Many pathogens of global health and conservation concern infect multiple host species. Ebola is a classic example, circulating naturally within a 'reservoir' host community, and with the potential to jump across to another host species with devastating effect. Clearly it is vital to understand how such pathogens are maintained in their host communities, and which species play a major role in spreading those pathogens. However, obtaining that understanding is notoriously hard. We have recently developed a mathematical approach to measure a host community's ability to maintain a pathogen, and identify 'key hosts' that drive pathogen spread. Importantly, unlike previous methods, this approach can be parameterised using relatively coarse-grained, easily-collected data (standard measures of host abundance and infection occurrence). We will provide the first rigorous test of this model, applying it to a natural 'multihost'-pathogen system of major conservation concern: chytrid fungus ('Bd') in amphibian communities. Bd is a major cause of amphibian declines worldwide, but we don't understand how it spreads through or is maintained by amphibian communities. We will apply our mathematical approach to historical and new data, and use it to identify those key hosts, and predict the effect of removing them. Crucially, we will then directly test those predictions by carrying out species removal experiments. Overall this will provide a rigorous test of our mathematical tool, show how host communities affect pathogen spread in general, and provide specific guidelines for the management of Bd in particular.
Many pathogens of global health and conservation concern infect multiple host species. Ebola is a classic example, circulating naturally within a 'reservoir' host community, and with the potential to jump across to another host species with devastating effect. Clearly it is vital to understand how such pathogens are maintained in their host communities, and which species play a major role in spreading those pathogens. However, obtaining that understanding is notoriously hard. We have recently developed a mathematical approach to measure a host community's ability to maintain a pathogen, and identify 'key hosts' that drive pathogen spread. Importantly, unlike previous methods, this approach can be parameterised using relatively coarse-grained, easily-collected data (standard measures of host abundance and infection occurrence). We will provide the first rigorous test of this model, applying it to a natural 'multihost'-pathogen system of major conservation concern: chytrid fungus ('Bd') in amphibian communities. Bd is a major cause of amphibian declines worldwide, but we don't understand how it spreads through or is maintained by amphibian communities. We will apply our mathematical approach to historical and new data, and use it to identify those key hosts, and predict the effect of removing them. Crucially, we will then directly test those predictions by carrying out species removal experiments. Overall this will provide a rigorous test of our mathematical tool, show how host communities affect pathogen spread in general, and provide specific guidelines for the management of Bd in particular.

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| Provider | Academic Bibliometrics & Assessment Computational Utility Service |
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| Provider | Academic Bibliometrics & Assessment Computational Utility Service |
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| Provider | Academic Bibliometrics & Assessment Computational Utility Service |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
| Provider | Academic Bibliometrics & Assessment Computational Utility Service |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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| Description | Stores the user session ID for Academic Bibliometrics & Assessment Computational Utility Service. |
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