Introduction to Quarto

Leykun (MSc)1 & Yebelay (MSc)2

1NDMC, EPHI and 2DMU & C4ED


April 28 - May 1, 2026

What is Quarto?

  • Quarto is an open-source scientific and technical publishing system built on Pandoc
  • Successor to R Markdown with expanded capabilities
  • Supports multiple languages: R, Python, Julia, and Observable
  • Produces diverse outputs: reports, presentations, websites, books, and more
  • Publishes to multiple formats: HTML, PDF, and Word

Why Quarto?

  • Multilingual — works across R, Python, Julia, and Observable independently
  • Built-in by default — comes with themes, templates, and cross-referencing included; no plugins or configuration needed to get started
  • Single-source publishing — generate Word, PDF, and HTML from one source file
  • Consistent syntax — uniform syntax for core features across all formats
  • Extensible — a rich extension system for custom functionality
  • Accessible by default — outputs meet accessibility guidelines

Installation

  1. Ensure R and RStudio are installed
  2. Check if Quarto is already available — RStudio v2022.07+ includes Quarto by default:
   quarto::quarto_version()
  1. If not found, download and install from quarto.org/docs/get-started/

Anatomy of a Quarto document

.qmd file format with three components:

  1. YAML: Metadata

  2. Text: Markdown

  3. Code: R, Python, Observable, and Julia

Weave it all together, and you have beautiful, powerful, and useful outputs!

Anatomy of a Quarto document

Metadata: YAML

report.qmd
---
title: "Measles Surveillance: Ethiopia 2025"
format: html
---

Anatomy of a Quarto document

Metadata: YAML

report.qmd
---
title: "Measles Surveillance: Ethiopia 2026"
format: html
---
  • Metadata of your document
  • Demarcated by three dashes (---) on either end
  • Uses key-value pairs in the format key: value

Quarto document

Text: Markdown

report.qmd
---
title: "Measles Surveillance: Ethiopia 2025"
format: html
---

The 2025 National Integrated Measles Supplementary Immunization Campaign (SIAs) 
successfully reached **18.5 million children**. However, as we move through 
**February 2026**, surveillance data indicates localized "pockets" of 
transmission in conflict-affected and drought-prone woredas.

### Current Epidemiological Status

* **National MCV1 Coverage:** 71% (Target: >90%)
* **Key Drivers:** High concentration of "zero-dose" children in border regions.
* **Outbreak Alerts:** 5 active outbreaks reported in the first six weeks of 2026.
  • Markdown is a lightweight language for creating formatted text

Writing Content

  • Use Markdown syntax for formatting text:
    • Bold: **text**
    • Italic: *text*
    • Lists:
      • - Item 1
      • - Item 2

Creating a Quarto Document

  • Create a new file in RStudio: File -> New File -> Quarto Document.
  • Use the following YAML header:
---
title: "Document Title"
author: "Your Name"
format: html
---

Code

report.qmd
---
title: "Measles Surveillance: Ethiopia 2025"
format: html
---

The 2025 National Integrated Measles Supplementary Immunization Campaign (SIAs) 
successfully reached **18.5 million children**. However, as we move through 
**February 2026**, surveillance data indicates localized "pockets" of 
transmission in conflict-affected and drought-prone woredas.

```{r}
#| message: false
library(tidyverse)
measles |>
  ggplot(aes(x = date, y = measles_total)) +
  geom_line(color = "steelblue", linewidth = 0.9)
```
  • Code chunks begin and end with three backticks (usually)
  • Code chunks are identified with a programming language in between {}
  • Code can include optional chunk options, in YAML style, identified by #| at the beginning of the line

Code - Example: Monthly reported measles cases data

  • Embed R code chunks:
```{r}
#| label: setup
#| message: false
library(tidyverse)
```
```{r}
#| label: fig-monthly-cases
#| fig-cap: "Monthly reported measles cases in Ethiopia, 2012-2024"

measles <- read_csv("data/measles_ts_data.csv", show_col_types = FALSE)

measles |>
  ggplot(aes(x = date, y = measles_total)) +
  geom_line(color = "steelblue", linewidth = 0.9) +
  geom_point(color = "steelblue", size = 0.6) +
  labs(
    title = "Monthly Measles Cases (2012-2024)",
    x = "Date",
    y = "Total cases (monthly)"
  ) +
  scale_x_date(date_breaks = "2 year", date_labels = "%Y") +
  theme_minimal(base_size = 14) 
```

Figure 1: Monthly reported measles cases in Ethiopia, 2012-2024

Common Chunk Options:

  • #| echo: true (Show the code in the output)
  • #| echo: false (Hide the code, show only the output)
  • #| eval: false (Show the code, but don’t run it)
  • #| include: false (Hide code and results)
  • #| label: fig-plot (A unique label for the chunk)
  • #| fig-cap: "A caption for the figure." (Adds a figure caption)

Rendering and Sharing

  • Render your document: Click the Render button in RStudio.
  • Share as HTML, PDF, or Word document.
  • Use quarto render yourfile.qmd in the terminal for command line rendering.

Exercise 1: MCV1 Coverage Report

Task: Using measles_demo.csv, create a one-page summary report (.qmd) that:

  1. Calculates MCV1 vaccination coverage (%) grouped by region
  2. Displays the results in a summary table
  3. Produces a horizontal bar chart of coverage by region
  4. Renders to HTML and Word (.docx) formats

Exercise 2: YRBSS summary report

Task: Using yrbss.csv, create a one-page summary report (.qmd) that:

  1. Selects variables: sex, grade, race4, and bmi
  2. Produces a publication-ready descriptive statistics table stratified by sex using gtsummary
  3. Adds an Overall column and p-values
  4. Renders to docx

Note

Hint: Use tbl_summary(by = sex) → add_p() → add_overall() → bold_labels() → italicize_levels().