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Welcome to FluDetWeb, a web-based implementation of a prospective influenza surveillance methodology for the early detection of the onset of influenza epidemics. The underlying statistical methodology is described in Martínez-Beneito et al. (Bayesian Markov switching models for the early detection of influenza epidemics, Statistics in Medicine, 27(22), 4455-4468).

After registering, users can introduce and edit their own data consisting of a series of weekly influenza incidence rates and ask the system about the probability of being in an epidemic phase, taking into account that historical data series must last at least three years. The system returns (via e-mail if desired), together with the probability of an increase of the incidence rate in the following week. It also provides two graphs: one with the weekly rates of the last two seasons indicating if the posterior probability of being in an epidemic phase in the analyzed week is greater or not than 0.5, and another with the weekly rates of all the seasons indicating only in those previously calculated which weeks have a posterior probability of being in an epidemic phase greater than 0.5 or not.

The implementation of this system has been done using statistical free-software (R and WinBUGS), a web server environment for Java code (TOMCAT) and a database server software package (MySQL). This surveillance system has been created by members of the Geeitema Research group in the context of the MEVIEPI project. More details about the architecture of the system and about how it works can be found here. For any other questions or requests, please contact with