Accès ouvert

Analysing trends and forecasting malaria epidemics in Madagascar using a sentinel surveillance network: a web-based application

Article scientifique 2017 Anglais

Résumé

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.

Citer ce document

Girond, F., Randrianasolo, L., Randriamampionona, L., Rakotomanana, F., Randrianarivelojosia, M., Ratsitorahina, M., Herbreteau, V., Mangeas, M., Zigiumugabe, S., Hedje, J., Rogier, C., Piola, P. (2017). Analysing trends and forecasting malaria epidemics in Madagascar using a sentinel surveillance network: a web-based application. https://doi.org/10.1186/s12936-017-1728-9

Accès au document

Voir sur le dépôt source

Ce document est hébergé sur son dépôt institutionnel d'origine.

Auteur(s)

Florian Girond Laurence Randrianasolo Léa Randriamampionona Fanjasoa Rakotomanana Milijaona Randrianarivelojosia Maherisoa Ratsitorahina Vincent Herbreteau Morgan Mangeas Sixte Zigiumugabe Judith Hedje Christophe Rogier Patrice Piola

Statistiques

Consultations : 2

Téléchargements : 0