Mise en place d’un système d’information géographique pour la détection précoce et la prédiction des épidémies de paludisme à Madagascar

Abstract : We describe a Malaria Early Warning System (MEWS) using various epidemic thresholds and a forecasting component with the support of recent technologies to improve the performance of a sentinel MEWS. Malaria-related data from sentinel sites collected by Short Message Service are automatically stored in a database hosted on a server at Institut Pasteur de Madagascar. Concomitantly our system routinely and automatically acquires site specific satellite weather data related to changes in malaria prevalence such as temperature, rainfall and Normalized Difference Vegetation Index (NDVI). A Malaria Control Intervention data base has also been. This system has already demonstrated its ability to detect a malaria outbreak in southeastern part of Madagascar in 2014. In a second time, we conducted a study to assess the relationship between the effectiveness of mass campaign of long-lasting insecticidal nets (LLIN) over time and malaria outbreaks identified in Madagascar from 2009 to 2015 through the Sentinel surveillance system. This study showed that the difference between efficacy and effectiveness may result in gaps in service coverage during the subsequent years contributing to malaria rebound well before the replacement of the LLINs and highlights the need of continuous distribution mechanism of LLINs.This work aims to maximize the usefulness of a sentinel surveillance system to predict and detect epidemics in limited-resource environments, to guide any changes in the orientation of malaria control programs and to provide practical examples and suggestions for use in other systems or settings.
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Florian Girond. Mise en place d’un système d’information géographique pour la détection précoce et la prédiction des épidémies de paludisme à Madagascar. Géographie. Université de la Réunion, 2017. Français. ⟨NNT : 2017LARE0012⟩. ⟨tel-01666234⟩

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