The purpose of this package is to make Kenya’s Demographic and Health Survey (DHS) indicators easier to explore and interpret. It brings long-run evidence on fertility, child survival, health services, HIV, malaria, education, gender and household conditions into one Shiny dashboard. The indicators were obtained from the Humanitarian Data Exchange and originate from The DHS Program.
The app is hosted on shinyapps.io and can be accessed here.
The dashboard connects a curated group of DHS indicators to the Sustainable Development Goals. The first page provides a quick view of the direction of the main trends. We can then select one indicator and read the survey years, published values, source, uncertainty availability and interpretation notes.
The full indicator catalogue is also included. This makes it possible to move from the policy overview to the published national series without presenting DHS data as a complete measure of Kenya’s development.
The plot below shows six of the indicators used in the overview. Each panel uses the indicator’s original unit and its own value scale. We should therefore compare the direction of the trends and not the steepness of one line with another.
This report is produced when README.Rmd is knitted. The scheduled
GitHub workflow refreshes the data, runs the tests and package check,
knits this README, commits the generated files and deploys the app.
| Item | Result |
|---|---|
| README generated | 2026-10-01 03:38 EAT |
| Latest DHS survey year | 2022 |
| Curated overview indicators | 16 |
| Indicators with repeated survey rounds | 15 |
| Indicators in the full catalogue | 1196 |
The first page is meant to be read quickly. The summary boxes filter the small trend charts by SDG theme or status. Each chart shows whether the indicator is improving, worsening or requires closer interpretation. It also states whether a higher or lower value is desirable.
When we hover over a trend we see its latest value and year. When we select it, the dashboard opens the full survey-year chart and the evidence details. The reading path is:
Scan the shapes -> identify the status -> check the latest value -> open the full evidence.
Status is calculated from the change between the first and latest available values in the curated national series. The direction is reversed for indicators such as mortality, unmet need and violence, where a lower value is desirable. A change of less than two percent from the baseline is labelled as little change.
An improving status does not mean that Kenya has reached an SDG target. It only means that the indicator moved in the desired direction over the survey years available. The status should be read together with confidence intervals, survey coverage and other indicators in the same policy area.
You can install the development version of kenyaIndicators from GitHub with:
# install.packages("remotes")
remotes::install_github("m-mburu/kenyaIndicators")After installing the package, run:
library(kenyaIndicators)
run_app()The project can also be run from the repository:
shiny::runApp()The dashboard has three main sections:
- Overview presents the curated SDG evidence as interactive small multiples.
- Explore indicators shows a fully labelled national trend for a selected indicator.
- Evidence coverage reports data quality, provides the indicator catalogue and identifies questions which require other datasets.
The package includes dhs_indicators, indicator_catalogue,
dashboard_timeline, hypothesis_map and kenya_counties as its main
data objects.
DHS data is collected in survey rounds rather than every year. A line between two survey years is a visual connection and not an estimate for the years between them. Some indicators have confidence intervals and denominators while others do not. The Evidence coverage section makes these differences visible.
The overview uses national series so that the first reading remains clear. National estimates can hide differences between counties and population groups. Questions on income, employment, climate, infrastructure and institutions also require companion datasets.
The application is organised as a golem package. The user interface is
in R/app_ui.R, server logic is in R/app_server.R, plotting functions
are in R/plots.R, and source-data preparation is in
data-raw/my_dataset.R.
devtools::test()
devtools::check()
rmarkdown::render("README.Rmd", output_format = "github_document")- The DHS Program for collecting and publishing Kenya’s demographic and health survey evidence.
- Humanitarian Data Exchange (HDX) for making the national indicator resources easier to access.
- Kenya National Bureau of Statistics and survey partners for producing the underlying survey data.