Identification

Author

Jones AE, Morse AP

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

Access

Language

English

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.