At the 2025 Annual Meeting, one of the highlights was the demonstration of a new R Shiny application developed by the Countdown partnership and APHRC. This tool represents a major step forward in making routine health data analysis more accessible, user-friendly, and impactful for countries. This video describes the advantages of the app:

Why the Shiny App?

For years, Countdown partners have worked with ministries of health and research institutions to strengthen their capacity to analyze and use routine health facility data. Earlier tools included Excel dashboards and Stata codes, but these required specialized software and technical skills. The new R Shiny App builds on this history, offering an interactive, browser-based platform that removes many of the barriers to entry. With just a few setup steps in R and RStudio, users can launch the dashboard in their browser, upload their datasets, and immediately begin exploring health system performance and service coverage trends.

As  Dr. Hannah Kagiri from Kenya’s Ministry of Health official reflected: “This is a truly amazing tool—the best innovation so far. It makes our work very easy, and it is fully aligned with Countdown’s goals to improve country capacity.”

What Can the App Do?

The Shiny App walks users through the full analytical workflow of routine health data: from quality checks to adjustments to advanced analyses. Key features include:

• Data Quality Checks: Assess reporting rates, detect outliers, check internal consistency, and measure completeness.
• Data Adjustment: Apply adjustments (such as reporting rate corrections) and track changes.
• National and Subnational Analysis: Generate coverage outputs, compare against global targets, and examine inequalities by region, education, or wealth.
• Mapping and Visualization: Create subnational maps of coverage, mortality, and service utilization.
• Equity Assessments: Explore differences by geography, socioeconomic group, or other stratifiers.
• Health System Performance: Analyze service delivery indicators, compare national and subnational systems, and examine public vs. private sector contributions.

All of this is done within one integrated dashboard, with outputs displayed interactively and exportable for reporting or advocacy.

How to Use It

STEP 1: INSTALL R AND RStudio.  The Shiny App runs through R (the statistical programming language) and RStudio (the integrated development environment).

• Download R: https://cran.r-project.org
• Download RStudio: https://posit.co/download/rstudio-desktop

Once both are installed, open RStudio.

STEP 2: LOAD THE PACKAGE. The Shiny App is packaged within the Countdown 2030 R library. Begin by ensuring you have the devtools package installed. Install and load the Countdown 2030 Shiny package.

STEP 3: LAUNCH THE DASHBOARD.  Once the package is loaded, the app can be launched with a single command: (dashboard()). This will automatically open the app in your default web browser.

App launched in the brower. The left navigation pane shows all the analytical steps that can be taken and the outputs that will be generated.

STEP 4: UPLOAD YOUR DATA. The first tab of the app is the Introduction and Load Data screen. Here you can:

• Upload health facility data (DHIS2 extracts, for example).
• Upload UN estimates and mortality data (stored in the provided UN folder).
• Upload survey data (as a folder).

The app includes error checks: if your file has problems, the app will display a message with documentation on how to fix common errors.

STEP 5: RUN ANALYSES. Once data are uploaded, you can proceed step by step:

Data Quality Checks

• Reporting rates
• Outlier detection
• Internal consistency
• Data completeness
• Ratio calculations

Data Adjustment

• Apply reporting-rate adjustments
• Track changes in an adjustment summary tab

Analysis Setup

• Specify denominators (e.g., Penta1 for vaccination coverage, DHS2 for maternal indicators).
• Upload survey and population files.

National and Subnational Analysis

• Generate coverage outputs at national and district level.
• Compare against global coverage targets.
• Explore inequalities by wealth quintile, education, or area.

Mapping and Equity Assessment

• Create maps by year, region, and indicator.
• Visualize equity gaps and coverage distribution.

Mortality and Service Utilization

• Analyze institutional mortality, mortality completeness, and service utilization indicators at national and subnational levels.

Health System Performance

• Assess national and subnational health system indicators.
• Compare public vs. private sector contributions.

 STEP 6: EXPORT RESULTS AND INTERPRET WITH GUIDANCE. Each analysis tab displays interactive graphs and tables. These can be exported for reports or presentations. For detailed interpretation guidance, use the “Get Help” button in the app. This links directly to the Countdown Guidebook hosted on GitHub, which explains methodology, definitions, and recommended use of outputs.

Watch the detailed tutorial video:

Why It Matters

For countries, the ability to quickly and reliably analyze routine data is crucial for:

• Monitoring progress toward global and national targets.
• Identifying inequities in coverage and access.
• Strengthening accountability in maternal, newborn, child, and adolescent health.
• Supporting decision-making with up-to-date, locally generated evidence.

By reducing reliance on specialized coding skills and making outputs accessible at the click of a button, the Shiny App empowers ministries, researchers, and partners to turn routine data into actionable insights.

Accessing the App

The Shiny App and related guidance are free and publicly available. The full package, documentation, and manuals can be accessed through the Countdown GitHub repository. A QR code linking to the guidebook is also included in the app interface.

Looking Ahead

The launch of this R Shiny App is part of Countdown’s broader mission: to strengthen country capacities to analyze, interpret, and use data for accountability and advocacy. By making powerful analytical tools more accessible, we are helping ensure that data serves its ultimate purpose: improving the health and lives of women, children, and adolescents.

For examples of outputs from the app, see the reports from the 2025 annual meeting.