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A Holistic Approach to Dynamic Modelling of Malaria Transmission. An Investigation of Climate-Based Models used for Predicting Malaria Transmission
Modu, Babagana
Modu, Babagana
Publication Date
2020
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The University of Bradford theses are licenced under a Creative Commons Licence.
Peer-Reviewed
Open Access status
Accepted for publication
Institution
University of Bradford
Department
Faculty of Engineering and Informatics
Awarded
2020
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Abstract
The uninterrupted spread of malaria, besides its seasonal uncertainty, is
due to the lack of suitable planning and intervention mechanisms and
tools. Several studies have been carried out to understand the factors
that affect the development and transmission of malaria, but these efforts
have been largely limited to piecemeal specific methods, hence they do
not offer comprehensive solutions to predict disease outbreaks. This thesis introduces a ’holistic’ approach to understand the relationship between
climate parameters and the occurrence of malaria using both mathematical and computational methods. In this respect, we develop new climate-based models using mathematical, agent-based and data-driven modelling
techniques. A malaria model is developed using mathematical modelling
to investigate the impact of temperature-dependent delays. Although this method is widely applicable, but it is limited to the study of homogeneous
populations. An agent-based technique is employed to address this limitation, where the spatial and temporal variability of agents involved in the transmission of malaria are taken into account. Moreover, whilst the mathematical and agent-based approaches allow for temperature and precipitation in the modelling process, they do not capture other dynamics that might potentially affect malaria. Hence, to accommodate the climatic predictors of malaria, an intelligent predictive model is developed using
machine-learning algorithms, which supports predictions of endemics in
certain geographical areas by monitoring the risk factors, e.g., temperature
and humidity. The thesis not only synthesises mathematical and computational methods to better understand the disease dynamics and its transmission, but also provides healthcare providers and policy makers with better planning and intervention tools.
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Type
Thesis
Qualification name
PhD