The Syndromic Surveillance R&D project led by Critical Software aims to collect structured clinical data on isolated populations in developing countries using mobile devices and relate it with geo-location and earth observation data. Through the analysis of correlated data and applying methods of business intelligence, the solution will allow detecting, monitoring, predicting outbreaks and epidemics and acting to minimize the consequences of infectious diseases such as Malaria and HIV/AIDS.
Fraunhofer AICOS will collaborate in this R&D project by providing its PostboxWeb framework to collect data in locations where there is no network coverage and transmit them whenever network is available. Fraunhofer AICOS will contribute with the technical and scientific knowledge in its areas of expertise, namely: information and communication technologies for development; mobile solutions; and interface design in human–computer interaction. In the course of the project, mobile applications prototypes will be developed together with a set of front-ends which will have an innovative interface aiming at the massive use of a channel for health records screening, and also featuring the automatic inference of the geographic locations where the clinical information is gathered. In addition, presentation layers will be built for operational monitoring of care plans and presentation of individual clinical records.
Syndromic Surveillance also aims the development of an interoperable health care monitoring system prototype to allow the surveillance of the infectious diseases, generating estimates of the HIV and Malaria epidemic in a given a country, while assuring the interoperability with external health information systems. This translates into a Health Management module prototype that must be able to receive relevant health information for HIV and Malaria surveillance, which will be transmitted by the PostboxWeb. The Health Management will interact with Electronic Health Records and must be able to process the received data generating statistical metrics to ensure accountability, as well as to monitor the population response to specific therapeutic or preventive programs in demarked regions.