Integration of epidemiological and genetic data to reconstruct disease outbreaks in host-viral systems. (360G-Wellcome-102427_Z_13_Z)
The recent history of a virus epidemic can be more accurately reconstructed when genetic and epidemiological data are integrated, compared to focusing on either data type alone. However, current reconstructive approaches are limited, being designed for outbreaks where most cases are identified. We lack a framework capable of powerful inference when more detailed epidemiological and viral genetic data are available, but when a smaller proportion of cases is sampled. I intend to resolve this by developing general Bayesian statistical methods and applying them to host-virus systems for which both viral genetic and host behavioural data are available: hepatitis C virus (HCV) in humans, and influenza in wild birds.Accessing data obtained from collaborators from four cohorts of HCV patients, I will apply improved methods to determine factors associated with increased risk of transmitting HCV. In tandem, I will study longitudinal viral genetic diversity in a resident mute swan colony (Abbotsbury, Dorset). This will test hypotheses that influenza dynamics in long-lived birds are unlike that in the short-lived species on which almost all research focuses. Combining epidemiological and genetic sequence data will increase understanding of the dynamic behaviour of these viruses, which can be translated to improving control and surveillance measures.
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Grant Details
Amount Awarded | 160309 |
Applicant Surname | Hill |
Approval Committee | PhD Studentships |
Award Date | 2013-06-24T00:00:00+00:00 |
Financial Year | 2012/13 |
Grant Programme: Title | PhD Studentship (Basic) |
Internal ID | 102427/Z/13/Z |
Lead Applicant | Dr Sarah Hill |
Partnership Value | 160309 |
Planned Dates: End Date | 2018-01-12T00:00:00+00:00 |
Planned Dates: Start Date | 2013-10-01T00:00:00+00:00 |
Recipient Org: Country | United Kingdom |
Region | South East |
Sponsor(s) | Prof Jonathan Flint |