Interactive Dashboard for 'HIV' Data Visualization

An interactive 'Shiny' dashboard for visualizing and exploring key metrics related to HIV/AIDS, including prevalence, incidence, mortality, and treatment coverage. The dashboard is designed to work with a dataset containing specific columns with standardized names. These columns must be present in the input data for the app to function properly: year: Numeric year of the data (e.g. 2010, 2021); sex: Gender classification (e.g. Male, Female); age_group: Age bracket (e.g. 15–24, 25–34); hiv_prevalence: Estimated HIV prevalence percentage; hiv_incidence: Number of new HIV cases per year; aids_deaths: Total AIDS-related deaths; plhiv: Estimated number of people living with HIV; art_coverage: Percentage receiving antiretroviral therapy (ART); testing_coverage: HIV testing services coverage; causes: Description of likely HIV transmission cause (e.g. unprotected sex, drug use). The dataset structure must strictly follow this column naming convention for the dashboard to render correctly.

📊 HIViz

An R package for interactive visualization and exploration of key HIV/AIDS indicators, including prevalence, incidence, mortality, and treatment coverage, via a Shiny dashboard.

📁 Required Dataset Structure

The input dataset must include the following columns with exact names:

• country: (e.g., Iran, Spain)
• year: Numeric year (e.g., 2010, 2021)
• sex: Gender classification (e.g., Male, Female)
• age_group: Age brackets (e.g., 15–24, 25–34)
• hiv_prevalence: Estimated HIV prevalence (%)
• hiv_incidence: Number of new HIV cases
• aids_deaths: AIDS-related deaths
• plhiv: People living with HIV
• art_coverage: ART (antiretroviral therapy) coverage rate
• testing_coverage: HIV testing coverage (%)
• causes: Categorical variable describing cause of transmission (e.g., unprotected sex, drug use, mother-to-child)

All column names must be spelled exactly as listed. The causes column should contain clear, human-readable labels for transmission modes.

Installation

The development version of the 'HIViz' package is available for installation. You can install it from Github using:

# install.packages("remotes")
remotes::install_github("AtefehRashidi/HIViz")

Installation

You can install the development version of HIViz from GitHub with:

# install pak if not installed:
install.packages("pak")

# then install HIViz from GitHub:
pak::pak("AtefehRashidi/HIViz")

Then run the Shiny App with:

HIViz::launchApp()

You can test the dashboard with the built-in sample_data.

🤝 Contributing

Issues and pull requests are welcome. Please open an issue to report bugs or suggest enhancements.