CDCAtlas provides R functions for retrieving public health surveillance data from CDC AtlasPlus. This vignette introduces installation, basic queries, and data handling.
Installation
# install.packages("remotes")
remotes::install_github("VagishHemmige/CDCAtlas")Example: State-level chlamydia data
library(CDCAtlas)
df <- get_atlas(
disease = "chlamydia",
geography = "state",
year = 2022
)
head(df)
#> indicator year geography data_status race_ethnicity sex
#> 1 Chlamydia 2022 Alabama Not Suppressed All races/ethnicities Both sexes
#> 2 Chlamydia 2022 Alaska Not Suppressed All races/ethnicities Both sexes
#> 3 Chlamydia 2022 Arizona Not Suppressed All races/ethnicities Both sexes
#> 4 Chlamydia 2022 Arkansas Not Suppressed All races/ethnicities Both sexes
#> 5 Chlamydia 2022 California Not Suppressed All races/ethnicities Both sexes
#> 6 Chlamydia 2022 Colorado Not Suppressed All races/ethnicities Both sexes
#> age transmission rate100000 cases population
#> 1 All age groups All transmission categories 612.1 31060 5074296
#> 2 All age groups All transmission categories 727.7 5338 733583
#> 3 All age groups All transmission categories 554.4 40796 7359197
#> 4 All age groups All transmission categories 588.3 17918 3045637
#> 5 All age groups All transmission categories 493.6 192647 39029342
#> 6 All age groups All transmission categories 456.3 26646 5839926
#> lowerci_rate upperci_rate rse lowerci_cases upperci_cases fips
#> 1 NA NA NA NA NA 01
#> 2 NA NA NA NA NA 02
#> 3 NA NA NA NA NA 04
#> 4 NA NA NA NA NA 05
#> 5 NA NA NA NA NA 06
#> 6 NA NA NA NA NA 08Simple visualization
library(ggplot2)
ggplot(df, aes(x = geography, y = rate100000)) +
geom_col() +
coord_flip() +
labs(
title = "Chlamydia Rate by State (2022)",
x = "State",
y = "Rate per 100,000"
)
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
Next steps
- Try different diseases or geographies
- See
?get_atlasfor full argument documentation - More vignettes coming soon!