Understanding the Impact of Climate Change on Infectious Disease Dynamics
The effects of climate change on human health have attracted increasing attention in recent years and it is widely expected to significantly affect the global spread, intensity and distribution of infectious diseases. Linking global and regional climate models with mathematical (and statistical) models of disease transmission provides a valuable tool towards improving and quantifying our understanding of how future changes in environmental drivers may affect disease dynamics.
My research aims to develop conceptual frameworks for modelling, analysing and evaluating the potential impact of global change on disease transmission. Of considerable interest is the question of whether changes in climatic variables may be reliably used to predict the spatiotemporal incidence of diseases such as malaria, dengue and schistosomiasis. Thus, as well as evaluating the long-term prospects for disease, this programme also aims to assess the use of seasonal climate data to develop early-warning systems using methods such as data assimilation used in weather and climate forecasting.
In addition, understanding, quantifying and improving our knowledge regarding key uncertainties in disease transmission, climate modelling and the interaction between the two is vital if we are to better understand the challenges that lie ahead and the implications for mitigation, adaptation and control.
Other research interests within mathematical biology and infectious disease modelling include chaotic behaviour in biological systems, quantifying uncertainty and risk, approximating stochastic models, complexity in dynamical systems, network/graph theory and understanding the effects of seasonality, stochasticity and nonlinearity on the static and dynamical properties of biological systems.
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