%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Girond, F.
%A Randrianasolo, L.
%A Randriamampionona, L.
%A Rakotomanana, F.
%A Randrianarivelojosia, M.
%A Ratsitorahina, M.
%A Brou, T. Y.
%A Herbreteau, Vincent
%A Mangeas, Morgan
%A Zigiumugabe, S.
%A Hedje, J.
%A Rogier, C.
%A Piola, P.
%T Analysing trends and forecasting malaria epidemics in Madagascar using a sentinel surveillance network : a web-based application
%D 2017
%L fdi:010069275
%G ENG
%J Malaria Journal
%@ 1475-2875
%K MADAGASCAR
%M ISI:000394189100001
%P art. 72 [11 ]
%R 10.1186/s12936-017-1728-9
%U https://www.documentation.ird.fr/hor/fdi:010069275
%> https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers17-03/010069275.pdf
%V 16
%W Horizon (IRD)
%X 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.
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