About

This chart visualizes measles cases across US states between 1928-2011 using a temporal heatmap. It highlights the impact of the 1963 measles vaccine introduction, demonstrating through historical public health data how vaccination successfully reduced disease incidence across the United States.

The visualization is based on historical public health records and clearly demonstrates the effectiveness of vaccination programs, providing insights into one of the most successful public health interventions in US history.

This chart was adapted from Ben Moore’s post. Thanks to him for sharing this insightful chart!

Load required libraries

This visualization only requires two R packages: dplyr for data preparation, and ggplot2 for creating the heatmap.

# Libraries
library(dplyr)
library(ggplot2)

Read and prepare the data

This code reads a CSV file containing measles cases per million inhabitants per year and US state. First, it imports the data using readr::read_csv(). See how the data is structured from the print() output. Then, it creates a new dataset “mdf” where states are converted to factors and arranged in reverse alphabetical order - this ordering will determine how states are displayed from top to bottom in our final heatmap.

# Read the data 
measles = readr::read_csv("https://raw.githubusercontent.com/holtzy/R-graph-gallery/refs/heads/master/measles_data_1928-2011.csv")

# Show the first few rows of the data
print(head(measles))

## # A tibble: 6 × 3
##    Year State  value
##   <dbl> <chr>  <dbl>
## 1  1928 Alaska  NA
## 2  1928 Ala.   335.
## 3  1928 Ark.   482.
## 4  1928 Ariz.  201.
## 5  1928 Calif.  69.2
## 6  1928 Colo.  207.

# Prepare the data: rename column and sort states alphabetically
mdf <- measles %>% 
  mutate(State = factor(State, levels = rev(sort(unique(State)))))

Create color palette

This code creates a custom color gradient for the heatmap that will represent different levels of measles cases. It combines two color palettes: a spectrum from light blue through deeper blues, green, and yellows/oranges for lower case counts up to 500, followed by an orange-to-red gradient for higher case counts from 500-4000. The colorRampPalette() function smoothly interpolates between these colors to create 100 total color steps.

cols <- c(
  colorRampPalette(c("#e7f0fa", "#c9e2f6", "#95cbee", "#0099dc", "#4ab04a", "#ffd73e", "#eec73a", "#e29421"))(20),
  colorRampPalette(c("#e29421", "#f05336", "#ce472e"))(80)
)

Create advanced temporal heatmap

This code generates a comprehensive temporal heatmap visualization in R using ggplot2 to display measles cases across US states from 1928 to 2011. It also highlights the year of vaccine introduction.

Core Plot Structure:

Creates a heatmap using ggplot2 with states on y-axis, years on x-axis, and case numbers determining color
Uses geom_tile() to create the rectangular cells with white borders

Color and Scale Settings:

Applies the custom color gradient defined earlier
Sets color scale limits from 0 to 4,000 cases per million
Formats legend labels with ‘k’ suffix (0k to 4k)

Timeline Features:

X-axis spans 1928-2012 with decade intervals
Adds black vertical line at 1963 (vaccine introduction)
Includes annotation “Vaccine introduced” near the line

Visual Styling:

Uses theme_minimal() with customized elements
Removes grid lines and unnecessary aesthetic elements
Sets horizontal legend at bottom of plot
Uses Helvetica font family throughout
Customizes text sizes (smaller for states, larger for years)

Title and Labels:

Adds main title “Measles cases per million by US state, 1928-2011”
Removes x and y-axis labels
Positions legend title “Cases per million” at top of color bar

ggplot(mdf, aes(x = Year, y = State, fill = value)) + 
geom_tile(colour = "white", linewidth = 0.5, 
            width = .9, height = .9) + 
theme_minimal() +
scale_fill_gradientn(colours = cols,
                    limits = c(0, 4000),
                    breaks = seq(0, 4000, by = 1000),
                    labels = c("0k", "1k", "2k", "3k", "4k"),
                    na.value = rgb(246/255, 246/255, 246/255),
                    guide = guide_colourbar(ticks = TRUE, 
                                          nbin = 50,
                                          barheight = .5, 
                                          label = TRUE, 
                                          barwidth = 10,
                                          title = "Cases per million",
                                          title.position = "top",
                                          title.hjust = 0.5)) +
scale_x_continuous(expand = c(0,0), 
                  breaks = seq(1930, 2010, by = 10),
                  limits = c(1928, 2012)) +
geom_vline(xintercept = 1963, color = "black", size = 0.5) +
  theme(legend.position = c(.5, -.13),
      legend.direction = "horizontal",
      legend.text = element_text(colour = "grey20"),
      plot.margin = grid::unit(c(.5,.5,1.5,.5), "cm"),
      axis.text.y = element_text(size = 6, family = "Helvetica", 
                                hjust = 1),
      axis.text.x = element_text(size = 8),
      axis.ticks.y = element_blank(),
      panel.grid = element_blank(),
      title = element_text(hjust = -.07, face = "bold", vjust = 1, 
                          family = "Helvetica"),
      text = element_text(family = "Helvetica")) +
ggtitle("Measles cases per million by US state, 1928-2011") +
annotate("text", label = "Vaccine introduced", x = 1963, y = 53, 
         vjust = 0.9, hjust = -0.1, size = I(3), family = "Helvetica") +
  xlab("") + ylab("")

Vaccination Impact Heatmap with R and ggplot2