Girond F. auteur aut IRD Randrianasolo L. auteur aut IRD Randriamampionona L. auteur aut IRD Rakotomanana F. auteur aut IRD Randrianarivelojosia M. auteur aut IRD Ratsitorahina M. auteur aut IRD Brou T. Y. auteur aut IRD Herbreteau Vincent auteur aut IRD Mangeas Morgan auteur aut IRD Zigiumugabe S. auteur aut IRD Hedje J. auteur aut IRD Rogier C. auteur aut IRD Piola P. auteur aut IRD text journalArticle eng text/pdf reformatted digital access Background : The use of a malaria early warning system (MEWS) to trigger prompt public health interventions is a key step in adding value to the epidemiological data routinely collected by sentinel surveillance systems. Methods : This study describes a system using various epidemic thresholds and a forecasting component with the support of new technologies to improve the performance of a sentinel MEWS. Malaria-related data from 21 sentinel sites collected by Short Message Service are automatically analysed to detect malaria trends and malaria outbreak alerts with automated feedback reports. Results : Roll Back Malaria partners can, through a user-friendly web-based tool, visualize potential outbreaks and generate a forecasting model. The system already demonstrated its ability to detect malaria outbreaks in Madagascar in 2014. Conclusion : This approach aims to maximize the usefulness of a sentinel surveillance system to predict and detect epidemics in limited-resource environments. specialized MADAGASCAR 052 050 128 16 art. 72 [11 p.] 2017 1475-2875 https://www.documentation.ird.fr/hor/fdi:010069275 10.1186/s12936-017-1728-9 1475-2875 [F B010069275] https://www.documentation.ird.fr/hor/fdi:010069275 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers17-03/010069275.pdf IRD - Base Horizon / Pleins textes 2017-04-04 2023-07-11 fdi:010069275 fre