ArticleMalaria journal2022
Malaria-VisAnalytics: a tool for visual exploratory analysis of Brazilian public malaria data.
Article in Malaria journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Analysis of inpatient data on dengue fever, malaria and leishmaniasis in Ecuador: A cross-sectional national study, 2015-2022.New microbes and new infectionsArticle
- Postmalaria elimination: Overview of recurrent malaria cases in Riau Province, Indonesia.Tropical parasitologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundData integration and visualisation 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. Visualisation allows large and complex data sets to be manipulated and interpreted in a more intuitive way.
methodsIntegration and visualisation techniques were applied in a malaria surveillance ecosystem to build an integrated database comprising notifications, deaths, vector control and climate data. This database is accessed through Malaria-VisAnalytics, a visual mining platform for descriptive and predictive analysis supporting decision and policy-making by governmental and health agents.
resultsExperimental and validation results have proved that the visual exploration and interaction mechanisms allow effective surveillance for rapid action in suspected outbreaks, as well as support a set of different research questions over integrated malaria electronic health records.
conclusionThe integrated database and the visual mining platform (Malaria-VisAnalytics) allow different types of users to explore malaria-related data in a user-friendly interface. Summary data and key insights can be obtained through different techniques and dimensions. The case study on Manaus can serve as a reference for future replication in other municipalities. Finally, both the database and the visual mining platform can be extended with new data sources and functionalities to accommodate more complex scenarios (such as real-time data capture and analysis).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.