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Thesis

Use of kernel embeddings in the context of spatial disease mapping

Abstract:

Over the last 20 years, high resolution mapping of estimated disease risk has become an important tool for disease control, facilitating the efficient allocation of limited resources. Maps of malaria risk, in particular, are widely used for operational planning and informing public health policy. Contemporary maps are typically made using Bayesian geostatistical models, informed by prevalence information from national health surveys and remote-sensed environmental and socioeconomic covaria...

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Division:
MSD
Department:
NDM
Sub department:
Structural Biology
Role:
Author

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Supervisor
Role:
Supervisor
Role:
Supervisor
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Name:
Engineering and Physical Sciences Research Council
Funder identifier:
http://dx.doi.org/10.13039/501100000266
Grant:
EP/G03706X/1
Programme:
Systems Biology studentship award
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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