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R Shiny App (DHS-General)

There are two primary venues to utilize this R Shiny application:

  1. Web-Based Tool:

    • Location: Deployed on an online server.
    • Requirements: Internet access and a web browser.
    • Usage: Ideal for users who prefer quick access without local setup.

  2. Local R Package Installation:

    • Location: on user’s machine, launched by RStudio.
    • Requirements: R environment and dependent packages.
    • Usage: Suitable for users who wish to run the application directly within their local R environment. This method allows for enhanced customization.

Web-based R Shiny app

The R Shiny app is readily accessible via https://rsc.stat.washington.edu/surveyPrevRShiny/. The only requirement is a stable internet connection. This web-based deployment supports full functionality and serves as the primary distribution channel.

One advantage of the online version is that it includes preloaded shapefiles, reducing the need for manual uploads. While all versions require users to upload their own DHS survey datasets for analysis, currently the online version internally hosts the 2018 Nigeria DHS, 2022 Kenya DHS, and 2023 Senegal DHS (without the need for data upload!), with more datasets planned for future inclusion.

Installation of the R Shiny app as a R package

The procedure for installing and running sae4health on your local machine is described below. You can also find the most up-to-date documentation on our GitHub repository.

Some non-CRAN dependencies can be installed using the following command. We strongly recommend installing the most recent version of SUMMER and surveyPrev package from Github.

# install.packages("devtools")
devtools::install_github("richardli/SUMMER")
devtools::install_github("richardli/surveyPrev")

install.packages("INLA",repos=c(getOption("repos"),
                INLA="https://inla.r-inla-download.org/R/testing"),dep=TRUE)

sae4health will be published on CRAN soon. You can install the development version of sae4health with:

devtools::install_github("wu-thomas/sae4health")

Processing the analysis dataset for indicators, using specific coding schemes and handling labels, requires the following libraries to be preloaded before running the app:

library(labelled)
library(naniar)
library(sjlabelled)
library(dplyr)
library(data.table)
library(haven)

You can launch the R Shiny app with the following command, and we recommend opening a new browser tab from within the launched R Shiny app for better accessing web links.

library(sae4health)
sae4health::run_app()

If the colors in the interactive Leaflet maps appear inverted relative to the legend (e.g., regions with high values in the legend are shown in low-value colors), you can run the app with the following option. This issue arises due to differences in R and Leaflet package versions and is beyond our control.

sae4health::run_app(legend_color_reverse=T)