Malaria Data by District is a Shiny web application that allows users to generate summary statistics and visualise surfaces from the Malaria Atlas Project without the need to interact with the R coding language.
Malaria Data by District is a Shiny web application that allows the visualisation of data hosted by the Malaria Atlas Project.
The application allows selection of up to one country, all available districts within that country and up to four rasters for summary statistics generation and surface visualisation.
The application allows users to download a formatted R Markdown file for the generated statistics.
The 'Application' page is comprised of two main sections:
- 'Inputs' where the user select a single country, any number of districts within that country and up to four surfaces.
- 'Outputs' Where the rendered results appear under three tabs on the right-hand side of the application page.
Generate Statistic Button
When the generate statistics button is clicked, the application retrives summary statistics and raster layer visualisations for the selected input and renders them in the three output tabs on the right-hand side of the application
The application generates district-level summary statistics for a range of malaria indicators/malariometric data, as available by MAP. The aggregated district-level statistics enable the interpretation of disaggregated, high-spatial resolution trends (5 km x 5 km), at the administrative level.
The application allows user interaction and creates interactive visualizations such as maps displaying mean values for each district selected by the user.
Download Report Button TBC
Malaria Data by District has been developed using R and Shiny and is dependent on the following software and R packages:
| Software | |
| R | Language and environment for statistical computing and graphics |
| R packages | |
| shiny | Web Application Framework for R |
| RColorBrewer | ColorBrewer palettes |
| malariaAtlas | An R interface to open-access malaria data, hosted by the Malaria Atlas Project |
| shinydashboard | shinydashboard |
| stringr | stringr: Simple, Consistent Wrappers for Common String Operations |
| shinyalert | Display a popup message (modal) in Shiny |
| shinyBS | Adds additional Twitter Bootstrap components to Shinyshiny |
| shinythemes | Themes for Shinys |
| shinycssloaders | shinycssloaders |
| ggplot2 | ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics |
| raster | Create a RasterLayer object |
| sp | A package providing classes and methods for spatial data: points, lines, polygons and grids |
| grDevices | The R Graphics Devices and Support for Colours and Fontsshiny |
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Andras Sali (2017). shinycssloaders: Add CSS Loading Animations to 'shiny' Outputs. R package version 0.2.0. https://CRAN.R-project.org/package=shinycssloaders
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Dean Attali and Tristan Edwards (2018). shinyalert: Easily Create Pretty Popup Messages (Modals) in 'Shiny'. R package version 1.0. https://CRAN.R-project.org/package=shinyalert
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Eric Bailey (2015). shinyBS: Twitter Bootstrap Components for Shiny. R package version 0.61. https://CRAN.R-project.org/package=shinyBS
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Erich Neuwirth (2014). RColorBrewer: ColorBrewer Palettes. R package version 1.1-2. https://CRAN.R-project.org/package=RColorBrewer
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H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.
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Hadley Wickham (2018). stringr: Simple, Consistent Wrappers for Common String Operations. R package version 1.3.1. https://CRAN.R-project.org/package=stringr
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Pebesma, E.J., R.S. Bivand, 2005. Classes and methods for spatial data in R. R News 5 (2), https://cran.r-project.org/doc/Rnews/.
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Pfeffer, D.A., Lucas, T.C., May, D., Harris, J., Rozier, J., Twohig, K.A., Dalrymple, U., Guerra, C.A., Moyes, C.L., Thorn, M., Nguyen, M., et al. 2018. malariaAtlas: an R interface to global malariometric data hosted by the Malaria Atlas Project. Malaria Journal, 17(1), p.352.
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R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
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R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
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Robert J. Hijmans (2019). raster: Geographic Data Analysis and Modeling. R package version 2.8-19. https://CRAN.R-project.org/package=raster
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Winston Chang (2018). shinythemes: Themes for Shiny. R package version 1.1.2. https://CRAN.R-project.org/package=shinythemes
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Winston Chang and Barbara Borges Ribeiro (2018). shinydashboard: Create Dashboards with 'Shiny'. R package version 0.7.1. https://CRAN.R-project.org/package=shinydashboard
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Winston Chang, Joe Cheng, JJ Allaire, Yihui Xie and Jonathan McPherson (2018). shiny: Web Application Framework for R. R package version 1.2.0. https://CRAN.R-project.org/package=shiny