship:
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 rabies viral sequences and metadata.
Refine model to spatially explicit landscapes so as 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
Keywords: Transmission, Lineages, Genomics, Inference, Statistics
Abstract:
Background: Metapopulations are a fundamental concept in ecology whereby colonization and extinctions underpin the persistence of populations across landscapes. 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. 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.
Aims of studentship:
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 rabies viral sequences and metadata.
Refine model to spatially explicit landscapes so as 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
Organisations
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R513222/1 | 01/10/2018 | 30/09/2023 | |||
| 2587459 | Studentship | EP/R513222/1 | 01/04/2021 | 30/09/2024 | Rowan Durrant |
| EP/T517896/1 | 01/10/2020 | 30/09/2025 | |||
| 2587459 | Studentship | EP/T517896/1 | 01/04/2021 | 30/09/2024 | Rowan Durrant |