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Study Completed: 2013
College of Sciences
Non-Parametric Estimation of Geographical Relative Risk Functions
Ms Fernando’s research focussed on the development of advanced statistical methods for modelling spatial and spatio-temporal variation in disease risk in both human and animal populations. These methods provide tools that help locate significant disease clusters in space and/or time, and hence provide the foundations for better disease control. The research also resulted in methods for quantifying the rate at which the risk posed by a disease changes over time. She developed techniques for visualizing how the spatial pattern of risk varies with other predictors of disease (for example, whether the geographical distribution of an infectious disease differs according to the attributes of the host or the strain of the pathogen). The methods that she developed can be integrated into disease surveillance systems, and thus contribute to better early warning systems for disease outbreaks.
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Last updated on Tuesday 04 April 2017