Identification
Author | Jones AE, Morse AP |
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Title | Application and validation of a seasonal ensemble prediction system using a dynamic Malaria model |
Year | 2010 |
Publication type | Article |
Journal | Journal of Climate |
Created | 2014-08-04 19:01:16+00:00 |
Modified | 2016-07-29 20:21:03.976327+00:00 |
Details
Volume | 23 |
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Access
Language | English |
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URL | http://journals.ametsoc.org/doi/abs/10.1175/2010JCLI3208.1 |
DOI | 10.1175/2010JCLI3208.1 |
Accessed | 2016-07-13 |
Extended information
Abstract | Seasonal multimodel forecasts from the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) project are used to drive a malaria model and create reforecasts of malaria incidence for Botswana, in southern Africa, in a unique integration of a fully dynamic, process-based malaria model with an ensemble forecasting system. The forecasts are verified against a 20-yr malaria index and compared against reference simulations obtained by driving the malaria model with data from the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40). Performance assessment reveals skill in the DEMETER-driven malaria forecasts for prediction of low (below the lower tercile), above-average (above the median), and high (above the upper tercile) malaria events, with the best results obtained for low malaria events [relative operating characteristics (ROC) area = 0.84, 95% confidence interval = 0.63–1.0]. For high malaria events, the DEMETER-driven malaria forecasts are skillful, but the forecasting system performs poorly for those years that it predicts the highest probabilities of a high malaria event. Potential economic value analysis demonstrates the potential value for the DEMETER-driven malaria forecasts over a wide range of user cost-loss ratios, which is primarily due to the ability of the system to save on the cost of action in low malaria years. |
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Links
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