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Better target the disease at-risk groups and promptly link them to appropriate health services
Country: Belgium
Website: MediScout
Contact Person: Xavier Morelle & Emmanuel André


MediScout consists of a suite of software innovations used for planning, monitoring, and reporting of small and large-scale community-based disease control activities.

MediScout-enabled community interventions are managed from a web-based interface that allows organizations to build surveys (an example is disease door-to-door screening tools), organize human resources, and operationalize the fieldwork in a decentralized way. Through the mobile app, the community-based health workers are automatically notified of new assignments and can start performing the work within settings whose geocoordinates have been predefined by program managers.

MediScout further provides two data-driven autonomous analysis systems aiming to increase the impact of community-based health interventions. First, a disease-prediction tool that allows mapping of areas at high risk for a particular disease, based on the integration of demographic, environmental and health-related data. These predictions are useful in allocating adequate resources based on data-driven risk classification.

Second, the individuals screened using the electronic survey questionnaire administering tools can be scored automatically based on their responses to questions asked, and this prompts an individualized action which the community health worker can immediately execute.

Finally, MediScout ensures full traceability of community-based interventions, as all data and GPS locations are automatically captured, reported and mapped on the web-interface in real-time.

MediScout has been successfully evaluated in the context of the tuberculosis epidemic in the South-Kivu province of DRC. In this province, 50% of the patients suffering from the disease are untreated. Finding these groups and linking them to care is of utmost priority. MediScout was used by a local NGO to predict the exact location of communities with an uncontrolled burden of disease and to operationalize active case-finding in these communities. Over 15.000 people were screened in 20 remote communities. Laboratory results confirmed the performance of this approach, ultimately increasing by three-fold the efficiency of the community-based interventions performed by the organization. Further validation studies are ongoing in Rwanda and the Katanga province of DRC.



Level of development:

Marketed but with little documented field experience

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