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Thesis

The utility of merging mechanistic and geospatial models for malaria intervention planning and policy guidance

Abstract:

This thesis describes the development and refinement of two frameworks for usefully combining mechanistic and geospatial models in malaria research. The first framework, focused on malaria transmission, uses machine learning tools and spatial data to identify key features for a mechanistic transmission model, then utilizes spatial data again to place mechanistic model results in a global context. This strategy is novel, flexible, customizable, and computationally efficient. The second, focuse...

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Division:
MSD
Department:
NDM
Role:
Author

Contributors

Role:
Supervisor, Contributor
Role:
Contributor
Role:
Supervisor
ORCID:
0000-0001-5962-4238
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
Language:
English
Keywords:
Subjects:
Deposit date:
2021-11-19

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