Avian Influenza Bird Depopulations

Last updated: October 24, 2026

This page contains plots of the number of birds depopulated due to the highly pathogenic avian influenza (HPAI) outbreak. The USDA maintains a page tracking the number of confirmed HPAI detections in commercial and backyard flocks, as well as the number of “Birds Affected” in those flocks, meaning those birds have been killed or “depopulated” according to USDA policy. The data presented on this page comes from what appears to be a CDC mirror of the data, which shows the same data as of December 20, 2024. This data is used for context on the Metaculus forecasting question: How many farmed birds will be killed in the United States due to bird flu in 2025?

Click the “Code” buttons to see the R code used on this page. An R Markdown file of this page is available here for anyone who wishes to download and run or modify it themselves.

library(tidyverse)
library(lubridate)

# Download the CSV file
data_url <- "https://www.cdc.gov/bird-flu/modules/situation-summary/commercial-backyard-flocks.csv"
data <- read_csv(data_url)

# Categorize entries by whether they're Commercial or Non-commercial
data <- data %>%
  mutate(Category = if_else(str_detect(tolower(`Flock Type`), "commercial"), "Commercial", "Non-commercial"))

# Convert "Outbreak Date" to Date type
data <- data %>%
  mutate(`Outbreak Date` = parse_date_time(`Outbreak Date`, orders = "mdy"))

# Prepare data for cumulative sum plot
cumulative_data <- data %>%
  group_by(`Outbreak Date`, Category) %>%
  summarise(Flock_Size = sum(`Flock Size`, na.rm = TRUE), .groups = "drop") %>%
  pivot_wider(names_from = Category, values_from = Flock_Size, values_fill = 0) %>%
  arrange(`Outbreak Date`) %>%
  mutate(
    Cum_Commercial = cumsum(Commercial),
    Cum_Non_Commercial = cumsum(`Non-commercial`)
  ) %>%
  pivot_longer(cols = starts_with("Cum_"), names_to = "Category", values_to = "Cumulative_Flock_Size")

# Plot cumulative sum of flock sizes
cumulative_data <- cumulative_data %>%
  mutate(Category = case_when(
    Category == "Cum_Commercial" ~ "Commercial",
    Category == "Cum_Non_Commercial" ~ "Non-commercial",
    TRUE ~ Category
  ))

cumulative_plot <- ggplot(cumulative_data, aes(x = `Outbreak Date`, y = Cumulative_Flock_Size, 
                            fill = fct_rev(fct_relevel(Category, "Commercial", "Non-commercial")))) +
  geom_area(alpha = 0.7) +
  labs(
    title = "Cumulative HPAI Poultry Depopulated in the United States",
    x = "Date",
    y = "Cumulative Birds Depopulated",
    fill = "Category"
  ) +
  scale_y_continuous(labels = scales::comma, breaks = scales::pretty_breaks(n = 8)) +
  theme_minimal() +
  theme(
    axis.title.x = element_text(margin = margin(t = 10), size = 14),  # Add top margin to x-axis label
    axis.title.y = element_text(margin = margin(r = 10), size = 14),  # Add right margin to y-axis label
    plot.title = element_text(size = 18),
    axis.text.x = element_text(size = 12),
    axis.text.y = element_text(size = 12)
  )


# Prepare data for yearly bar graph
yearly_data <- data %>%
  mutate(Year = format(`Outbreak Date`, "%Y")) %>%
  group_by(Year, Category) %>%
  summarise(Flock_Size = sum(`Flock Size`, na.rm = TRUE), .groups = "drop")

current_year <- format(Sys.Date(), "%Y")

yearly_totals <- yearly_data %>%
  group_by(Year) %>%
  summarise(Total = sum(Flock_Size))

# Plot yearly bar graph
annual_plot <- ggplot(yearly_data, aes(x = Year, y = Flock_Size)) +  # Removed fill from global aes
  geom_bar(aes(fill = fct_relevel(Category, "Non-commercial", "Commercial")), 
           stat = "identity", position = "stack") +  # Added fill to geom_bar
  geom_text(
    data = yearly_totals,
    aes(y = Total, label = paste0("Total: ", scales::comma(Total))),
    vjust = -0.5, color = "black"
  ) +
  geom_text(
    data = yearly_data %>% filter(Category == "Non-commercial" & Year == current_year),
    aes(label = "Preliminary", y = -1000000),
    color = "red"
  ) +
  labs(
    title = "HPAI Poultry Depopulated by Year in the United States",
    x = "Year",
    y = "Birds Depopulated",
    fill = "Category"
  ) +
  scale_y_continuous(labels = scales::comma, breaks = scales::pretty_breaks(n = 8)) +
  theme_minimal() +
  theme(
    axis.title.x = element_text(margin = margin(t = 10), size = 14),  # Add top margin to x-axis label
    axis.title.y = element_text(margin = margin(r = 10), size = 14),  # Add right margin to y-axis label
    plot.title = element_text(size = 18),
    axis.text.x = element_text(size = 12),
    axis.text.y = element_text(size = 12)
  )

ggsave("cumulative_depopulations.png", cumulative_plot, width = 10, height = 6, dpi = 300, bg = "white")
ggsave("annual_depopulations.png", annual_plot, width = 10, height = 6, dpi = 300, bg = "white")