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Advancing Early Warning Systems for Malaria: Progress, Challenges, and Future Directions - A Scoping Review

Article scientifique 2024 Anglais

Résumé

ABSTRACT Background Malaria Early Warning Systems(EWS) are predictive tools that often use climatic and environmental variables to forecast malaria risk and trigger timely interventions. Despite their potential benefits, the development and implementation of malaria EWS face significant challenges and limitations. We reviewed the current evidence on malaria EWS, including their settings, methods, performance, actions, and evaluation. Methods We conducted a comprehensive literature search using keywords related to EWS and malaria in various databases and registers. We included primary research and programmatic reports focused on developing and implementing Malaria EWS. We extracted and synthesized data on the characteristics, outcomes, and experiences of Malaria EWS. Results After reviewing 5,535 records, we identified 30 studies from 16 countries that met our inclusion criteria. The studies varied in their transmission settings, from pre-elimination to high burden, and their purposes, ranging from outbreak detection to resource allocation. The studies employed various statistical and machine-learning models to forecast malaria cases, often incorporating environmental covariates such as rainfall and temperature. The most common mode used is the time series model. The performance of the models was assessed using measures such as the Akaike Information Criterion( AIC), Root Mean Square Error (RMSE), and adjusted R squared(R 2 ). The studies reported actions and responses triggered by EWS predictions, such as vector control, case management, and health education. The lack of standardized criteria and methodologies limited the evaluation of EWS impact. Conclusions This review provides a comprehensive overview of the current status of Malaria EWS, highlighting the progress, challenges, and gaps in the field. The review informs and guides policymakers, researchers, and practitioners in enhancing EWS and malaria control strategies. The review also underscores the need for further research on the integration, sustainability, and evaluation of Malaria EWS usage and harmonized methods to ease review.

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Mategula, D., Gichuki, J., Barnes, K. I., Giorgi, E., & Terlouw, D. J. (2024). Advancing Early Warning Systems for Malaria: Progress, Challenges, and Future Directions - A Scoping Review. medRxiv. https://doi.org/10.1101/2024.09.03.24313035

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