Malaria-VisAnalytics: A Tool for Visual Exploratory Analysis of Brazilian Public Malaria Data

Abstract Background: Data integration and visualization techniques have been widely used in scientific research to allow the exploitation of large volumes of data and support highly complex or long-lasting research questions. Integration allows data from different sources to be aggregated into a single database comprising variables of interest for different types of studies. Visualization allows large and complex data sets to be manipulated and interpreted in a more intuitive way.Methods: In this paper, we present how integration and visualization techniques were applied in a malaria surveillance ecosystem to build an integrated database comprising notifications, deaths, vector control andclimate data. This database is accessed through Malaria-VisAnalytics, a visual mining platform for descriptive and predictive analytics supporting decision and policy making by governmental and health agents.Results: Our experimental and validation results so far have proved that the visual exploration and interaction mechanisms allow effective surveillance for rapid action in suspected outbreaks, as well support a set of different research questions over integrated malaria electronic health records.Conclusion: At last, it can be easily extended with new functionalities and data sources to accommodate more complex scenarios.