Arguably one of the most important effects of climate change is the likely impact on human health. While this may take many forms, the implications for vector-borne diseases are both potentially significant and highly uncertain. Our research aims to establish tools to help map vectors and/or disease transmission, calculate risk, and plan control strategies under a changing climate, a process that is of great importance for tackling both established and emerging diseases. This is a rapidly emerging multi-disciplinary field and translating this research into outputs for use by stakeholders in planning and improving vector and disease control strategies for pathogens that infect millions of people worldwide is vital.
Improvements in vector-borne disease control strategies will have a direct impact on human populations through reducing the burden of established vector-borne diseases or preventing future outbreaks in vulnerable populations. In addition, while climate and climate change are extremely likely to influence the future transmission and range of vector-borne diseases, the magnitude of the effect is likely to vary between diseases. It should be recognised that a multitude of other epidemiological, ecological and socioeconomic factors are also likely to affect disease transmission. Nevertheless, quantifying the role of climate change in future vector-borne disease trends compared to other known drivers represents an important goal.
An important development in recent years in climate modelling has been the development of multi-model ensembles to make projections about future climate scenarios. Such multi-model approaches in climate modelling are almost always found to be superior to the single ‘best’ model in a given ensemble, and these form the basis of the Intergovernmental Panel for Climate Change’s AR4 and AR5 projections. By analogy, our research is currently working towards developing and validating an ensemble of appropriately-weighted climate-driven vector-borne disease models as a means of better understanding the role of climatic and environmental variables on transmission, as well as the impact of climate variability and change on interventions in different settings. In addition to uncertainties in climate modelling and factors surrounding future climate scenarios, considerable uncertainties exist within non-climatic factors known to affect local vector-borne disease transmission. These uncertainties mean it is difficult to develop realistic projections about future transmission patterns and the likely impact of intervention programmes.
Our research seeks to understand how this array of uncertainties in disease epidemiology, vector ecology, parasite biology, and climate modelling, as well as the causal links between these biological, environmental and climatological systems, may be accounted for within multi-model approaches based on a ‘collective consensus’ across a suite of viable models. We are also assessing the cost effectiveness of different intervention measures. This forms a vital component of future public health policy planning.
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