Call Selected: FP7-ENV-2009-1 (ENV.2009.1.2.1.2)
Sub-Scheme Selected: CP-FP-SICA. Small or medium-scale focused research project.
Proposal ID: 243964
Coordinator: Andrew Morse
Nota de prensa UC (Spanish)
QWeCI statistical downscaling portal [login]
One of the most dramatic and immediate impacts of climate variation is that on disease, especially the vector-borne diseases that disproportionally affect the poorest people in Africa. Although we can clearly see that, for example, an El Nino event triggers Rift Valley Fever epidemics, we remain poor at understanding why particular areas are vulnerable and how this will change in coming decades, since climate change is likely to cause entirely new global disease distributions. This applies to most vector borne disease. At the same time, we do not know currently the limit of predictability of the specific climate drivers for vector-borne disease using state-of-the-art seasonal forecast models, and how best to use these to produce skilful infection-rate predictions on seasonal timescales.
The QWeCI project thus aims to understand at a more fundamental level the climate drivers of the vector-borne diseases of malaria, Rift Valley Fever, and certain tick-borne diseases, which all have major human and livestock health and economic implications in Africa, in order to assist with their short-term management and make projections of their future likely impacts. QWeCI will develop and test the methods and technology required for an integrated decision support framework for health impacts of climate and weather. Uniquely, QWeCl will bring together the best in world integrated weather/climate forecasting systems with heath impacts modelling and climate change research groups in order to build an end-to-end seamless integration of climate and weather information for the quantification and prediction of climate and weather on health impacts in Africa.
Contribution of the Santander Meteorology Group:
Our group coordinates WP3.1 Downscaled and calibrated seamless seasonal atmospheric forecasts and contributes to WP1.2: Atmospheric database, WP1.3: Climate-desease associations, and WP5.1: Integrated decision support systems.
People involved in the project (attendants to the KoM):
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