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Title: The spatial ecology of host parasite communities
Author: Keegan, Shaun
ISNI:       0000 0004 9352 1082
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2020
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Tobler's First Law of Geography states that 'everything is related to everything else, but near things are more related than distant things'. In the context of infectious diseases this implies that there are likely to be further cases of these infections spatially closer to an infected host than spatially further away. This is a simplistic interpretation that fails to consider the transmission biology of parasites. I investigated whether a function of spatial clustering, the K function, differed from the host and between parasites of a range of taxa and transmission modes in the wild wood mouse. Using the studentized permutation test, I found that there is a significant difference between a close contact transmitted virus, Wood Mouse Herpes Virus (WMHV), and the host and a number of parasite species. This is consistent with prior studies of close contact transmitted viruses in wood mice, suggesting there is a link between spatial clustering and close contact transmission. Interactions among coinfecting parasites are typically examined at the within-host level, often revealing strong effects on individual host susceptibility or disease progression. However the effect of these interactions on parasite transmission between hosts, and the spatial scales over which those effects operate, has remained unknown. I analyse a spatially explicit dataset of the diverse community of parasites infecting wild wood mice, to assess the effects of local neighbourhood prevalence of each parasite species on individual-level infection risk by the other species, over an increasing range of spatial scales. This revealed that the effects of within-host interactions between coinfecting parasites can indeed ripple out beyond the individual host, resulting in a network of facilitatory and suppressive effects on transmission among these parasites. However these between-host effects were only seen over relatively restricted distances around each host, over spatial scales likely reflecting the spatial scale of transmission. Classical models of infectious diseases generally assume random mixing of individuals in a population. In these models each individual is as likely to encounter every other individual equally. Ignoring heterogeneities in contacts between individuals can overlook a significant element of the transmission biology of the parasite. Recently, studies focusing on how social networks relate to the spread of infection have increased in number dramatically. I explore how two measures of an individual's place in a social network, eigenvector centrality and degree, affect the disease status of individuals, using a very different study system to the wood mouse, the African buffalo. I find that for some parasites, eigenvector centrality affects disease status but that for all parasites degree has no effect. I then adapt the neighbourhood analysis technique to investigate potential novel parasite-parasite interactions, detecting one previously unknown. Spatial scale is the theme binding each of the studies in this thesis - from scale of clustering, to scale of coinfection interactions. Using pre-existing and bespoke techniques, I have explored 2 very different host-parasite communities to tackle these issues, concluding that spatial scale is an important consideration in understanding parasite biology.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral