PhD: Hydro-dynamic modelling of malaria environmental suitability

 (via FindaPhD)
University of Leeds
Leeds, United Kingdom
Position Type: 
Organization Type: 
University/Academia/Research/Think tank
Experience Level: 
Not Specified


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About the Project

Also supervised by Dr Tom Willis (Leeds) and Prof Chris Thomas (Lincoln)

Malaria is a climate sensitive vector-borne disease that was responsible for an estimated 445,000 deaths from 216 million malaria cases worldwide in 2016; 91% of these malaria deaths were in Africa (WHO, 2017). Detailed mapping of current malaria transmission is vital for distribution of health resources and targeting of control measures. Moreover, an understanding of environmental conditions required for malaria transmission is necessary for predicting areas subject to future outbreaks. Future climate change is likely to alter the distribution and intensity of malaria transmission, though the exact nature and extent of this influence has been the subject of recent debate (Caminade et al., 2014).

The availability of water suitable for mosquito breeding is a critical control on malaria transmission, particularly where predominant mosquito vectors are adapted to exploit new water arising from seasonal rains and flooding. Such understanding is crucial if we are to make the link to climate and estimate the impact of projected climate change. Moreover, this knowledge can contribute to malaria adaptation/mitigation, namely the identification of mosquito larval ‘hotspots’ that could be targeted in malaria control programmes.

Ambient air temperature controls the rate of several components of the malaria transmission cycle including sporogonic and gonotrophic development rates, biting rate and individual longevity. Malaria climatic suitability is thus modelled based on well-established thermal response curves (e.g. Mordecai et al., 2012); however, water body availability is afforded no such detailed treatment. Instead, simple rainfall thresholds are used to represent water availability (see the review in Smith et al., 2013). Current research by the project team is coupling a continental-scale hydrological model with malaria thermal response curves to provide a more physically-based estimate of malaria hydro-climatic suitability.

Meanwhile, at the landscape scale, previous and ongoing work is focused on establishing a greater understanding of the hydrological and geomorphological impact of habitat suitability at the landscape scale (e.g. Hardy et al., 2013). This includes linking detailed hydraulic models with agent-based mosquito spatial ecology modelling to identify larval hotspots and model the dynamics with the passing of annual flood waves at high resolution.

The major aim of this project will be to bridge the scale gap between continental-scale and landscape-scale efforts of modelling malaria hydro-climatic suitability. The daily runoff output of global scale hydrological models can be used to drive global hydro-dynamic river routing models (e.g. CaMa-Flood; Yamakazi et al., 2011; Trigg et al., 2016) capable of representing flood expansion and contraction across Africa at spatial scales below 1 km. Such a development will allow for vector niches to be represented explicitly in a continental-scale model.

In this project, you will work with a team of scientists at the University of Leeds, the University of Lincoln and a network of international collaborators to embed hydrological and geomorphological understanding into continental-scale models of malaria hydro-climatic suitability. In particular, according to their research interests, the successful student could:

Input daily runoff data into global hydro-dynamic river routing models to then evaluate hydro-climatic suitability for malaria across Africa both for the present day and up until 2100;

Expand this modelling approach to cover each continent and evaluate potential changes in hydro-climatic malaria suitability;

Compare predictions of the above for different emissions pathways;

Evaluate the global hydro-dynamic modelling output with more detailed modelling of individual field sites (particularly the Barotse floodplain of the Zambezi) along with potentially collecting ground truth data sets.

This builds on our recent research published in Nature Communications (Smith et al., 2020).

Funding Notes

We offer 3.5 years fully funded studentships including full tuition fees for all successful applicants, and stipend at the UKRI rate plus a training grant